From 35d62876e986dbb4ec2e6ccebabefdbfb7436047 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 11 Feb 2025 11:43:00 +0200 Subject: [PATCH 01/85] diabetes module and test file --- src/tlo/methods/diabetes_retionopathy.py | 181 +++++++++++++++++++++++ tests/test_diabetes_retinopathy.py | 44 ++++++ 2 files changed, 225 insertions(+) create mode 100644 src/tlo/methods/diabetes_retionopathy.py create mode 100644 tests/test_diabetes_retinopathy.py diff --git a/src/tlo/methods/diabetes_retionopathy.py b/src/tlo/methods/diabetes_retionopathy.py new file mode 100644 index 0000000000..98eb0ca3b8 --- /dev/null +++ b/src/tlo/methods/diabetes_retionopathy.py @@ -0,0 +1,181 @@ +from pathlib import Path + +import pandas as pd + +from tlo import Module, Simulation, Parameter, Types, Property, Population +from tlo.events import RegularEvent, PopulationScopeEventMixin +from tlo.methods import Metadata + + +class Diabetes_Retinopathy(Module): + """ This is Diabetes Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ + + INIT_DEPENDENCIES = {'SymptomManager', 'Lifestyle', 'HealthSystem', 'CardioMetabolicDisorders'} + ADDITIONAL_DEPENDENCIES = set() + + METADATA = { + Metadata.DISEASE_MODULE, + Metadata.USES_SYMPTOMMANAGER, + Metadata.USES_HEALTHSYSTEM, + Metadata.USES_HEALTHBURDEN, + } + + # define a dictionary of parameters this module will use + PARAMETERS = { + 'rate_onset_to_early_dr': Parameter(Types.REAL, 'Probability to dr'), + 'rate_progression_to_dr': Parameter(Types.REAL, 'Probability to dr'), + 'prob_fast_dr': Parameter(Types.REAL, 'Probability to dr'), + 'init_prob_any_dr': Parameter(Types.REAL, 'Probability to dr'), + 'init_prob_late_dr': Parameter(Types.REAL, 'Probability to dr'), + } + + # define a dictionary of properties this module will use + PROPERTIES = { + "dr_status": Property( + Types.CATEGORICAL, + categories=[ + "none", + "early", + "late", + ], + description="dr status", + ), + } + + def __init__(self): + # this method is included to define all things that should be initialised first + super().__init__() + + + def read_parameters(self, data_folder: str | Path) -> None: + """ initialise module parameters. Here we are assigning values to all parameters defined at the beginning of + this module. For this demo module, we will manually assign values to parameters but in the + Thanzi model we do this by reading from an Excel file containing parameter names and values + + :param data_folder: Path to the folder containing parameter values + + """ + self.parameters['rate_onset_to_early_dr'] = 0.5 + self.parameters['rate_progression_to_dr'] = 0.5 + self.parameters['prob_fast_dr'] = 0.5 + self.parameters['init_prob_any_dr'] = 0.5 + self.parameters['init_prob_late_dr'] = 0.5 + + def initialise_population(self, population: Population) -> None: + """ set the initial state of the population. The state will be update over time + + :param population: all individuals in the model + + """ + df = population.props + p = self.parameters + + + alive_diabetes_idx = df.loc[df.is_alive & df.nc_diabetes].index + + any_dr_idx = alive_diabetes_idx[ + self.rng.random_sample(size=len(alive_diabetes_idx)) < self.parameters['init_prob_any_dr'] + ] + no_dr_idx = set(alive_diabetes_idx) - set(any_dr_idx) + + late_dr_idx = any_dr_idx[ + self.rng.random_sample(size=len(any_dr_idx)) < self.parameters['init_prob_late_dr'] + ] + + early_dr_idx = set(any_dr_idx) - set(late_dr_idx) + + # write to property: + df.loc[df.is_alive & ~df.nc_diabetes, 'dr_status'] = 'none' + df.loc[list(no_dr_idx), 'dr_status'] = 'none' + df.loc[list(early_dr_idx), "dr_status"] = "early" + df.loc[list(late_dr_idx), "dr_status"] = "late" + + + + + + def initialise_simulation(self, sim: Simulation) -> None: + """ This is where you should include all things you want to be happening during simulation + + :param sim: simulation object + + """ + # schedule an event to infect people with tb + sim.schedule_event(DrPollEvent(self), date=sim.date + pd.DateOffset(years=3)) + # sim.schedule_event(TblInfectionEvent(self), date=sim.date + pd.DateOffset(months=1)) + # schedule an event to cure people from tb + sim.schedule_event(TblCureEvent(self), date=sim.date + pd.DateOffset(months=2)) + + def on_birth(self, mother_id: int, child_id: int) -> None: + """ set properties of a child when they are born. """ + pass + + def on_simulation_end(self) -> None: + tb_inc_and_prev = pd.DataFrame(index=list(self.incidence_tb.keys()), + data={'incidence': self.incidence_tb.values(), + 'prevalence': self.prevalence_tb.values(), + 'total_pop': len(self.sim.population.props)}) + + print(f'\n\nrunning the model with infection probability at {self.parameters["p_infection"]}') + print(tb_inc_and_prev) + + +class DrPollEvent(RegularEvent, PopulationScopeEventMixin): + """An event that controls the development process of Diabetes Retionpathy (DR) and logs current states. DR diagnosis + begins at least after 3 years of being infected with Diabetes Mellitus.""" + + def __init__(self, module): + super().__init__(module, frequency=pd.DateOffset(months=3)) + +class TblInfectionEvent(RegularEvent, PopulationScopeEventMixin): + """ cause individuals to be infected by Tb. This event will run every one month """ + + def __init__(self, module: Module) -> None: + self.repeat = 1 + super().__init__(module, frequency=pd.DateOffset(months=self.repeat)) + + def apply(self, population: Population) -> None: + """ actions that should be applied to the population when this event is triggered """ + df = population.props + + # select individuals to infect. should be those without tb at the present time + individuals_to_infect = ~df['tbl_is_infected'] + random_selection = self.module.rng.choice([True, False], size=len(individuals_to_infect), + p=[self.module.parameters['p_infection'], + 1 - self.module.parameters['p_infection']]) + + # update the properties of individuals that have been selected for tb infection + idx_individuals_to_infect = individuals_to_infect.index[random_selection] + df.loc[idx_individuals_to_infect, 'tbl_is_infected'] = True + df.loc[idx_individuals_to_infect, 'tbl_date_infected'] = self.sim.date + + # incidence of Tb + self.module.incidence_tb.update({self.sim.date: len(idx_individuals_to_infect)}) + self.module.prevalence_tb.update({self.sim.date: df.tbl_is_infected.sum()}) + + +class TblCureEvent(RegularEvent, PopulationScopeEventMixin): + """ cause individuals to recover from Tb. This event will run every one month """ + + def __init__(self, module: Module) -> None: + self.repeat = 1 + super().__init__(module, frequency=pd.DateOffset(months=self.repeat)) + self.module = module + + def apply(self, population: Population) -> None: + """ actions that should be applied to the population when this event is triggered """ + df = population.props + + # select individuals to recover. should be those with tb and infected not less than a month ago + individuals_to_recover = df.loc[df.tbl_is_infected & + (self.sim.date - pd.DateOffset(months=1) > df.tbl_date_infected)] + + random_selection = self.module.rng.choice([True, False], size=len(individuals_to_recover), + p=[self.module.parameters['p_cure'], + 1 - self.module.parameters['p_cure']]) + + # update the properties of individuals that have been selected for tb cure. + # they should be well and have a date of recovery + idx_individuals_to_recover = individuals_to_recover.index[random_selection] + df.loc[idx_individuals_to_recover, 'tbl_is_infected'] = False + df.loc[idx_individuals_to_recover, 'tbl_date_cure'] = self.sim.date diff --git a/tests/test_diabetes_retinopathy.py b/tests/test_diabetes_retinopathy.py new file mode 100644 index 0000000000..6398fecfb9 --- /dev/null +++ b/tests/test_diabetes_retinopathy.py @@ -0,0 +1,44 @@ +import os +from pathlib import Path + +import pytest + +from tlo import Date, Simulation +from tlo.methods import cardio_metabolic_disorders, demography, enhanced_lifestyle, simplified_births, healthsystem, \ + symptommanager, healthseekingbehaviour, healthburden, diabetes_retionopathy, depression + +resourcefilepath = Path(os.path.dirname(__file__)) / '../resources' +start_date = Date(2010, 1, 1) +end_date = Date(2010, 1, 2) +@pytest.mark.slow +def test_basic_run(tmpdir, seed, diabetes_retinopathy=None): + """Run the simulation with the Copd module and read the log from the Copd module.""" + + popsize = 1000 + sim = Simulation( + start_date=start_date, + seed=seed, + log_config={ + 'filename': 'temp', + 'directory': tmpdir, + }, + ) + + sim.register(demography.Demography(resourcefilepath=resourcefilepath), + simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), + enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), + healthsystem.HealthSystem(resourcefilepath=resourcefilepath, + disable=False, + cons_availability='all'), + symptommanager.SymptomManager(resourcefilepath=resourcefilepath), + healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath, + # force symptoms to lead to health care seeking: + force_any_symptom_to_lead_to_healthcareseeking=True + ), + healthburden.HealthBurden(resourcefilepath=resourcefilepath), + cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + diabetes_retionopathy.Diabetes_Retinopathy(), + depression.Depression(resourcefilepath=resourcefilepath), + ) + sim.make_initial_population(n=popsize) + sim.simulate(end_date=Date(2010, 2, 1)) # Long run From fd4fa73ae4add1aac0740029daf4fda719da87ae Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 11 Feb 2025 15:25:42 +0200 Subject: [PATCH 02/85] Add HSI and appointment --- src/tlo/methods/diabetes_retionopathy.py | 203 ++++++++++++++++------- 1 file changed, 145 insertions(+), 58 deletions(-) diff --git a/src/tlo/methods/diabetes_retionopathy.py b/src/tlo/methods/diabetes_retionopathy.py index 98eb0ca3b8..5b6662b822 100644 --- a/src/tlo/methods/diabetes_retionopathy.py +++ b/src/tlo/methods/diabetes_retionopathy.py @@ -1,11 +1,18 @@ from pathlib import Path +from typing import List import pandas as pd -from tlo import Module, Simulation, Parameter, Types, Property, Population -from tlo.events import RegularEvent, PopulationScopeEventMixin +from tlo import Module, Simulation, Parameter, Types, Property, Population, logging +from tlo.events import RegularEvent, PopulationScopeEventMixin, IndividualScopeEventMixin +from tlo.lm import LinearModel, LinearModelType from tlo.methods import Metadata +from tlo.methods.hsi_event import HSI_Event +from tlo.methods.hsi_generic_first_appts import HSIEventScheduler +from tlo.methods.symptommanager import Symptom +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) class Diabetes_Retinopathy(Module): """ This is Diabetes Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ @@ -40,6 +47,20 @@ class Diabetes_Retinopathy(Module): ], description="dr status", ), + 'dr_on_treatment': Property( + Types.BOOL, 'Whether this person will die during a current severe exacerbation' + ), + 'dr_early_diagnosed': Property( + Types.BOOL, 'Whether this person will die during a current severe exacerbation' + ), + 'dr_late_diagnosed': Property( + Types.BOOL, 'Whether this person will die during a current severe exacerbation' + ), + 'dr_diagnosed': Property( + Types.BOOL, 'Whether this person will die during a current severe exacerbation' + ), + 'p_medication': Parameter( + Types.REAL, 'Probability that a treatment is successful in curing the individual'), } def __init__(self): @@ -60,6 +81,12 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['prob_fast_dr'] = 0.5 self.parameters['init_prob_any_dr'] = 0.5 self.parameters['init_prob_late_dr'] = 0.5 + self.parameters['p_medication'] = 0.4 + + self.sim.modules['SymptomManager'].register_symptom( + Symptom(name='blindness_partial'), # will not trigger any health seeking behaviour + Symptom(name='blindness_full') + ) def initialise_population(self, population: Population) -> None: """ set the initial state of the population. The state will be update over time @@ -89,9 +116,8 @@ def initialise_population(self, population: Population) -> None: df.loc[list(no_dr_idx), 'dr_status'] = 'none' df.loc[list(early_dr_idx), "dr_status"] = "early" df.loc[list(late_dr_idx), "dr_status"] = "late" - - - + df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False + df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False def initialise_simulation(self, sim: Simulation) -> None: @@ -100,82 +126,143 @@ def initialise_simulation(self, sim: Simulation) -> None: :param sim: simulation object """ - # schedule an event to infect people with tb - sim.schedule_event(DrPollEvent(self), date=sim.date + pd.DateOffset(years=3)) - # sim.schedule_event(TblInfectionEvent(self), date=sim.date + pd.DateOffset(months=1)) - # schedule an event to cure people from tb - sim.schedule_event(TblCureEvent(self), date=sim.date + pd.DateOffset(months=2)) + sim.schedule_event(DrPollEvent(self), date=sim.date) + + self.make_the_linear_models() + + + def report_daly_values(self) -> pd.Series: + return pd.Series(index=self.sim.population.props.index, data=0.0) def on_birth(self, mother_id: int, child_id: int) -> None: """ set properties of a child when they are born. """ - pass + self.sim.population.props.at[child_id, 'dr_status'] = 'none' + self.sim.population.props.at[child_id, 'dr_on_treatment'] = False + self.sim.population.props.at[child_id, 'dr_diagnosed'] = False + self.sim.population.props.at[child_id, 'dr_diagnosis_date'] = pd.NaT + def on_simulation_end(self) -> None: - tb_inc_and_prev = pd.DataFrame(index=list(self.incidence_tb.keys()), - data={'incidence': self.incidence_tb.values(), - 'prevalence': self.prevalence_tb.values(), - 'total_pop': len(self.sim.population.props)}) + pass - print(f'\n\nrunning the model with infection probability at {self.parameters["p_infection"]}') - print(tb_inc_and_prev) + def make_the_linear_models(self) -> None: + """Here is where we make and save LinearModels that will be used when the module is running""" + self.lm = dict() + + self.lm['onset_early_dr'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + intercept=self.parameters['rate_onset_to_early_dr'] + ) + + self.lm['onset_late_dr'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + intercept=self.parameters['rate_progression_to_dr'] + ) + + self.lm['onset_fast_dr'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + intercept=self.parameters['prob_fast_dr'] + ) class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retionpathy (DR) and logs current states. DR diagnosis begins at least after 3 years of being infected with Diabetes Mellitus.""" def __init__(self, module): - super().__init__(module, frequency=pd.DateOffset(months=3)) - -class TblInfectionEvent(RegularEvent, PopulationScopeEventMixin): - """ cause individuals to be infected by Tb. This event will run every one month """ - - def __init__(self, module: Module) -> None: - self.repeat = 1 - super().__init__(module, frequency=pd.DateOffset(months=self.repeat)) + super().__init__(module, frequency=pd.DateOffset(months=1)) def apply(self, population: Population) -> None: - """ actions that should be applied to the population when this event is triggered """ + """ + + """ df = population.props - # select individuals to infect. should be those without tb at the present time - individuals_to_infect = ~df['tbl_is_infected'] - random_selection = self.module.rng.choice([True, False], size=len(individuals_to_infect), - p=[self.module.parameters['p_infection'], - 1 - self.module.parameters['p_infection']]) + diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] + diabetes_and_alive_earlydr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'early')] - # update the properties of individuals that have been selected for tb infection - idx_individuals_to_infect = individuals_to_infect.index[random_selection] - df.loc[idx_individuals_to_infect, 'tbl_is_infected'] = True - df.loc[idx_individuals_to_infect, 'tbl_date_infected'] = self.sim.date + will_progress = self.module.lm['onset_early_dr'].predict(diabetes_and_alive_nodr, self.module.rng) + will_progress_idx = will_progress[will_progress].index + df.loc[will_progress_idx, 'dr_status'] = 'early' - # incidence of Tb - self.module.incidence_tb.update({self.sim.date: len(idx_individuals_to_infect)}) - self.module.prevalence_tb.update({self.sim.date: df.tbl_is_infected.sum()}) + early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) + early_to_late_idx = early_to_late[early_to_late].index + df.loc[early_to_late_idx, 'dr_status'] = 'late' + fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) + fast_dr_idx = fast_dr[fast_dr].index + df.loc[fast_dr_idx, 'dr_status'] = 'late' -class TblCureEvent(RegularEvent, PopulationScopeEventMixin): - """ cause individuals to recover from Tb. This event will run every one month """ + if len(will_progress_idx): + self.sim.modules['SymptomManager'].change_symptom( + person_id=will_progress_idx, + symptom_string='blindness_partial', + add_or_remove='+', + disease_module=self, + ) - def __init__(self, module: Module) -> None: - self.repeat = 1 - super().__init__(module, frequency=pd.DateOffset(months=self.repeat)) - self.module = module + if len(early_to_late_idx): + self.sim.modules['SymptomManager'].change_symptom( + person_id=early_to_late_idx, + symptom_string='blindness_full', + add_or_remove='+', + disease_module=self, + ) - def apply(self, population: Population) -> None: - """ actions that should be applied to the population when this event is triggered """ - df = population.props + def do_at_generic_first_appt_emergency( + self, + person_id: int, + symptoms: List[str], + schedule_hsi_event: HSIEventScheduler, + **kwargs, + ) -> None: + # Example for mockitis + if "blindness_full" in symptoms or "blindness_partial" in symptoms: + event = HSI_Dr_StartTreatment( + module=self, + person_id=person_id, + ) + schedule_hsi_event(event, priority=1, topen=self.sim.date) + + + + +class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): + """ + This is a Health System Interaction Event. + + It is appointment at which treatment for mockitiis is inititaed. + + """ + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + assert isinstance(module, Diabetes_Retinopathy) + + # Define the necessary information for an HSI + self.TREATMENT_ID = 'Mockitis_Treatment_Initiation' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) + self.ACCEPTED_FACILITY_LEVEL = '1a' + self.ALERT_OTHER_DISEASES = [] + def apply(self, person_id, squeeze_factor): + logger.debug(key='debug', + data=f'This is HSI_Dr_StartTreatment: initiating treatment for person {person_id}') + df = self.sim.population.props + person = df.loc[person_id] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + treatment_slows_progression_to_late = self.module.rng.rand() < self.module.parameters['p_medication'] + + #TODO Add consumables in codition below + if treatment_slows_progression_to_late: + df.at[person_id, 'dr_on_treatment'] = True - # select individuals to recover. should be those with tb and infected not less than a month ago - individuals_to_recover = df.loc[df.tbl_is_infected & - (self.sim.date - pd.DateOffset(months=1) > df.tbl_date_infected)] - random_selection = self.module.rng.choice([True, False], size=len(individuals_to_recover), - p=[self.module.parameters['p_cure'], - 1 - self.module.parameters['p_cure']]) - # update the properties of individuals that have been selected for tb cure. - # they should be well and have a date of recovery - idx_individuals_to_recover = individuals_to_recover.index[random_selection] - df.loc[idx_individuals_to_recover, 'tbl_is_infected'] = False - df.loc[idx_individuals_to_recover, 'tbl_date_cure'] = self.sim.date From 97487a0c14cff2014c22694e6f45e84454f7efd1 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 11 Feb 2025 15:32:28 +0200 Subject: [PATCH 03/85] Add HSI and appointment fix --- src/tlo/methods/diabetes_retionopathy.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/tlo/methods/diabetes_retionopathy.py b/src/tlo/methods/diabetes_retionopathy.py index 5b6662b822..012cc16caf 100644 --- a/src/tlo/methods/diabetes_retionopathy.py +++ b/src/tlo/methods/diabetes_retionopathy.py @@ -34,6 +34,7 @@ class Diabetes_Retinopathy(Module): 'prob_fast_dr': Parameter(Types.REAL, 'Probability to dr'), 'init_prob_any_dr': Parameter(Types.REAL, 'Probability to dr'), 'init_prob_late_dr': Parameter(Types.REAL, 'Probability to dr'), + 'p_medication': Parameter(Types.REAL, 'Probability to dr'), } # define a dictionary of properties this module will use @@ -59,8 +60,7 @@ class Diabetes_Retinopathy(Module): 'dr_diagnosed': Property( Types.BOOL, 'Whether this person will die during a current severe exacerbation' ), - 'p_medication': Parameter( - Types.REAL, 'Probability that a treatment is successful in curing the individual'), + } def __init__(self): @@ -198,7 +198,7 @@ def apply(self, population: Population) -> None: person_id=will_progress_idx, symptom_string='blindness_partial', add_or_remove='+', - disease_module=self, + disease_module=self.module, ) if len(early_to_late_idx): @@ -206,7 +206,7 @@ def apply(self, population: Population) -> None: person_id=early_to_late_idx, symptom_string='blindness_full', add_or_remove='+', - disease_module=self, + disease_module=self.module, ) def do_at_generic_first_appt_emergency( From df1b1166bd060d179f30b79692d499ebe7e97b51 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 14 Feb 2025 16:47:42 +0200 Subject: [PATCH 04/85] Adding DR analyses file --- .../diabetic_retinopathy_analyses.py | 169 ++++++++++++++++++ src/tlo/methods/diabetes_retionopathy.py | 130 ++++++++++---- 2 files changed, 260 insertions(+), 39 deletions(-) create mode 100644 src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py new file mode 100644 index 0000000000..542f52ab17 --- /dev/null +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -0,0 +1,169 @@ +""" +* Check key outputs for reporting in the calibration table of the write-up +* Produce representative plots for the default parameters + +NB. To see larger effects +* Increase incidence of cancer (see tests) +* Increase symptom onset (r_urinary_symptoms_prostate_ca or r_pelvic_pain_symptoms_local_ln_prostate_ca) +* Increase progression rates (see tests) +""" + +import datetime +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd + +from tlo import Date, Simulation +from tlo.analysis.utils import make_age_grp_types, parse_log_file +from tlo.methods import ( + care_of_women_during_pregnancy, + contraception, + demography, + enhanced_lifestyle, + healthburden, + healthseekingbehaviour, + healthsystem, + labour, + newborn_outcomes, + oesophagealcancer, + postnatal_supervisor, + pregnancy_supervisor, + prostate_cancer, + symptommanager, + diabetes_retionopathy, + hiv, tb, epi, + cardio_metabolic_disorders, + depression, +) + +# Where will outputs go +outputpath = Path("./outputs") # folder for convenience of storing outputs + +# date-stamp to label log files and any other outputs +datestamp = datetime.date.today().strftime("__%Y_%m_%d") + +# The resource files +resourcefilepath = Path("./resources") + +# Set parameters for the simulation +start_date = Date(2010, 1, 1) +end_date = Date(2010, 6, 6) +popsize = 5000 + + +def run_sim(service_availability): + log_config = { + 'filename': 'LogFile', + 'directory': outputpath + } + # Establish the simulation object and set the seed + # sim = Simulation(start_date=start_date, seed=0, log_config=log_config) + sim = Simulation(start_date=start_date, log_config={"filename": "LogFile"}) + + # Register the appropriate modules + sim.register(care_of_women_during_pregnancy.CareOfWomenDuringPregnancy(resourcefilepath=resourcefilepath), + demography.Demography(resourcefilepath=resourcefilepath), + contraception.Contraception(resourcefilepath=resourcefilepath), + enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), + healthsystem.HealthSystem(resourcefilepath=resourcefilepath, + service_availability=service_availability), + symptommanager.SymptomManager(resourcefilepath=resourcefilepath), + healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath), + healthburden.HealthBurden(resourcefilepath=resourcefilepath), + labour.Labour(resourcefilepath=resourcefilepath), + newborn_outcomes.NewbornOutcomes(resourcefilepath=resourcefilepath), + pregnancy_supervisor.PregnancySupervisor(resourcefilepath=resourcefilepath), + oesophagealcancer.OesophagealCancer(resourcefilepath=resourcefilepath), + # prostate_cancer.ProstateCancer(resourcefilepath=resourcefilepath), + postnatal_supervisor.PostnatalSupervisor(resourcefilepath=resourcefilepath), + diabetes_retionopathy.Diabetes_Retinopathy(), + hiv.Hiv(resourcefilepath=resourcefilepath), + tb.Tb(resourcefilepath=resourcefilepath), + epi.Epi(resourcefilepath=resourcefilepath), + cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + depression.Depression(resourcefilepath=resourcefilepath), + ) + + # Run the simulation + sim.make_initial_population(n=popsize) + sim.simulate(end_date=end_date) + + return sim.log_filepath + + +def get_summary_stats(logfile): + output = parse_log_file(logfile) + + # 1) TOTAL COUNTS BY STAGE OVER TIME + counts_by_stage = output['tlo.methods.diabetes_retionopathy']['summary_stats'] + counts_by_stage['date'] = pd.to_datetime(counts_by_stage['date']) + counts_by_stage = counts_by_stage.set_index('date', drop=True) + + # 2) NUMBERS UNDIAGNOSED-DIAGNOSED-TREATED-PALLIATIVE CARE OVER TIME (SUMMED ACROSS TYPES OF CANCER) + def get_cols_excl_none(allcols, stub): + # helper function to some columns with a certain prefix stub - excluding the 'none' columns (ie. those + # that do not have cancer) + cols = allcols[allcols.str.startswith(stub)] + cols_not_none = [s for s in cols if ("none" not in s)] + return cols_not_none + + summary = { + 'total': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'total_')].sum(axis=1), + 'off': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'off_treatment_')].sum(axis=1), + 'tr': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'treatment_')].sum(axis=1) + } + counts_by_cascade = pd.DataFrame(summary) + counts_by_stage['year'] = counts_by_stage.index.year + + + + return { + 'total_counts_by_stage_over_time': counts_by_stage, + 'counts_by_cascade': counts_by_cascade + } + + +# %% Run the simulation with and without interventions being allowed + +# With interventions: +logfile_with_healthsystem = run_sim(service_availability=['*']) +results_with_healthsystem = get_summary_stats(logfile_with_healthsystem) + +# Without interventions: +logfile_no_healthsystem = run_sim(service_availability=[]) +results_no_healthsystem = get_summary_stats(logfile_no_healthsystem) + +# %% Produce Summary Graphs: + +# Examine Counts by Stage Over Time +counts = results_no_healthsystem['total_counts_by_stage_over_time'] + +print(f'Results No Health SYstem Keys {results_no_healthsystem.keys()}') +print(f'Columns in Counts {counts.columns}') +counts.plot(y=['total_early', + 'total_late' + ]) +plt.title('Count in Each Stage of Disease Over Time') +plt.xlabel('Time') +plt.ylabel('Count') +plt.show() + +# Examine numbers in each stage of the cascade: +results_with_healthsystem['counts_by_cascade'].plot(y=['off', 'tr']) +plt.title('With Health System') +plt.xlabel('Numbers of those With DR by Stage in Cascade') +plt.xlabel('Time') +plt.legend(['Off Treatment', 'On Treatment']) +plt.show() + +results_no_healthsystem['counts_by_cascade'].plot(y=['off', 'tr']) +plt.title('With No Health System') +plt.xlabel('Numbers of those With DR by Stage in Cascade') +plt.xlabel('Time') +plt.legend(['Off Treatment', 'On Treatment']) +plt.show() + + + diff --git a/src/tlo/methods/diabetes_retionopathy.py b/src/tlo/methods/diabetes_retionopathy.py index 012cc16caf..d09d06c5e2 100644 --- a/src/tlo/methods/diabetes_retionopathy.py +++ b/src/tlo/methods/diabetes_retionopathy.py @@ -2,8 +2,9 @@ from typing import List import pandas as pd +import numpy as np -from tlo import Module, Simulation, Parameter, Types, Property, Population, logging +from tlo import DateOffset, Module, Simulation, Parameter, Types, Property, Population, logging from tlo.events import RegularEvent, PopulationScopeEventMixin, IndividualScopeEventMixin from tlo.lm import LinearModel, LinearModelType from tlo.methods import Metadata @@ -14,6 +15,7 @@ logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) + class Diabetes_Retinopathy(Module): """ This is Diabetes Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ @@ -29,12 +31,16 @@ class Diabetes_Retinopathy(Module): # define a dictionary of parameters this module will use PARAMETERS = { - 'rate_onset_to_early_dr': Parameter(Types.REAL, 'Probability to dr'), - 'rate_progression_to_dr': Parameter(Types.REAL, 'Probability to dr'), - 'prob_fast_dr': Parameter(Types.REAL, 'Probability to dr'), - 'init_prob_any_dr': Parameter(Types.REAL, 'Probability to dr'), - 'init_prob_late_dr': Parameter(Types.REAL, 'Probability to dr'), - 'p_medication': Parameter(Types.REAL, 'Probability to dr'), + 'rate_onset_to_early_dr': Parameter(Types.REAL, + 'Probability of people who get diagnosed with early diabetic retinopathy'), + 'rate_progression_to_dr': Parameter(Types.REAL, + 'Probability of people who get diagnosed with late diabetic retinopathy'), + 'prob_fast_dr': Parameter(Types.REAL, + 'Probability of people who get diagnosed from none phase to late diabetic retinopathy stage'), + 'init_prob_any_dr': Parameter(Types.REAL, 'Initial probability of anyone with diabetic retinopathy'), + 'init_prob_late_dr': Parameter(Types.REAL, + 'Initial probability of people with diabetic retinopathy in the late stage'), + 'p_medication': Parameter(Types.REAL, 'Diabetic retinopathy treatment/medication effectiveness'), } # define a dictionary of properties this module will use @@ -49,7 +55,11 @@ class Diabetes_Retinopathy(Module): description="dr status", ), 'dr_on_treatment': Property( - Types.BOOL, 'Whether this person will die during a current severe exacerbation' + Types.BOOL, 'Whether this person is on diabetic retinopathy treatment', + ), + 'dr_date_treatment': Property( + Types.DATE, + 'date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)' ), 'dr_early_diagnosed': Property( Types.BOOL, 'Whether this person will die during a current severe exacerbation' @@ -58,7 +68,7 @@ class Diabetes_Retinopathy(Module): Types.BOOL, 'Whether this person will die during a current severe exacerbation' ), 'dr_diagnosed': Property( - Types.BOOL, 'Whether this person will die during a current severe exacerbation' + Types.BOOL, 'Whether this person has been diagnosed with any diabetic retinopathy' ), } @@ -67,7 +77,6 @@ def __init__(self): # this method is included to define all things that should be initialised first super().__init__() - def read_parameters(self, data_folder: str | Path) -> None: """ initialise module parameters. Here we are assigning values to all parameters defined at the beginning of this module. For this demo module, we will manually assign values to parameters but in the @@ -84,7 +93,7 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['p_medication'] = 0.4 self.sim.modules['SymptomManager'].register_symptom( - Symptom(name='blindness_partial'), # will not trigger any health seeking behaviour + Symptom(name='blindness_partial'), Symptom(name='blindness_full') ) @@ -97,17 +106,16 @@ def initialise_population(self, population: Population) -> None: df = population.props p = self.parameters - alive_diabetes_idx = df.loc[df.is_alive & df.nc_diabetes].index any_dr_idx = alive_diabetes_idx[ self.rng.random_sample(size=len(alive_diabetes_idx)) < self.parameters['init_prob_any_dr'] - ] + ] no_dr_idx = set(alive_diabetes_idx) - set(any_dr_idx) late_dr_idx = any_dr_idx[ self.rng.random_sample(size=len(any_dr_idx)) < self.parameters['init_prob_late_dr'] - ] + ] early_dr_idx = set(any_dr_idx) - set(late_dr_idx) @@ -118,7 +126,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(late_dr_idx), "dr_status"] = "late" df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False - + df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation @@ -127,10 +135,10 @@ def initialise_simulation(self, sim: Simulation) -> None: """ sim.schedule_event(DrPollEvent(self), date=sim.date) + sim.schedule_event(DiabeticRetinopathyLoggingEvent(self), sim.date + DateOffset(months=1)) self.make_the_linear_models() - def report_daly_values(self) -> pd.Series: return pd.Series(index=self.sim.population.props.index, data=0.0) @@ -138,10 +146,10 @@ def on_birth(self, mother_id: int, child_id: int) -> None: """ set properties of a child when they are born. """ self.sim.population.props.at[child_id, 'dr_status'] = 'none' self.sim.population.props.at[child_id, 'dr_on_treatment'] = False + self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_diagnosis_date'] = pd.NaT - def on_simulation_end(self) -> None: pass @@ -165,12 +173,13 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['prob_fast_dr'] ) + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retionpathy (DR) and logs current states. DR diagnosis begins at least after 3 years of being infected with Diabetes Mellitus.""" def __init__(self, module): - super().__init__(module, frequency=pd.DateOffset(months=1)) + super().__init__(module, frequency=DateOffset(months=1)) def apply(self, population: Population) -> None: """ @@ -182,15 +191,23 @@ def apply(self, population: Population) -> None: diabetes_and_alive_earlydr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'early')] will_progress = self.module.lm['onset_early_dr'].predict(diabetes_and_alive_nodr, self.module.rng) - will_progress_idx = will_progress[will_progress].index + # will_progress_idx = will_progress[will_progress].index + # print(f'Will Progress: {will_progress_idx}') + # will_progress_idx = df.index[np.where(will_progress)[0]] + will_progress_idx = df.index[np.where(will_progress)[0]] + print(f'New Will Progress: {will_progress_idx}') + old_will_progress_idx = will_progress[will_progress].index + print(f'Old Will Progress: {old_will_progress_idx}') df.loc[will_progress_idx, 'dr_status'] = 'early' early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) - early_to_late_idx = early_to_late[early_to_late].index + # early_to_late_idx = early_to_late[early_to_late].index + early_to_late_idx = df.index[np.where(early_to_late)[0]] df.loc[early_to_late_idx, 'dr_status'] = 'late' fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) - fast_dr_idx = fast_dr[fast_dr].index + # fast_dr_idx = fast_dr[fast_dr].index + fast_dr_idx = df.index[np.where(fast_dr)[0]] df.loc[fast_dr_idx, 'dr_status'] = 'late' if len(will_progress_idx): @@ -225,8 +242,6 @@ def do_at_generic_first_appt_emergency( schedule_hsi_event(event, priority=1, topen=self.sim.date) - - class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ This is a Health System Interaction Event. @@ -240,29 +255,66 @@ def __init__(self, module, person_id): assert isinstance(module, Diabetes_Retinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Mockitis_Treatment_Initiation' + self.TREATMENT_ID = 'Dr_Treatment_Initiation' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '1a' self.ALERT_OTHER_DISEASES = [] - def apply(self, person_id, squeeze_factor): - logger.debug(key='debug', - data=f'This is HSI_Dr_StartTreatment: initiating treatment for person {person_id}') - df = self.sim.population.props - person = df.loc[person_id] - if not df.at[person_id, 'is_alive']: - # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + def apply(self, person_id, squeeze_factor): + logger.debug(key='debug', + data=f'This is HSI_Dr_StartTreatment: initiating treatment for person {person_id}') + df = self.sim.population.props + person = df.loc[person_id] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + treatment_slows_progression_to_late = self.module.rng.rand() < self.module.parameters['p_medication'] + + #TODO Add consumables in codition below + if treatment_slows_progression_to_late: + df.at[person_id, 'dr_on_treatment'] = True + df.at[person_id, 'dr_date_treatment'] = self.sim.date + # df.at[person_id, 'dr_status'] = 'early' + # else: + # df.at[person_id, 'dr_on_treatment'] = True + # df.at[person_id, 'dr_status'] = 'late' #checkout cervical cancer on via after some years + + +class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): + """The only logging event for this module""" + + def __init__(self, module): + """schedule logging to repeat every 1 month + """ + self.repeat = 30 + super().__init__(module, frequency=DateOffset(days=self.repeat)) + + def apply(self, population): + """Compute statistics regarding the current status of persons and output to the logger + """ + df = population.props - # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + # CURRENT STATUS COUNTS + # Create dictionary for each subset, adding prefix to key name, and adding to make a flat dict for logging. + out = {} - treatment_slows_progression_to_late = self.module.rng.rand() < self.module.parameters['p_medication'] + # Current counts, total + out.update({ + f'total_{k}': v for k, v in df.loc[df.is_alive].dr_status.value_counts().items()}) - #TODO Add consumables in codition below - if treatment_slows_progression_to_late: - df.at[person_id, 'dr_on_treatment'] = True + # Current counts, off treatment + out.update({f'off_treatment_{k}': v for k, v in df.loc[df.is_alive].loc[ + pd.isnull(df.dr_date_treatment), 'dr_status'].value_counts().items()}) + # Current counts, on treatment (excl. palliative care) + out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( + df.dr_date_treatment)), 'dr_status'].value_counts().items()}) + logger.info(key='summary_stats', data=out) From e8524dc9ce1068f957e76d2ef1b2cf8bdb8788d2 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 20 Feb 2025 15:49:18 +0200 Subject: [PATCH 05/85] Renaming files and adding effectiveness in HSI --- .../diabetic_retinopathy_analyses.py | 8 ++-- ...etionopathy.py => diabetic_retinopathy.py} | 38 ++++++++++++++----- tests/test_diabetes_retinopathy.py | 4 +- 3 files changed, 34 insertions(+), 16 deletions(-) rename src/tlo/methods/{diabetes_retionopathy.py => diabetic_retinopathy.py} (90%) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 542f52ab17..52717d4c45 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -32,7 +32,7 @@ pregnancy_supervisor, prostate_cancer, symptommanager, - diabetes_retionopathy, + diabetic_retinopathy, hiv, tb, epi, cardio_metabolic_disorders, depression, @@ -49,7 +49,7 @@ # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2010, 6, 6) +end_date = Date(2011, 1, 1) popsize = 5000 @@ -78,7 +78,7 @@ def run_sim(service_availability): oesophagealcancer.OesophagealCancer(resourcefilepath=resourcefilepath), # prostate_cancer.ProstateCancer(resourcefilepath=resourcefilepath), postnatal_supervisor.PostnatalSupervisor(resourcefilepath=resourcefilepath), - diabetes_retionopathy.Diabetes_Retinopathy(), + diabetic_retinopathy.Diabetic_Retinopathy(), hiv.Hiv(resourcefilepath=resourcefilepath), tb.Tb(resourcefilepath=resourcefilepath), epi.Epi(resourcefilepath=resourcefilepath), @@ -97,7 +97,7 @@ def get_summary_stats(logfile): output = parse_log_file(logfile) # 1) TOTAL COUNTS BY STAGE OVER TIME - counts_by_stage = output['tlo.methods.diabetes_retionopathy']['summary_stats'] + counts_by_stage = output['tlo.methods.diabetic_retinopathy']['summary_stats'] counts_by_stage['date'] = pd.to_datetime(counts_by_stage['date']) counts_by_stage = counts_by_stage.set_index('date', drop=True) diff --git a/src/tlo/methods/diabetes_retionopathy.py b/src/tlo/methods/diabetic_retinopathy.py similarity index 90% rename from src/tlo/methods/diabetes_retionopathy.py rename to src/tlo/methods/diabetic_retinopathy.py index d09d06c5e2..7f814a3bb2 100644 --- a/src/tlo/methods/diabetes_retionopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -16,8 +16,8 @@ logger.setLevel(logging.INFO) -class Diabetes_Retinopathy(Module): - """ This is Diabetes Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ +class Diabetic_Retinopathy(Module): + """ This is Diabetic Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ INIT_DEPENDENCIES = {'SymptomManager', 'Lifestyle', 'HealthSystem', 'CardioMetabolicDisorders'} ADDITIONAL_DEPENDENCIES = set() @@ -85,12 +85,12 @@ def read_parameters(self, data_folder: str | Path) -> None: :param data_folder: Path to the folder containing parameter values """ - self.parameters['rate_onset_to_early_dr'] = 0.5 - self.parameters['rate_progression_to_dr'] = 0.5 + self.parameters['rate_onset_to_early_dr'] = 0.29 + self.parameters['rate_progression_to_dr'] = 0.07 self.parameters['prob_fast_dr'] = 0.5 - self.parameters['init_prob_any_dr'] = 0.5 - self.parameters['init_prob_late_dr'] = 0.5 - self.parameters['p_medication'] = 0.4 + self.parameters['init_prob_any_dr'] = 0.36 + self.parameters['init_prob_late_dr'] = 0.09 + self.parameters['p_medication'] = 0.8 self.sim.modules['SymptomManager'].register_symptom( Symptom(name='blindness_partial'), @@ -175,7 +175,7 @@ def make_the_linear_models(self) -> None: class DrPollEvent(RegularEvent, PopulationScopeEventMixin): - """An event that controls the development process of Diabetes Retionpathy (DR) and logs current states. DR diagnosis + """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis begins at least after 3 years of being infected with Diabetes Mellitus.""" def __init__(self, module): @@ -252,7 +252,7 @@ class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): def __init__(self, module, person_id): super().__init__(module, person_id=person_id) - assert isinstance(module, Diabetes_Retinopathy) + assert isinstance(module, Diabetic_Retinopathy) # Define the necessary information for an HSI self.TREATMENT_ID = 'Dr_Treatment_Initiation' @@ -274,12 +274,30 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() - treatment_slows_progression_to_late = self.module.rng.rand() < self.module.parameters['p_medication'] + randomly_sampled = self.module.rng.rand() + print(f'Randomly sampled {randomly_sampled}') + treatment_slows_progression_to_late = randomly_sampled < self.module.parameters['p_medication'] #TODO Add consumables in codition below if treatment_slows_progression_to_late: df.at[person_id, 'dr_on_treatment'] = True df.at[person_id, 'dr_date_treatment'] = self.sim.date + + # Reduce probability of progression to "late" DR + progression_chance = self.module.parameters['rate_progression_to_dr'] * ( + 1 - self.module.parameters['p_medication']) + + # Determine if person will still progress + if self.module.rng.rand() < progression_chance: + df.at[person_id, 'dr_status'] = 'late' + else: + df.at[person_id, 'dr_status'] = 'early' # Stays in early stage due to medication + + else: + # If medication is not effective, progression happens as usual + df.at[person_id, 'dr_on_treatment'] = True + df.at[person_id, 'dr_status'] = 'late' + # df.at[person_id, 'dr_status'] = 'early' # else: # df.at[person_id, 'dr_on_treatment'] = True diff --git a/tests/test_diabetes_retinopathy.py b/tests/test_diabetes_retinopathy.py index 6398fecfb9..352fce0eec 100644 --- a/tests/test_diabetes_retinopathy.py +++ b/tests/test_diabetes_retinopathy.py @@ -5,7 +5,7 @@ from tlo import Date, Simulation from tlo.methods import cardio_metabolic_disorders, demography, enhanced_lifestyle, simplified_births, healthsystem, \ - symptommanager, healthseekingbehaviour, healthburden, diabetes_retionopathy, depression + symptommanager, healthseekingbehaviour, healthburden, diabetic_retinopathy, depression resourcefilepath = Path(os.path.dirname(__file__)) / '../resources' start_date = Date(2010, 1, 1) @@ -37,7 +37,7 @@ def test_basic_run(tmpdir, seed, diabetes_retinopathy=None): ), healthburden.HealthBurden(resourcefilepath=resourcefilepath), cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), - diabetes_retionopathy.Diabetes_Retinopathy(), + diabetic_retinopathy.Diabetic_Retinopathy(), depression.Depression(resourcefilepath=resourcefilepath), ) sim.make_initial_population(n=popsize) From 0419122114be3e3da14b713af0a26e75bf9a982e Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 24 Feb 2025 10:49:08 +0200 Subject: [PATCH 06/85] tidy up --- .../diabetic_retinopathy_analyses.py | 30 ++------- src/tlo/methods/diabetic_retinopathy.py | 67 +++++++------------ ...opathy.py => test_diabetic_retinopathy.py} | 24 +++++-- 3 files changed, 50 insertions(+), 71 deletions(-) rename tests/{test_diabetes_retinopathy.py => test_diabetic_retinopathy.py} (76%) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 52717d4c45..664e6aad21 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -1,41 +1,31 @@ -""" -* Check key outputs for reporting in the calibration table of the write-up -* Produce representative plots for the default parameters - -NB. To see larger effects -* Increase incidence of cancer (see tests) -* Increase symptom onset (r_urinary_symptoms_prostate_ca or r_pelvic_pain_symptoms_local_ln_prostate_ca) -* Increase progression rates (see tests) -""" - import datetime from pathlib import Path import matplotlib.pyplot as plt -import numpy as np import pandas as pd from tlo import Date, Simulation from tlo.analysis.utils import make_age_grp_types, parse_log_file from tlo.methods import ( + cardio_metabolic_disorders, care_of_women_during_pregnancy, contraception, demography, + depression, + diabetic_retinopathy, enhanced_lifestyle, + epi, healthburden, healthseekingbehaviour, healthsystem, + hiv, labour, newborn_outcomes, oesophagealcancer, postnatal_supervisor, pregnancy_supervisor, - prostate_cancer, symptommanager, - diabetic_retinopathy, - hiv, tb, epi, - cardio_metabolic_disorders, - depression, + tb, ) # Where will outputs go @@ -76,9 +66,8 @@ def run_sim(service_availability): newborn_outcomes.NewbornOutcomes(resourcefilepath=resourcefilepath), pregnancy_supervisor.PregnancySupervisor(resourcefilepath=resourcefilepath), oesophagealcancer.OesophagealCancer(resourcefilepath=resourcefilepath), - # prostate_cancer.ProstateCancer(resourcefilepath=resourcefilepath), postnatal_supervisor.PostnatalSupervisor(resourcefilepath=resourcefilepath), - diabetic_retinopathy.Diabetic_Retinopathy(), + diabetic_retinopathy.DiabeticRetinopathy(), hiv.Hiv(resourcefilepath=resourcefilepath), tb.Tb(resourcefilepath=resourcefilepath), epi.Epi(resourcefilepath=resourcefilepath), @@ -117,8 +106,6 @@ def get_cols_excl_none(allcols, stub): counts_by_cascade = pd.DataFrame(summary) counts_by_stage['year'] = counts_by_stage.index.year - - return { 'total_counts_by_stage_over_time': counts_by_stage, 'counts_by_cascade': counts_by_cascade @@ -164,6 +151,3 @@ def get_cols_excl_none(allcols, stub): plt.xlabel('Time') plt.legend(['Off Treatment', 'On Treatment']) plt.show() - - - diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 7f814a3bb2..11f2c68504 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,11 +1,11 @@ from pathlib import Path from typing import List -import pandas as pd import numpy as np +import pandas as pd -from tlo import DateOffset, Module, Simulation, Parameter, Types, Property, Population, logging -from tlo.events import RegularEvent, PopulationScopeEventMixin, IndividualScopeEventMixin +from tlo import DateOffset, Module, Parameter, Population, Property, Simulation, Types, logging +from tlo.events import IndividualScopeEventMixin, PopulationScopeEventMixin, RegularEvent from tlo.lm import LinearModel, LinearModelType from tlo.methods import Metadata from tlo.methods.hsi_event import HSI_Event @@ -16,8 +16,8 @@ logger.setLevel(logging.INFO) -class Diabetic_Retinopathy(Module): - """ This is Diabetic Retinopathy module. It seeks to skeleton of blindness due to diabetes. """ +class DiabeticRetinopathy(Module): + """ This is Diabetic Retinopathy module. It seeks to model of blindness due to diabetes. """ INIT_DEPENDENCIES = {'SymptomManager', 'Lifestyle', 'HealthSystem', 'CardioMetabolicDisorders'} ADDITIONAL_DEPENDENCIES = set() @@ -29,21 +29,20 @@ class Diabetic_Retinopathy(Module): Metadata.USES_HEALTHBURDEN, } - # define a dictionary of parameters this module will use PARAMETERS = { 'rate_onset_to_early_dr': Parameter(Types.REAL, 'Probability of people who get diagnosed with early diabetic retinopathy'), 'rate_progression_to_dr': Parameter(Types.REAL, 'Probability of people who get diagnosed with late diabetic retinopathy'), 'prob_fast_dr': Parameter(Types.REAL, - 'Probability of people who get diagnosed from none phase to late diabetic retinopathy stage'), + 'Probability of people who get diagnosed from none phase to late diabetic ' + 'retinopathy stage'), 'init_prob_any_dr': Parameter(Types.REAL, 'Initial probability of anyone with diabetic retinopathy'), 'init_prob_late_dr': Parameter(Types.REAL, 'Initial probability of people with diabetic retinopathy in the late stage'), 'p_medication': Parameter(Types.REAL, 'Diabetic retinopathy treatment/medication effectiveness'), } - # define a dictionary of properties this module will use PROPERTIES = { "dr_status": Property( Types.CATEGORICAL, @@ -62,10 +61,10 @@ class Diabetic_Retinopathy(Module): 'date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)' ), 'dr_early_diagnosed': Property( - Types.BOOL, 'Whether this person will die during a current severe exacerbation' + Types.BOOL, 'Whether this person has been diagnosed with early diabetic retinopathy' ), 'dr_late_diagnosed': Property( - Types.BOOL, 'Whether this person will die during a current severe exacerbation' + Types.BOOL, 'Whether this person has been diagnosed with late diabetic retinopathy' ), 'dr_diagnosed': Property( Types.BOOL, 'Whether this person has been diagnosed with any diabetic retinopathy' @@ -74,17 +73,16 @@ class Diabetic_Retinopathy(Module): } def __init__(self): - # this method is included to define all things that should be initialised first super().__init__() def read_parameters(self, data_folder: str | Path) -> None: """ initialise module parameters. Here we are assigning values to all parameters defined at the beginning of - this module. For this demo module, we will manually assign values to parameters but in the - Thanzi model we do this by reading from an Excel file containing parameter names and values + this module. :param data_folder: Path to the folder containing parameter values """ + #TODO Read from resourcefile self.parameters['rate_onset_to_early_dr'] = 0.29 self.parameters['rate_progression_to_dr'] = 0.07 self.parameters['prob_fast_dr'] = 0.5 @@ -98,13 +96,13 @@ def read_parameters(self, data_folder: str | Path) -> None: ) def initialise_population(self, population: Population) -> None: - """ set the initial state of the population. The state will be update over time + """ Set property values for the initial population :param population: all individuals in the model """ df = population.props - p = self.parameters + # p = self.parameters alive_diabetes_idx = df.loc[df.is_alive & df.nc_diabetes].index @@ -130,20 +128,21 @@ def initialise_population(self, population: Population) -> None: def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation - - :param sim: simulation object - + * Schedule the main polling event + * Schedule the main logging event + * Call the LinearModels """ sim.schedule_event(DrPollEvent(self), date=sim.date) sim.schedule_event(DiabeticRetinopathyLoggingEvent(self), sim.date + DateOffset(months=1)) - self.make_the_linear_models() def report_daly_values(self) -> pd.Series: return pd.Series(index=self.sim.population.props.index, data=0.0) def on_birth(self, mother_id: int, child_id: int) -> None: - """ set properties of a child when they are born. """ + """ set properties of a child when they are born. + :param child_id: the new child + """ self.sim.population.props.at[child_id, 'dr_status'] = 'none' self.sim.population.props.at[child_id, 'dr_on_treatment'] = False self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT @@ -154,7 +153,7 @@ def on_simulation_end(self) -> None: pass def make_the_linear_models(self) -> None: - """Here is where we make and save LinearModels that will be used when the module is running""" + """Make and save LinearModels that will be used when the module is running""" self.lm = dict() @@ -182,9 +181,6 @@ def __init__(self, module): super().__init__(module, frequency=DateOffset(months=1)) def apply(self, population: Population) -> None: - """ - - """ df = population.props diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] @@ -192,12 +188,9 @@ def apply(self, population: Population) -> None: will_progress = self.module.lm['onset_early_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # will_progress_idx = will_progress[will_progress].index - # print(f'Will Progress: {will_progress_idx}') # will_progress_idx = df.index[np.where(will_progress)[0]] will_progress_idx = df.index[np.where(will_progress)[0]] - print(f'New Will Progress: {will_progress_idx}') old_will_progress_idx = will_progress[will_progress].index - print(f'Old Will Progress: {old_will_progress_idx}') df.loc[will_progress_idx, 'dr_status'] = 'early' early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) @@ -233,7 +226,7 @@ def do_at_generic_first_appt_emergency( schedule_hsi_event: HSIEventScheduler, **kwargs, ) -> None: - # Example for mockitis + if "blindness_full" in symptoms or "blindness_partial" in symptoms: event = HSI_Dr_StartTreatment( module=self, @@ -241,18 +234,15 @@ def do_at_generic_first_appt_emergency( ) schedule_hsi_event(event, priority=1, topen=self.sim.date) - +#TODO HSI_Dr_StartTreatment should be called by HSI_Dr_TestingFollowingSymptoms class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ - This is a Health System Interaction Event. - - It is appointment at which treatment for mockitiis is inititaed. - + This event initiates the treatment of DR. """ def __init__(self, module, person_id): super().__init__(module, person_id=person_id) - assert isinstance(module, Diabetic_Retinopathy) + assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI self.TREATMENT_ID = 'Dr_Treatment_Initiation' @@ -275,7 +265,6 @@ def apply(self, person_id, squeeze_factor): return self.sim.modules["HealthSystem"].get_blank_appt_footprint() randomly_sampled = self.module.rng.rand() - print(f'Randomly sampled {randomly_sampled}') treatment_slows_progression_to_late = randomly_sampled < self.module.parameters['p_medication'] #TODO Add consumables in codition below @@ -285,7 +274,7 @@ def apply(self, person_id, squeeze_factor): # Reduce probability of progression to "late" DR progression_chance = self.module.parameters['rate_progression_to_dr'] * ( - 1 - self.module.parameters['p_medication']) + 1 - self.module.parameters['p_medication']) # Determine if person will still progress if self.module.rng.rand() < progression_chance: @@ -298,11 +287,6 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dr_on_treatment'] = True df.at[person_id, 'dr_status'] = 'late' - # df.at[person_id, 'dr_status'] = 'early' - # else: - # df.at[person_id, 'dr_on_treatment'] = True - # df.at[person_id, 'dr_status'] = 'late' #checkout cervical cancer on via after some years - class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): """The only logging event for this module""" @@ -334,5 +318,4 @@ def apply(self, population): out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( df.dr_date_treatment)), 'dr_status'].value_counts().items()}) - logger.info(key='summary_stats', data=out) diff --git a/tests/test_diabetes_retinopathy.py b/tests/test_diabetic_retinopathy.py similarity index 76% rename from tests/test_diabetes_retinopathy.py rename to tests/test_diabetic_retinopathy.py index 352fce0eec..5130464460 100644 --- a/tests/test_diabetes_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -4,15 +4,27 @@ import pytest from tlo import Date, Simulation -from tlo.methods import cardio_metabolic_disorders, demography, enhanced_lifestyle, simplified_births, healthsystem, \ - symptommanager, healthseekingbehaviour, healthburden, diabetic_retinopathy, depression +from tlo.methods import ( + cardio_metabolic_disorders, + demography, + depression, + diabetic_retinopathy, + enhanced_lifestyle, + healthburden, + healthseekingbehaviour, + healthsystem, + simplified_births, + symptommanager, +) resourcefilepath = Path(os.path.dirname(__file__)) / '../resources' start_date = Date(2010, 1, 1) end_date = Date(2010, 1, 2) + + @pytest.mark.slow -def test_basic_run(tmpdir, seed, diabetes_retinopathy=None): - """Run the simulation with the Copd module and read the log from the Copd module.""" +def test_basic_run(tmpdir, seed): + """Run the simulation with the diabetic_retinopathy module and read the log from the diabetic_retinopathy module.""" popsize = 1000 sim = Simulation( @@ -37,8 +49,8 @@ def test_basic_run(tmpdir, seed, diabetes_retinopathy=None): ), healthburden.HealthBurden(resourcefilepath=resourcefilepath), cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), - diabetic_retinopathy.Diabetic_Retinopathy(), + diabetic_retinopathy.DiabeticRetinopathy(), depression.Depression(resourcefilepath=resourcefilepath), ) sim.make_initial_population(n=popsize) - sim.simulate(end_date=Date(2010, 2, 1)) # Long run + sim.simulate(end_date=Date(2010, 2, 1)) # Long run From 84968f01e9cf2fa9713a56baeb331e56b12f5529 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 27 Feb 2025 15:44:08 +0200 Subject: [PATCH 07/85] HSI testing for symptoms, stacked bars, temp item codes in res file, treatment ID color --- ...rceFile_Consumables_Items_and_Packages.csv | 4 +- .../diabetic_retinopathy_analyses.py | 130 +++++++++++------- src/tlo/analysis/utils.py | 1 + src/tlo/methods/diabetic_retinopathy.py | 120 +++++++++++++++- 4 files changed, 198 insertions(+), 57 deletions(-) diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index 0ee403abb0..ee72f95b7b 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:4106c2e3ae068d40b115857885b673bec3e1114be5183c0a4ae0366560e2a5c9 -size 249391 +oid sha256:db947ae71c8c2914191654fcb1cbdaec24f3d0953a29ac8e5215e3cb8a3ad3d9 +size 246682 diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 664e6aad21..a07d5c38e1 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -5,7 +5,7 @@ import pandas as pd from tlo import Date, Simulation -from tlo.analysis.utils import make_age_grp_types, parse_log_file +from tlo.analysis.utils import parse_log_file from tlo.methods import ( cardio_metabolic_disorders, care_of_women_during_pregnancy, @@ -42,15 +42,12 @@ end_date = Date(2011, 1, 1) popsize = 5000 - def run_sim(service_availability): log_config = { 'filename': 'LogFile', 'directory': outputpath } - # Establish the simulation object and set the seed - # sim = Simulation(start_date=start_date, seed=0, log_config=log_config) - sim = Simulation(start_date=start_date, log_config={"filename": "LogFile"}) + sim = Simulation(start_date=start_date, seed=0, log_config={"filename": "LogFile"}) # Register the appropriate modules sim.register(care_of_women_during_pregnancy.CareOfWomenDuringPregnancy(resourcefilepath=resourcefilepath), @@ -81,73 +78,102 @@ def run_sim(service_availability): return sim.log_filepath - def get_summary_stats(logfile): output = parse_log_file(logfile) - - # 1) TOTAL COUNTS BY STAGE OVER TIME counts_by_stage = output['tlo.methods.diabetic_retinopathy']['summary_stats'] counts_by_stage['date'] = pd.to_datetime(counts_by_stage['date']) counts_by_stage = counts_by_stage.set_index('date', drop=True) - # 2) NUMBERS UNDIAGNOSED-DIAGNOSED-TREATED-PALLIATIVE CARE OVER TIME (SUMMED ACROSS TYPES OF CANCER) - def get_cols_excl_none(allcols, stub): - # helper function to some columns with a certain prefix stub - excluding the 'none' columns (ie. those - # that do not have cancer) - cols = allcols[allcols.str.startswith(stub)] - cols_not_none = [s for s in cols if ("none" not in s)] - return cols_not_none - summary = { - 'total': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'total_')].sum(axis=1), - 'off': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'off_treatment_')].sum(axis=1), - 'tr': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'treatment_')].sum(axis=1) + 'total': counts_by_stage.filter(like='total_').sum(axis=1), + 'off': counts_by_stage.filter(like='off_treatment_').sum(axis=1), + 'tr': counts_by_stage.filter(like='treatment_').sum(axis=1), + 'new_early': counts_by_stage.get('new_early', pd.Series(0, index=counts_by_stage.index)), + 'new_late': counts_by_stage.get('new_late', pd.Series(0, index=counts_by_stage.index)) } + counts_by_cascade = pd.DataFrame(summary) counts_by_stage['year'] = counts_by_stage.index.year + incidence_by_stage = pd.DataFrame({'new_early': summary['new_early'], 'new_late': summary['new_late']}) return { 'total_counts_by_stage_over_time': counts_by_stage, - 'counts_by_cascade': counts_by_cascade + 'counts_by_cascade': counts_by_cascade, + 'incidence_by_stage': incidence_by_stage } -# %% Run the simulation with and without interventions being allowed +def plot_dr_progression(counts_by_stage, title): + """Plot stacked bars for early and late diabetic retinopathy over time.""" + + # Set the index to be years only + counts_by_stage = counts_by_stage.copy() + counts_by_stage.index = counts_by_stage.index.strftime('%Y-%m') + + fig, ax = plt.subplots(figsize=(12, 6)) + + counts_by_stage[['total_early', 'total_late']].plot( + kind='bar', stacked=True, ax=ax, colormap="viridis" + ) + + ax.set_title(title) + ax.set_xlabel("Time (Months & Years)") + ax.set_ylabel("Number of People") + ax.legend(["Early DR", "Late DR"]) + plt.xticks(rotation=45) # Rotate x-axis labels for readability + + plt.tight_layout() + plt.show() + +def plot_treatment_cascade(counts_by_cascade, title): + """Plot stacked bar chart for treatment status over time.""" + + counts_by_cascade = counts_by_cascade.copy() + counts_by_cascade.index = counts_by_cascade.index.strftime('%Y-%m') + + fig, ax = plt.subplots(figsize=(12, 6)) + + counts_by_cascade[['off', 'tr']].plot( + kind='bar', stacked=True, ax=ax, colormap="coolwarm" + ) + + ax.set_title(title) + ax.set_xlabel("Time (Months & Years)") + ax.set_ylabel("Number of People") + ax.legend(["Off Treatment", "On Treatment"]) + plt.xticks(rotation=45) + + plt.tight_layout() + plt.show() + + +def plot_dr_incidence(incidence_by_stage, title): + """Plot stacked bars for new cases of early and late DR over time.""" + incidence_by_stage = incidence_by_stage.copy() + incidence_by_stage.index = incidence_by_stage.index.strftime('%Y-%m') + + print(f'Incidence data for plotting {incidence_by_stage.head()}') + + fig, ax = plt.subplots(figsize=(12, 6)) + incidence_by_stage[['new_early', 'new_late']].plot(kind='bar', stacked=True, ax=ax, colormap="plasma") + + ax.set_title(title) + ax.set_xlabel("Time (Months & Years)") + ax.set_ylabel("Number of New Cases") + ax.legend(["New Early DR Cases", "New Late DR Cases"]) + plt.xticks(rotation=45) + plt.tight_layout() + plt.show() -# With interventions: logfile_with_healthsystem = run_sim(service_availability=['*']) results_with_healthsystem = get_summary_stats(logfile_with_healthsystem) -# Without interventions: logfile_no_healthsystem = run_sim(service_availability=[]) results_no_healthsystem = get_summary_stats(logfile_no_healthsystem) -# %% Produce Summary Graphs: - -# Examine Counts by Stage Over Time -counts = results_no_healthsystem['total_counts_by_stage_over_time'] - -print(f'Results No Health SYstem Keys {results_no_healthsystem.keys()}') -print(f'Columns in Counts {counts.columns}') -counts.plot(y=['total_early', - 'total_late' - ]) -plt.title('Count in Each Stage of Disease Over Time') -plt.xlabel('Time') -plt.ylabel('Count') -plt.show() - -# Examine numbers in each stage of the cascade: -results_with_healthsystem['counts_by_cascade'].plot(y=['off', 'tr']) -plt.title('With Health System') -plt.xlabel('Numbers of those With DR by Stage in Cascade') -plt.xlabel('Time') -plt.legend(['Off Treatment', 'On Treatment']) -plt.show() - -results_no_healthsystem['counts_by_cascade'].plot(y=['off', 'tr']) -plt.title('With No Health System') -plt.xlabel('Numbers of those With DR by Stage in Cascade') -plt.xlabel('Time') -plt.legend(['Off Treatment', 'On Treatment']) -plt.show() +plot_dr_progression(results_with_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (With Health System)") +plot_dr_progression(results_no_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (No Health System)") +plot_treatment_cascade(results_with_healthsystem['counts_by_cascade'], "Treatment Status Over Time (With Health System)") +plot_treatment_cascade(results_no_healthsystem['counts_by_cascade'], "Treatment Status Over Time (No Health System)") +plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") +plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") diff --git a/src/tlo/analysis/utils.py b/src/tlo/analysis/utils.py index 749e155f79..669b4348b7 100644 --- a/src/tlo/analysis/utils.py +++ b/src/tlo/analysis/utils.py @@ -888,6 +888,7 @@ def get_color_coarse_appt(coarse_appt_type: str) -> str: 'Schisto*': 'skyblue', 'CardioMetabolicDisorders*': 'brown', + 'DiabeticRetinopathy*': 'coffee', 'BladderCancer*': 'orchid', 'BreastCancer*': 'mediumvioletred', diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 11f2c68504..1e090dd643 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -69,11 +69,20 @@ class DiabeticRetinopathy(Module): 'dr_diagnosed': Property( Types.BOOL, 'Whether this person has been diagnosed with any diabetic retinopathy' ), + "dr_date_diagnosis": Property( + Types.DATE, + "the date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" + ), + "dr_blindness_investigated": Property( + Types.BOOL, + "whether blindness has been investigated, and diabetic retinopathy missed" + ), } def __init__(self): super().__init__() + self.cons_item_codes = None # (Will store consumable item codes) def read_parameters(self, data_folder: str | Path) -> None: """ initialise module parameters. Here we are assigning values to all parameters defined at the beginning of @@ -125,6 +134,8 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation @@ -135,6 +146,7 @@ def initialise_simulation(self, sim: Simulation) -> None: sim.schedule_event(DrPollEvent(self), date=sim.date) sim.schedule_event(DiabeticRetinopathyLoggingEvent(self), sim.date + DateOffset(months=1)) self.make_the_linear_models() + self.look_up_consumable_item_codes() def report_daly_values(self) -> pd.Series: return pd.Series(index=self.sim.population.props.index, data=0.0) @@ -147,7 +159,8 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_on_treatment'] = False self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_diagnosed'] = False - self.sim.population.props.at[child_id, 'dr_diagnosis_date'] = pd.NaT + self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT + self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False def on_simulation_end(self) -> None: pass @@ -172,6 +185,21 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['prob_fast_dr'] ) + def look_up_consumable_item_codes(self): + """Look up the item codes used in the HSI of this module""" + get_item_codes = self.sim.modules['HealthSystem'].get_item_code_from_item_name + + self.cons_item_codes = dict() + # self.cons_item_codes['laser_photocoagulation'] = { + # get_item_codes("Anesthetic Eye drops, 15ml"): 3, + # get_item_codes('Disposables gloves, powder free, 100 pieces per box'): 1, + # } + self.cons_item_codes['eye_injection'] = { + get_item_codes("Anesthetic Eye drops, 15ml"): 1, + get_item_codes('Aflibercept, 2mg'): 3, + } + + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis @@ -190,12 +218,16 @@ def apply(self, population: Population) -> None: # will_progress_idx = will_progress[will_progress].index # will_progress_idx = df.index[np.where(will_progress)[0]] will_progress_idx = df.index[np.where(will_progress)[0]] - old_will_progress_idx = will_progress[will_progress].index + # old_will_progress_idx = will_progress[will_progress].index + # Count new early cases for incidence tracking + new_early_cases = len(will_progress_idx) df.loc[will_progress_idx, 'dr_status'] = 'early' early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) # early_to_late_idx = early_to_late[early_to_late].index early_to_late_idx = df.index[np.where(early_to_late)[0]] + # Count new late cases for incidence tracking + new_late_cases = len(early_to_late_idx) df.loc[early_to_late_idx, 'dr_status'] = 'late' fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) @@ -228,12 +260,80 @@ def do_at_generic_first_appt_emergency( ) -> None: if "blindness_full" in symptoms or "blindness_partial" in symptoms: - event = HSI_Dr_StartTreatment( + event = HSI_Dr_TestingFollowingSymptoms( module=self, person_id=person_id, ) schedule_hsi_event(event, priority=1, topen=self.sim.date) + + +class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): + """ + This event is scheduled by do_at_generic_first_appt_emergency following presentation for care with the symptoms + of partial and full blindness. + This event begins the investigation that may result in diagnosis of Diabetic Retinopathy and the scheduling of + treatment. + """ + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + + self.TREATMENT_ID = "DiabeticRetinopathy_Investigation" + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1}) + self.ACCEPTED_FACILITY_LEVEL = '1a' + self.ALERT_OTHER_DISEASES = [] + + + def apply(self, person_id, squeeze_factor): + df = self.sim.population.props + person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] + + # Ignore this event if the person is no longer alive: + if not df.at[person_id, 'is_alive']: + return hs.get_blank_appt_footprint() + + # Check that this event has been called for someone with the symptom blindness_partial + assert 'blindness_partial' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) + # Check that this event has been called for someone with the symptom blindness_full + assert 'blindness_full' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) + + # If the person is already diagnosed, then take no action: + if not pd.isnull(df.at[person_id, "dr_date_diagnosis"]): + return hs.get_blank_appt_footprint() + + df.at[person_id, 'dr_blindness_investigated'] = True + + is_cons_available = self.get_consumables( + self.module.cons_item_codes['eye_injection'] + ) + + dx_result = hs.dx_manager.run_dx_test( + dx_tests_to_run='dilated_eye_exam_dr_blindness', + hsi_event=self + ) + # TODO Those in early DR must not go to start treatment since late DR Work can be managed with good blood + # sugar control to slow the progression. + if dx_result and is_cons_available: + # record date of diagnosis + df.at[person_id, 'dr_date_diagnosis'] = self.sim.date + # If consumables are available, add equipment used and run dx_test + self.add_equipment({'Ophthalmoscope'}) + + hs.schedule_hsi_event( + hsi_event=HSI_Dr_StartTreatment( + module=self.module, + person_id=person_id + ), + priority=0, + topen=self.sim.date, + tclose=None + ) + + + + #TODO HSI_Dr_StartTreatment should be called by HSI_Dr_TestingFollowingSymptoms class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ @@ -268,6 +368,10 @@ def apply(self, person_id, squeeze_factor): treatment_slows_progression_to_late = randomly_sampled < self.module.parameters['p_medication'] #TODO Add consumables in codition below + is_cons_available = self.get_consumables( + self.module.cons_item_codes['eye_injection'] + ) + if treatment_slows_progression_to_late: df.at[person_id, 'dr_on_treatment'] = True df.at[person_id, 'dr_date_treatment'] = self.sim.date @@ -318,4 +422,14 @@ def apply(self, population): out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( df.dr_date_treatment)), 'dr_status'].value_counts().items()}) + # Count new cases + new_early_cases = len(df.loc[df.is_alive & (df.dr_status == 'early') & (df.dr_date_treatment == self.sim.date)]) + new_late_cases = len(df.loc[df.is_alive & (df.dr_status == 'late') & (df.dr_date_treatment == self.sim.date)]) + + # Log incidence counts + out.update({ + 'new_early': new_early_cases, + 'new_late': new_late_cases + }) + logger.info(key='summary_stats', data=out) From 1a8a2e585942d248f0c960abc30a6f69086b2380 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 28 Feb 2025 10:48:45 +0200 Subject: [PATCH 08/85] reformat test file, add initial prevalence test --- tests/test_diabetic_retinopathy.py | 112 +++++++++++++++++++++++++---- 1 file changed, 99 insertions(+), 13 deletions(-) diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 5130464460..d2aaf11154 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -1,6 +1,7 @@ import os from pathlib import Path +import pandas as pd import pytest from tlo import Date, Simulation @@ -17,40 +18,125 @@ symptommanager, ) -resourcefilepath = Path(os.path.dirname(__file__)) / '../resources' +try: + resourcefilepath = Path(os.path.dirname(__file__)) / '../resources' +except NameError: + # running interactively + resourcefilepath = Path('./resources') + start_date = Date(2010, 1, 1) end_date = Date(2010, 1, 2) +popsize = 1000 -@pytest.mark.slow -def test_basic_run(tmpdir, seed): - """Run the simulation with the diabetic_retinopathy module and read the log from the diabetic_retinopathy module.""" +def get_simulation(seed): + """Return simulation objection with Diabetic Retinopathy and other necessary modules registered.""" + sim = Simulation( + start_date=start_date, + seed=seed, + ) - popsize = 1000 + sim.register(demography.Demography(resourcefilepath=resourcefilepath), + simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), + enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), + healthsystem.HealthSystem(resourcefilepath=resourcefilepath, + disable=False, + cons_availability='all'), + symptommanager.SymptomManager(resourcefilepath=resourcefilepath), + healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath, + # force symptoms to lead to health care seeking: + force_any_symptom_to_lead_to_healthcareseeking=True + ), + healthburden.HealthBurden(resourcefilepath=resourcefilepath), + cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + diabetic_retinopathy.DiabeticRetinopathy(), + depression.Depression(resourcefilepath=resourcefilepath), + ) + return sim + + +def get_simulation_healthsystemdisabled(seed): + """Make the simulation with the health system disabled + """ sim = Simulation( start_date=start_date, seed=seed, - log_config={ - 'filename': 'temp', - 'directory': tmpdir, - }, ) + # Register the appropriate modules sim.register(demography.Demography(resourcefilepath=resourcefilepath), simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), healthsystem.HealthSystem(resourcefilepath=resourcefilepath, - disable=False, - cons_availability='all'), + disable=True), symptommanager.SymptomManager(resourcefilepath=resourcefilepath), healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath, # force symptoms to lead to health care seeking: - force_any_symptom_to_lead_to_healthcareseeking=True + force_any_symptom_to_lead_to_healthcareseeking=False ), healthburden.HealthBurden(resourcefilepath=resourcefilepath), cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), diabetic_retinopathy.DiabeticRetinopathy(), depression.Depression(resourcefilepath=resourcefilepath), ) + return sim + + +def check_dtypes(sim): + df = sim.population.props + orig = sim.population.new_row + assert (df.dtypes == orig.dtypes).all() + + +def zero_out_init_prev(sim): + # Set initial prevalence to zero: + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = 0.0 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 + return sim + + +def check_configuration_of_population(sim): + df = sim.population.props.copy() + + # Boolean for any stage of diabetic retinopathy + df['dr_status_any_stage'] = df.dr_status != 'none' + + # Get alive people: + df = df.loc[df.is_alive] + + # check that diagnosis and treatment is never applied to someone who has never had diabetic retinopathy: + assert pd.isnull(df.loc[df.dr_status == 'none', 'dr_date_diagnosis']).all() + assert pd.isnull(df.loc[df.dr_status == 'none', 'dr_date_treatment']).all() + + # check that those with symptoms are a subset of those with diabetic retinopathy: + assert set(sim.modules['SymptomManager'].who_has('blindness_full')).issubset(df.index[df.dr_status != 'none']) + assert set(sim.modules['SymptomManager'].who_has('blindness_partial')).issubset(df.index[df.dr_status != 'none']) + + # check that those diagnosed are a subset of those with any dr (and that the date makes sense): + assert set(df.index[~pd.isnull(df.dr_date_diagnosis)]).issubset(df.index[df.dr_status_any_stage]) + + +@pytest.mark.slow +def test_basic_run(seed): + """Run the simulation with the diabetic_retinopathy module and read the log from the diabetic_retinopathy module.""" + sim = get_simulation(seed) sim.make_initial_population(n=popsize) - sim.simulate(end_date=Date(2010, 2, 1)) # Long run + + check_dtypes(sim) + #TODO Add check params when resourcefile has been created + # check_params_read(sim) + sim.simulate(end_date=Date(2010, 5, 1)) + check_dtypes(sim) + + +def test_initial_config_of_pop_zero_prevalence(seed): + """Tests of the the way the population is configured: with zero initial prevalence values """ + sim = get_simulation_healthsystemdisabled(seed=seed) + sim = zero_out_init_prev(sim) + sim.make_initial_population(n=popsize) + check_dtypes(sim) + check_configuration_of_population(sim) + df = sim.population.props + assert (df.loc[df.is_alive].dr_status == 'none').all() + + From 6df9cf57d8e1215eeff944d944cfcc65c1c07c52 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 28 Feb 2025 12:39:47 +0200 Subject: [PATCH 09/85] tidy up --- src/tlo/methods/diabetic_retinopathy.py | 26 +++++++------------------ tests/test_diabetic_retinopathy.py | 3 +-- 2 files changed, 8 insertions(+), 21 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 1e090dd643..b4be16c590 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -167,7 +167,6 @@ def on_simulation_end(self) -> None: def make_the_linear_models(self) -> None: """Make and save LinearModels that will be used when the module is running""" - self.lm = dict() self.lm['onset_early_dr'] = LinearModel( @@ -195,10 +194,9 @@ def look_up_consumable_item_codes(self): # get_item_codes('Disposables gloves, powder free, 100 pieces per box'): 1, # } self.cons_item_codes['eye_injection'] = { - get_item_codes("Anesthetic Eye drops, 15ml"): 1, - get_item_codes('Aflibercept, 2mg'): 3, - } - + get_item_codes("Anesthetic Eye drops, 15ml"): 1, + get_item_codes('Aflibercept, 2mg'): 3, + } class DrPollEvent(RegularEvent, PopulationScopeEventMixin): @@ -216,18 +214,12 @@ def apply(self, population: Population) -> None: will_progress = self.module.lm['onset_early_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # will_progress_idx = will_progress[will_progress].index - # will_progress_idx = df.index[np.where(will_progress)[0]] will_progress_idx = df.index[np.where(will_progress)[0]] - # old_will_progress_idx = will_progress[will_progress].index - # Count new early cases for incidence tracking - new_early_cases = len(will_progress_idx) df.loc[will_progress_idx, 'dr_status'] = 'early' early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) # early_to_late_idx = early_to_late[early_to_late].index early_to_late_idx = df.index[np.where(early_to_late)[0]] - # Count new late cases for incidence tracking - new_late_cases = len(early_to_late_idx) df.loc[early_to_late_idx, 'dr_status'] = 'late' fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) @@ -267,7 +259,6 @@ def do_at_generic_first_appt_emergency( schedule_hsi_event(event, priority=1, topen=self.sim.date) - class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): """ This event is scheduled by do_at_generic_first_appt_emergency following presentation for care with the symptoms @@ -284,7 +275,6 @@ def __init__(self, module, person_id): self.ACCEPTED_FACILITY_LEVEL = '1a' self.ALERT_OTHER_DISEASES = [] - def apply(self, person_id, squeeze_factor): df = self.sim.population.props person = df.loc[person_id] @@ -332,9 +322,6 @@ def apply(self, person_id, squeeze_factor): ) - - -#TODO HSI_Dr_StartTreatment should be called by HSI_Dr_TestingFollowingSymptoms class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ This event initiates the treatment of DR. @@ -368,9 +355,10 @@ def apply(self, person_id, squeeze_factor): treatment_slows_progression_to_late = randomly_sampled < self.module.parameters['p_medication'] #TODO Add consumables in codition below - is_cons_available = self.get_consumables( - self.module.cons_item_codes['eye_injection'] - ) + + # is_cons_available = self.get_consumables( + # self.module.cons_item_codes['eye_injection'] + # ) if treatment_slows_progression_to_late: df.at[person_id, 'dr_on_treatment'] = True diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index d2aaf11154..6a14cb7bda 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -130,7 +130,7 @@ def test_basic_run(seed): def test_initial_config_of_pop_zero_prevalence(seed): - """Tests of the the way the population is configured: with zero initial prevalence values """ + """Tests of the way the population is configured: with zero initial prevalence values """ sim = get_simulation_healthsystemdisabled(seed=seed) sim = zero_out_init_prev(sim) sim.make_initial_population(n=popsize) @@ -139,4 +139,3 @@ def test_initial_config_of_pop_zero_prevalence(seed): df = sim.population.props assert (df.loc[df.is_alive].dr_status == 'none').all() - From 3c41ba3766ce8661cc6fdda6da2aa750188bdd89 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 28 Feb 2025 13:05:00 +0200 Subject: [PATCH 10/85] more tidy up --- tests/test_diabetic_retinopathy.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 6a14cb7bda..4f8cb9786b 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -123,8 +123,6 @@ def test_basic_run(seed): sim.make_initial_population(n=popsize) check_dtypes(sim) - #TODO Add check params when resourcefile has been created - # check_params_read(sim) sim.simulate(end_date=Date(2010, 5, 1)) check_dtypes(sim) From 0a4800a24a66b628209d52af171493d8b66ca111 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 12 Mar 2025 13:39:44 +0200 Subject: [PATCH 11/85] reworked plots --- .../diabetic_retinopathy_analyses.py | 44 ++++++++++++++----- src/tlo/methods/diabetic_retinopathy.py | 13 +++--- 2 files changed, 38 insertions(+), 19 deletions(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index a07d5c38e1..939e399152 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -39,7 +39,7 @@ # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2011, 1, 1) +end_date = Date(2012, 1, 1) popsize = 5000 def run_sim(service_availability): @@ -84,22 +84,42 @@ def get_summary_stats(logfile): counts_by_stage['date'] = pd.to_datetime(counts_by_stage['date']) counts_by_stage = counts_by_stage.set_index('date', drop=True) + # summary = { + # 'total': counts_by_stage.filter(like='total_').sum(axis=1), + # 'off': counts_by_stage.filter(like='off_treatment_').sum(axis=1), + # 'tr': counts_by_stage.filter(like='treatment_').sum(axis=1), + # 'new_early': counts_by_stage.get('new_early', pd.Series(0, index=counts_by_stage.index)), + # 'new_late': counts_by_stage.get('new_late', pd.Series(0, index=counts_by_stage.index)) + # } + + # 2) NUMBERS UNDIAGNOSED-DIAGNOSED-TREATED-PALLIATIVE CARE OVER TIME (SUMMED ACROSS TYPES OF CANCER) + def get_cols_excl_none(allcols, stub): + # helper function to some columns with a certain prefix stub - excluding the 'none' columns (ie. those + # that do not have cancer) + cols = allcols[allcols.str.startswith(stub)] + cols_not_none = [s for s in cols if ("none" not in s)] + return cols_not_none + summary = { - 'total': counts_by_stage.filter(like='total_').sum(axis=1), - 'off': counts_by_stage.filter(like='off_treatment_').sum(axis=1), - 'tr': counts_by_stage.filter(like='treatment_').sum(axis=1), - 'new_early': counts_by_stage.get('new_early', pd.Series(0, index=counts_by_stage.index)), - 'new_late': counts_by_stage.get('new_late', pd.Series(0, index=counts_by_stage.index)) + 'total': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'total_')].sum(axis=1), + 'udx': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'undiagnosed_')].sum(axis=1), + 'dx': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'diagnosed_')].sum(axis=1), + 'tr': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'treatment_')].sum(axis=1) } counts_by_cascade = pd.DataFrame(summary) + # counts_by_stage['year'] = counts_by_stage.index.year + # incidence_by_stage = pd.DataFrame({'new_early': summary['new_early'], 'new_late': summary['new_late']}) + + # Rates of diagnosis per year: counts_by_stage['year'] = counts_by_stage.index.year - incidence_by_stage = pd.DataFrame({'new_early': summary['new_early'], 'new_late': summary['new_late']}) + annual_count_of_dxtr = counts_by_stage.groupby(by='year')[['diagnosed_since_last_log', + 'treated_since_last_log']].sum() return { 'total_counts_by_stage_over_time': counts_by_stage, 'counts_by_cascade': counts_by_cascade, - 'incidence_by_stage': incidence_by_stage + 'annual_count_of_dxtr': annual_count_of_dxtr } @@ -133,14 +153,14 @@ def plot_treatment_cascade(counts_by_cascade, title): fig, ax = plt.subplots(figsize=(12, 6)) - counts_by_cascade[['off', 'tr']].plot( + counts_by_cascade[['udx', 'dx', 'tr']].plot( kind='bar', stacked=True, ax=ax, colormap="coolwarm" ) ax.set_title(title) ax.set_xlabel("Time (Months & Years)") ax.set_ylabel("Number of People") - ax.legend(["Off Treatment", "On Treatment"]) + ax.legend(['Undiagnosed', 'Diagnosed', 'On Treatment']) plt.xticks(rotation=45) plt.tight_layout() @@ -175,5 +195,5 @@ def plot_dr_incidence(incidence_by_stage, title): plot_dr_progression(results_no_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (No Health System)") plot_treatment_cascade(results_with_healthsystem['counts_by_cascade'], "Treatment Status Over Time (With Health System)") plot_treatment_cascade(results_no_healthsystem['counts_by_cascade'], "Treatment Status Over Time (No Health System)") -plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") -plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") +# plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") +# plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b4be16c590..897bc81863 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -277,7 +277,7 @@ def __init__(self, module, person_id): def apply(self, person_id, squeeze_factor): df = self.sim.population.props - person = df.loc[person_id] + # person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] # Ignore this event if the person is no longer alive: @@ -410,14 +410,13 @@ def apply(self, population): out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( df.dr_date_treatment)), 'dr_status'].value_counts().items()}) - # Count new cases - new_early_cases = len(df.loc[df.is_alive & (df.dr_status == 'early') & (df.dr_date_treatment == self.sim.date)]) - new_late_cases = len(df.loc[df.is_alive & (df.dr_status == 'late') & (df.dr_date_treatment == self.sim.date)]) - # Log incidence counts + date_now = self.sim.date + date_lastlog = self.sim.date - pd.DateOffset(months=self.repeat) + out.update({ - 'new_early': new_early_cases, - 'new_late': new_late_cases + 'diagnosed_since_last_log': df.dr_date_diagnosis.between(date_lastlog, date_now).sum(), + 'treated_since_last_log': df.dr_date_treatment.between(date_lastlog, date_now).sum(), }) logger.info(key='summary_stats', data=out) From 7c2729b89782c7a6c68dc43c8ea45e80f19532cf Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 12 Mar 2025 16:15:46 +0200 Subject: [PATCH 12/85] High prevalence tests and Diet Management HSI. HSI call Incomplete --- src/tlo/methods/diabetic_retinopathy.py | 78 ++++++++++++++++++------- tests/test_diabetic_retinopathy.py | 36 ++++++++++++ 2 files changed, 94 insertions(+), 20 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 897bc81863..eaa3cd5d6f 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -30,17 +30,18 @@ class DiabeticRetinopathy(Module): } PARAMETERS = { - 'rate_onset_to_early_dr': Parameter(Types.REAL, - 'Probability of people who get diagnosed with early diabetic retinopathy'), - 'rate_progression_to_dr': Parameter(Types.REAL, - 'Probability of people who get diagnosed with late diabetic retinopathy'), + "rate_onset_to_early_dr": Parameter(Types.REAL, + "Probability of people who get diagnosed with early diabetic retinopathy"), + "rate_progression_to_dr": Parameter(Types.REAL, + "Probability of people who get diagnosed with late diabetic retinopathy"), 'prob_fast_dr': Parameter(Types.REAL, - 'Probability of people who get diagnosed from none phase to late diabetic ' - 'retinopathy stage'), - 'init_prob_any_dr': Parameter(Types.REAL, 'Initial probability of anyone with diabetic retinopathy'), - 'init_prob_late_dr': Parameter(Types.REAL, - 'Initial probability of people with diabetic retinopathy in the late stage'), - 'p_medication': Parameter(Types.REAL, 'Diabetic retinopathy treatment/medication effectiveness'), + "Probability of people who get diagnosed from none phase to late diabetic " + "retinopathy stage"), + #TODO Change init_prob_any_dr to LIST + "init_prob_any_dr": Parameter(Types.REAL, "Initial probability of anyone with diabetic retinopathy"), + "init_prob_late_dr": Parameter(Types.REAL, + "Initial probability of people with diabetic retinopathy in the late stage"), + "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), } PROPERTIES = { @@ -53,21 +54,21 @@ class DiabeticRetinopathy(Module): ], description="dr status", ), - 'dr_on_treatment': Property( - Types.BOOL, 'Whether this person is on diabetic retinopathy treatment', + "dr_on_treatment": Property( + Types.BOOL, "Whether this person is on diabetic retinopathy treatment", ), - 'dr_date_treatment': Property( + "dr_date_treatment": Property( Types.DATE, - 'date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)' + "date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)" ), - 'dr_early_diagnosed': Property( - Types.BOOL, 'Whether this person has been diagnosed with early diabetic retinopathy' + "dr_early_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with early diabetic retinopathy" ), - 'dr_late_diagnosed': Property( - Types.BOOL, 'Whether this person has been diagnosed with late diabetic retinopathy' + "dr_late_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with late diabetic retinopathy" ), - 'dr_diagnosed': Property( - Types.BOOL, 'Whether this person has been diagnosed with any diabetic retinopathy' + "dr_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy" ), "dr_date_diagnosis": Property( Types.DATE, @@ -77,6 +78,9 @@ class DiabeticRetinopathy(Module): Types.BOOL, "whether blindness has been investigated, and diabetic retinopathy missed" ), + "dr_ever_diet_mgmt": Property(Types.BOOL, + "whether this person has ever had a diabetic retinopathy management" + "session in the diabetic clinic"), } @@ -322,6 +326,40 @@ def apply(self, person_id, squeeze_factor): ) + +class HSI_Dr_DietManagement(HSI_Event, IndividualScopeEventMixin): + """This is a Health System Interaction Event in which a person receives a session of diet management in the + diabetes clinic. It is one of a course of 5 sessions (at months 0, 6, 12, 18, 24). If one of these HSI does not happen + then no further sessions occur. Sessions after the first have no direct effect, as the only property affected is + reflects ever having had one session of talking therapy.""" + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + + self.TREATMENT_ID = 'Dr_DietManagement' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) + self.ACCEPTED_FACILITY_LEVEL = '1b' + self.num_of_sessions_had = 0 # A counter for the number of diet management sessions had + + def apply(self, person_id, squeeze_factor): + """Set the property `dr_ever_diet_mgmt` to be True and schedule the next session in the course if the person + has not yet had 5 sessions.""" + + self.num_of_sessions_had += 1 + + df = self.sim.population.props + if not df.at[person_id, 'dr_ever_diet_mgmt']: + df.at[person_id, 'dr_ever_diet_mgmt'] = True + + if self.num_of_sessions_had < 5: + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=self, + topen=self.sim.date + pd.DateOffset(months=6), + tclose=None, + priority=1 + ) + + class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ This event initiates the treatment of DR. diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 4f8cb9786b..35cbc2f498 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -90,10 +90,24 @@ def check_dtypes(sim): def zero_out_init_prev(sim): # Set initial prevalence to zero: + # Change to [0.0] * 2 (or num of stages) after getting all stages from Shaffi and changing TYPE to LIST sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = 0.0 sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 return sim +def make_high_init_prev(sim): + # Set initial prevalence to a high value: + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = 0.1 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 + return sim + +def incr_rates_of_progression(sim): + # Rates of DR progression: + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_early_dr'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_progression_to_dr'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['prob_fast_dr'] *= 5 + return sim + def check_configuration_of_population(sim): df = sim.population.props.copy() @@ -137,3 +151,25 @@ def test_initial_config_of_pop_zero_prevalence(seed): df = sim.population.props assert (df.loc[df.is_alive].dr_status == 'none').all() + +def test_initial_config_of_pop_high_prevalence(seed): + """Tests the way the population is configured: with high initial prevalence values """ + sim = get_simulation_healthsystemdisabled(seed=seed) + sim = make_high_init_prev(sim) + sim.make_initial_population(n=popsize) + check_dtypes(sim) + check_configuration_of_population(sim) + +@pytest.mark.slow +def test_run_sim_from_high_prevalence(seed): + """Run the simulation from the usual prevalence values and high rates of incidence and check configuration of + properties at the end""" + sim = get_simulation_healthsystemdisabled(seed=seed) + sim = make_high_init_prev(sim) + sim = incr_rates_of_progression(sim) + sim.make_initial_population(n=popsize) + check_dtypes(sim) + check_configuration_of_population(sim) + sim.simulate(end_date=Date(2010, 4, 1)) + check_dtypes(sim) + check_configuration_of_population(sim) From 4b3579291394df4e00d134ff8c5b18de436517e9 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 13 Mar 2025 16:08:57 +0200 Subject: [PATCH 13/85] comment out unused variables --- .../diabetic_retinopathy_analyses.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 939e399152..5f9ae773b4 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -43,10 +43,10 @@ popsize = 5000 def run_sim(service_availability): - log_config = { - 'filename': 'LogFile', - 'directory': outputpath - } + # log_config = { + # 'filename': 'LogFile', + # 'directory': outputpath + # } sim = Simulation(start_date=start_date, seed=0, log_config={"filename": "LogFile"}) # Register the appropriate modules From ba71d979b0e4d552cf7980b5f4ee54cae7992c4a Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 17 Mar 2025 16:05:29 +0200 Subject: [PATCH 14/85] diet management initial param and linear model. Define treatment IDs in priority_rank. Rework utils color map --- .../CVD.csv | 4 +-- .../ClinicallyVulnerable.csv | 4 +-- .../Default.csv | 4 +-- .../EHP_III.csv | 4 +-- .../LCOA_EHP.csv | 4 +-- .../Naive.csv | 4 +-- .../RMNCH.csv | 4 +-- .../Test Mode 1.csv | 4 +-- .../Test.csv | 4 +-- .../VerticalProgrammes.csv | 4 +-- src/tlo/analysis/utils.py | 2 +- src/tlo/methods/diabetic_retinopathy.py | 36 +++++++++++++++---- 12 files changed, 51 insertions(+), 27 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 52b99ed461..d6dec096ca 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cc09af1e8f19821e0db693fe260ab1775409fa8a391ed2ccccf09b96543528f5 -size 3499 +oid sha256:6fcf65f3c87f7f8e3fdd8b6cc44c01ffa9071a11dd5e6d2d09d2d74f98c4418b +size 3692 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index 8c7ff906fe..b69289e834 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:a34370ec4e83a3726bbf4f28c6c309e52ed033e7d9b48f53888496fb7aa5a7ee -size 3159 +oid sha256:9702fc9746ffaa1215068a909c4feb7b0413c81783a885ca2dc745e8949af8b8 +size 3352 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 1262bd6035..a0c9cecbab 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cfb5baf5936b7ba3c207d627d55ba2c44d1d01958a30de5e54caf20ddb3edd20 -size 3501 +oid sha256:a37e328872a5abcd130d21545a5323a3e74a69352ad099350b700f886e4b56ee +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index f37a393041..803c8f02c0 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:57449b3c28576e94797e8d400bc268cf9201d7e596c806924bdc30525d699c77 -size 3500 +oid sha256:a7c5300bfc989596f8b4b09b81b66367ec00e06cc138e01ab25178af8dc615ab +size 3693 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 83d405f0ac..20b3c71800 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:c93a6fb2e4cad0fc034b14b272453b70e1642ee818d1871a64c77466699bd123 -size 3499 +oid sha256:a0c8192848d16e383928bb8153dffbdbf4a4d1a8e512626dc5b9758214bbbd47 +size 3692 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index 2540feeadc..616ab663a1 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:0fe06f32b2f70bb1ca4c1f7352b903ba525afa314e614a71d67aa29ca376e17e -size 3499 +oid sha256:613859532affc86192a53efaf681e55a60a866435522da9673ce991c1e1d828f +size 3692 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 6fe57d665a..57f0e08304 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:ad79df6d5a331739def0c5fcb0d4c8ffb7c803442db519da53a19d566886a41b -size 3484 +oid sha256:2481aeb6d5a954afe810bb7985eadccc88c10a14392fa13d96e101abc2faa7d4 +size 3677 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 5db5e3409f..2f064550b6 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:be03d20472c7f1e476a02dfd8ebcf0f218a0cf0aa7fa12cf55a83139e26bab7e -size 3501 +oid sha256:97e88ec0bdfa7fbb4793dcaa173d93fd24057a9cc6607299e4b07ba4885cc58d +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 02d1286257..48b3d0fcfb 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:79d1805d9389115bbd2a32296b6e81e4ae5f8465e4ef11b0708400e4e3f85407 -size 3501 +oid sha256:1115b157ed0b031467ebca6ea3a205f025cfff04636feb29f9d34c0f2f1389d7 +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 1df2416902..0dae174ec6 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:419b8f59fe5bd8cbcc212c4b5425c42a7d1172416cd3488c81a3533c84092e2b -size 3499 +oid sha256:e895d941bac75771fa64b8c518c5646ff3072b0446890672fbe937f4a4175882 +size 3692 diff --git a/src/tlo/analysis/utils.py b/src/tlo/analysis/utils.py index 669b4348b7..95bce8289a 100644 --- a/src/tlo/analysis/utils.py +++ b/src/tlo/analysis/utils.py @@ -888,7 +888,7 @@ def get_color_coarse_appt(coarse_appt_type: str) -> str: 'Schisto*': 'skyblue', 'CardioMetabolicDisorders*': 'brown', - 'DiabeticRetinopathy*': 'coffee', + 'Dr*': 'firebrick', 'BladderCancer*': 'orchid', 'BreastCancer*': 'mediumvioletred', diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index eaa3cd5d6f..8d7770923c 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -42,6 +42,10 @@ class DiabeticRetinopathy(Module): "init_prob_late_dr": Parameter(Types.REAL, "Initial probability of people with diabetic retinopathy in the late stage"), "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), + "init_prob_ever_diet_mgmt_if_diagnosed": Parameter( + Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " + "with diabetic retinopathy" + ), } PROPERTIES = { @@ -79,7 +83,7 @@ class DiabeticRetinopathy(Module): "whether blindness has been investigated, and diabetic retinopathy missed" ), "dr_ever_diet_mgmt": Property(Types.BOOL, - "whether this person has ever had a diabetic retinopathy management" + "whether this person has ever had a diabetic retinopathy diet management" "session in the diabetic clinic"), } @@ -102,6 +106,7 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['init_prob_any_dr'] = 0.36 self.parameters['init_prob_late_dr'] = 0.09 self.parameters['p_medication'] = 0.8 + self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] = 0.1 self.sim.modules['SymptomManager'].register_symptom( Symptom(name='blindness_partial'), @@ -140,6 +145,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False + df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation @@ -165,6 +171,7 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False + self.sim.population.props.at[child_id, 'dr_ever_diet_mgmt'] = False def on_simulation_end(self) -> None: pass @@ -188,6 +195,11 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['prob_fast_dr'] ) + self.lm['ever_diet_mgmt_initialisation'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + intercept=self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] + ) + def look_up_consumable_item_codes(self): """Look up the item codes used in the HSI of this module""" get_item_codes = self.sim.modules['HealthSystem'].get_item_code_from_item_name @@ -247,7 +259,7 @@ def apply(self, population: Population) -> None: disease_module=self.module, ) - def do_at_generic_first_appt_emergency( + def do_at_generic_first_appt( self, person_id: int, symptoms: List[str], @@ -274,9 +286,9 @@ class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): def __init__(self, module, person_id): super().__init__(module, person_id=person_id) - self.TREATMENT_ID = "DiabeticRetinopathy_Investigation" + self.TREATMENT_ID = "Dr_Investigation" self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1}) - self.ACCEPTED_FACILITY_LEVEL = '1a' + self.ACCEPTED_FACILITY_LEVEL = '2' self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): @@ -338,7 +350,7 @@ def __init__(self, module, person_id): self.TREATMENT_ID = 'Dr_DietManagement' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) - self.ACCEPTED_FACILITY_LEVEL = '1b' + self.ACCEPTED_FACILITY_LEVEL = '2' self.num_of_sessions_had = 0 # A counter for the number of diet management sessions had def apply(self, person_id, squeeze_factor): @@ -372,7 +384,7 @@ def __init__(self, module, person_id): # Define the necessary information for an HSI self.TREATMENT_ID = 'Dr_Treatment_Initiation' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) - self.ACCEPTED_FACILITY_LEVEL = '1a' + self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): @@ -452,9 +464,21 @@ def apply(self, population): date_now = self.sim.date date_lastlog = self.sim.date - pd.DateOffset(months=self.repeat) + n_any_dr = (df.is_alive & ((df.dr_status == "late") | (df.dr_status == "early"))).sum() + n_ever_diet_mgmt = ( + df.dr_ever_diet_mgmt & df.is_alive & ((df.dr_status == "late") | (df.dr_status == "early"))).sum() + + def zero_out_nan(x): + return x if not np.isnan(x) else 0.0 + + def safe_divide(x, y): + return float(x / y) if y > 0.0 else 0.0 + + out.update({ 'diagnosed_since_last_log': df.dr_date_diagnosis.between(date_lastlog, date_now).sum(), 'treated_since_last_log': df.dr_date_treatment.between(date_lastlog, date_now).sum(), + 'prop_ever_diet_mgmt_if_any_dr': zero_out_nan(safe_divide(n_ever_diet_mgmt, n_any_dr)), }) logger.info(key='summary_stats', data=out) From 4e6e8a71a55d7a898b4790cf6cd03e95e93dd44b Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 21 Mar 2025 16:27:27 +0200 Subject: [PATCH 15/85] Selected for regular eye exam --- src/tlo/methods/diabetic_retinopathy.py | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 8d7770923c..41363c6d78 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -46,6 +46,9 @@ class DiabeticRetinopathy(Module): Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " "with diabetic retinopathy" ), + "prob_reg_eye_exam": Parameter( + Types.REAL, "Probability of people with Diabetes Mellitus selected for regular eye exam" + ), } PROPERTIES = { @@ -107,6 +110,7 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['init_prob_late_dr'] = 0.09 self.parameters['p_medication'] = 0.8 self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] = 0.1 + self.parameters['prob_reg_eye_exam'] = 0.05 self.sim.modules['SymptomManager'].register_symptom( Symptom(name='blindness_partial'), @@ -243,6 +247,24 @@ def apply(self, population: Population) -> None: fast_dr_idx = df.index[np.where(fast_dr)[0]] df.loc[fast_dr_idx, 'dr_status'] = 'late' + eligible_for_ns_threatening = df.loc[df.is_alive & df.nc_diabetes & (df.age_years >= 40) + & (df.dr_status == 'none')] + + df.loc[eligible_for_ns_threatening, 'selected_for_regular_eye_exam'] = ( + np.random.random_sample(size=len(df[eligible_for_ns_threatening])) + < self.module.parameters['prob_reg_eye_exam']) + + # Schedule HSI event for selected individuals + selected_for_exam = df.index[df['selected_for_regular_eye_exam']] + for person_id in selected_for_exam: + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Regular_Eye_Exam(module=self.module, person_id=person_id), + priority=0, + topen=self.sim.date, + tclose=None + ) + + if len(will_progress_idx): self.sim.modules['SymptomManager'].change_symptom( person_id=will_progress_idx, From cee5630f2f074ff67aab337392f67ad0e104f985 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 7 Apr 2025 11:35:46 +0200 Subject: [PATCH 16/85] New stages. 3 tests adjusted --- .../parameter_values.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 310 +++++++++++++----- tests/test_diabetic_retinopathy.py | 15 +- 3 files changed, 235 insertions(+), 94 deletions(-) diff --git a/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv b/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv index dc928eca48..4fe2812b34 100644 --- a/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv +++ b/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:36a05f9d9432101bea90c6f772930bfd47aa72ce053dc9ac37aa600c28d761b4 -size 1334 +oid sha256:332e44d101a5263a41eadcceee8bc0eeafc38d23aa45fe9fd6abed7a06aeed0b +size 1337 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 41363c6d78..085f884936 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -6,7 +6,7 @@ from tlo import DateOffset, Module, Parameter, Population, Property, Simulation, Types, logging from tlo.events import IndividualScopeEventMixin, PopulationScopeEventMixin, RegularEvent -from tlo.lm import LinearModel, LinearModelType +from tlo.lm import LinearModel, LinearModelType, Predictor from tlo.methods import Metadata from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler @@ -30,17 +30,21 @@ class DiabeticRetinopathy(Module): } PARAMETERS = { - "rate_onset_to_early_dr": Parameter(Types.REAL, - "Probability of people who get diagnosed with early diabetic retinopathy"), - "rate_progression_to_dr": Parameter(Types.REAL, - "Probability of people who get diagnosed with late diabetic retinopathy"), + "rate_onset_to_mild_dr": Parameter(Types.REAL, + "Probability of people who get diagnosed with mild diabetic retinopathy"), + "rate_mild_to_moderate": Parameter(Types.REAL, + "Probability of people who get diagnosed with moderate diabetic retinopathy"), + "rate_moderate_to_severe": Parameter(Types.REAL, + "Probability of people who get diagnosed with severe diabetic retinopathy"), + "rate_severe_to_proliferative": Parameter(Types.REAL, + "Probability of people who get diagnosed with proliferative diabetic retinopathy"), 'prob_fast_dr': Parameter(Types.REAL, - "Probability of people who get diagnosed from none phase to late diabetic " + "Probability of people who get diagnosed from none phase to proliferative diabetic " "retinopathy stage"), #TODO Change init_prob_any_dr to LIST - "init_prob_any_dr": Parameter(Types.REAL, "Initial probability of anyone with diabetic retinopathy"), - "init_prob_late_dr": Parameter(Types.REAL, - "Initial probability of people with diabetic retinopathy in the late stage"), + "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), + # "init_prob_proliferative_dr": Parameter(Types.REAL, + # "Initial probability of people with diabetic retinopathy in the proliferative stage"), "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), "init_prob_ever_diet_mgmt_if_diagnosed": Parameter( Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " @@ -49,6 +53,21 @@ class DiabeticRetinopathy(Module): "prob_reg_eye_exam": Parameter( Types.REAL, "Probability of people with Diabetes Mellitus selected for regular eye exam" ), + "rp_dr_tobacco": Parameter( + Types.REAL, "relative prevalence at baseline of diabetic retinopathy if tobacco" + ), + "rp_dr_ex_alc": Parameter( + Types.REAL, "relative prevalence at baseline of diabetic retinopathy if excessive alcohol" + ), + "rp_dr_high_sugar": Parameter( + Types.REAL, "relative prevalence at baseline of diabetic retinopathy if high sugar" + ), + "rp_dr_low_ex": Parameter( + Types.REAL, "relative prevalence at baseline of diabetic retinopathy if low exercise" + ), + "rp_dr_urban": Parameter( + Types.REAL, "relative prevalence at baseline of diabetic retinopathy if urban" + ), } PROPERTIES = { @@ -56,11 +75,18 @@ class DiabeticRetinopathy(Module): Types.CATEGORICAL, categories=[ "none", - "early", - "late", + "mild", # was early + "moderate", + "severe", + "proliferative", # was late ], description="dr status", ), + # "dr_status": Property( + # Types.CATEGORICAL, + # "DR status", + # categories=["none", "mild", "moderate", "severe", "proliferative"], + # ), "dr_on_treatment": Property( Types.BOOL, "Whether this person is on diabetic retinopathy treatment", ), @@ -68,11 +94,11 @@ class DiabeticRetinopathy(Module): Types.DATE, "date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)" ), - "dr_early_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with early diabetic retinopathy" + "dr_mild_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with mild diabetic retinopathy" ), - "dr_late_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with late diabetic retinopathy" + "dr_proliferative_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with proliferative diabetic retinopathy" ), "dr_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy" @@ -103,15 +129,27 @@ def read_parameters(self, data_folder: str | Path) -> None: """ #TODO Read from resourcefile - self.parameters['rate_onset_to_early_dr'] = 0.29 - self.parameters['rate_progression_to_dr'] = 0.07 + self.parameters['rate_onset_to_mild_dr'] = 0.29 + + self.parameters['rate_mild_to_moderate'] = 0.4 + self.parameters['rate_moderate_to_severe'] = 0.5 + + self.parameters['rate_severe_to_proliferative'] = 0.07 + self.parameters['prob_fast_dr'] = 0.5 - self.parameters['init_prob_any_dr'] = 0.36 - self.parameters['init_prob_late_dr'] = 0.09 + self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.2] + # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] + # self.parameters['init_prob_proliferative_dr'] = 0.09 self.parameters['p_medication'] = 0.8 self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] = 0.1 self.parameters['prob_reg_eye_exam'] = 0.05 + self.parameters['rp_dr_ex_alc'] = 1.1 + self.parameters['rp_dr_tobacco'] = 1.3 + self.parameters['rp_dr_high_sugar'] = 1.2 + self.parameters['rp_dr_low_ex'] = 1.3 + self.parameters['rp_dr_urban'] = 1.4 + self.sim.modules['SymptomManager'].register_symptom( Symptom(name='blindness_partial'), Symptom(name='blindness_full') @@ -128,22 +166,22 @@ def initialise_population(self, population: Population) -> None: alive_diabetes_idx = df.loc[df.is_alive & df.nc_diabetes].index - any_dr_idx = alive_diabetes_idx[ - self.rng.random_sample(size=len(alive_diabetes_idx)) < self.parameters['init_prob_any_dr'] - ] - no_dr_idx = set(alive_diabetes_idx) - set(any_dr_idx) - - late_dr_idx = any_dr_idx[ - self.rng.random_sample(size=len(any_dr_idx)) < self.parameters['init_prob_late_dr'] - ] - - early_dr_idx = set(any_dr_idx) - set(late_dr_idx) + # any_dr_idx = alive_diabetes_idx[ + # self.rng.random_sample(size=len(alive_diabetes_idx)) < self.parameters['init_prob_any_dr'] + # ] + # no_dr_idx = set(alive_diabetes_idx) - set(any_dr_idx) + # + # proliferative_dr_idx = any_dr_idx[ + # self.rng.random_sample(size=len(any_dr_idx)) < self.parameters['init_prob_proliferative_dr'] + # ] + # + # mild_dr_idx = set(any_dr_idx) - set(proliferative_dr_idx) # write to property: df.loc[df.is_alive & ~df.nc_diabetes, 'dr_status'] = 'none' - df.loc[list(no_dr_idx), 'dr_status'] = 'none' - df.loc[list(early_dr_idx), "dr_status"] = "early" - df.loc[list(late_dr_idx), "dr_status"] = "late" + # df.loc[list(no_dr_idx), 'dr_status'] = 'none' + # df.loc[list(mild_dr_idx), "dr_status"] = "mild" + # df.loc[list(proliferative_dr_idx), "dr_status"] = "proliferative" df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT @@ -151,6 +189,86 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False + # -------------------- dr_status ----------- + # Determine who has diabetic retinopathy at all stages: + # check parameters are sensible: probability of having any cancer stage cannot exceed 1.0 + assert sum(self.parameters['init_prob_any_dr']) <= 1.0 + + lm_init_dr_status_any_dr = LinearModel( + LinearModelType.MULTIPLICATIVE, + sum(self.parameters['init_prob_any_dr']), + Predictor('li_ex_alc').when(True, self.parameters['rp_dr_ex_alc']), + Predictor('li_tob').when(True, self.parameters['rp_dr_tobacco']), + Predictor('li_high_sugar').when(True, self.parameters['rp_dr_high_sugar']), + Predictor('li_low_ex').when(True, self.parameters['rp_dr_low_ex']), + Predictor('li_urban').when(True, self.parameters['rp_dr_urban']), + ) + + any_dr = \ + lm_init_dr_status_any_dr.predict(df.loc[df.is_alive & df.nc_diabetes], self.rng) + + # Get boolean Series of who has DR + has_dr = lm_init_dr_status_any_dr.predict(df.loc[df.is_alive & df.nc_diabetes], self.rng) + + # Get indices of those with DR + dr_idx = has_dr[has_dr].index if has_dr.any() else pd.Index([]) + + if not dr_idx.empty: + # Get non-none categories + categories = [cat for cat in df.dr_status.cat.categories if cat != 'none'] + + # Verify probabilities match categories + assert len(categories) == len(self.parameters['init_prob_any_dr']) + + # Normalize probabilities + total_prob = sum(self.parameters['init_prob_any_dr']) + probs = [p / total_prob for p in self.parameters['init_prob_any_dr']] + + # Assign DR stages + df.loc[dr_idx, 'dr_status'] = self.rng.choice( + categories, + size=len(dr_idx), + p=probs + ) + + + # dr_stage_probs = self.parameters["init_prob_any_dr"] + # Determine the stage of DR for those who have DM: + # if any_dr.sum(): + # categories = [cat for cat in df.dr_status.cat.categories if cat != 'none'] + # + # # Make sure we have the right number of probabilities + # assert len(categories) == len(self.parameters['init_prob_any_dr']) + # + # # Normalize probabilities + # sum_probs = sum(self.parameters['init_prob_any_dr']) + # prob_by_stage_of_dr_if_dr = [p / sum_probs for p in self.parameters['init_prob_any_dr']] + # + # # Assign statuses + # df.loc[any_dr, "dr_status"] = self.rng.choice( + # categories, + # size=any_dr.sum(), + # p=prob_by_stage_of_dr_if_dr + # ) + + # sum_probs = sum(self.parameters['init_prob_any_dr']) + # if sum_probs > 0: + # prob_by_stage_of_dr_if_dr = [i / sum_probs for i in self.parameters['init_prob_any_dr']] + # assert (sum(prob_by_stage_of_dr_if_dr) - 1.0) < 1e-10 + # # df.loc[any_dr, "dr_status"] = self.rng.choice( + # # dr_stage_probs[1:], # exclude "none" + # # size=len(df.loc[any_dr]), + # # p=dr_stage_probs + # # ) + # df.loc[any_dr, "dr_status"] = self.rng.choice( + # [val for val in df.dr_status.cat.categories if val != 'none'], + # size=any_dr.sum(), + # p=prob_by_stage_of_dr_if_dr + # ) + + # df.loc[~any_dr, "dr_status"] = "none" + + def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation * Schedule the main polling event @@ -184,21 +302,28 @@ def make_the_linear_models(self) -> None: """Make and save LinearModels that will be used when the module is running""" self.lm = dict() - self.lm['onset_early_dr'] = LinearModel( + self.lm['onset_mild_dr'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + intercept=self.parameters['rate_onset_to_mild_dr'] + ) + + self.lm['mild_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_onset_to_early_dr'] + intercept=self.parameters['rate_mild_to_moderate'] ) - self.lm['onset_late_dr'] = LinearModel( + self.lm['moderate_severe_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_progression_to_dr'] + intercept=self.parameters['rate_moderate_to_severe'] ) - self.lm['onset_fast_dr'] = LinearModel( + self.lm['severe_proliferative_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['prob_fast_dr'] + intercept=self.parameters['rate_severe_to_proliferative'] ) + + self.lm['ever_diet_mgmt_initialisation'] = LinearModel( LinearModelType.MULTIPLICATIVE, intercept=self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] @@ -230,40 +355,53 @@ def apply(self, population: Population) -> None: df = population.props diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] - diabetes_and_alive_earlydr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'early')] + diabetes_and_alive_milddr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'mild')] + diabetes_and_alive_moderatedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'moderate')] + diabetes_and_alive_severedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'severe')] - will_progress = self.module.lm['onset_early_dr'].predict(diabetes_and_alive_nodr, self.module.rng) + will_progress = self.module.lm['onset_mild_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # will_progress_idx = will_progress[will_progress].index will_progress_idx = df.index[np.where(will_progress)[0]] - df.loc[will_progress_idx, 'dr_status'] = 'early' - - early_to_late = self.module.lm['onset_late_dr'].predict(diabetes_and_alive_earlydr, self.module.rng) - # early_to_late_idx = early_to_late[early_to_late].index - early_to_late_idx = df.index[np.where(early_to_late)[0]] - df.loc[early_to_late_idx, 'dr_status'] = 'late' - - fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) - # fast_dr_idx = fast_dr[fast_dr].index - fast_dr_idx = df.index[np.where(fast_dr)[0]] - df.loc[fast_dr_idx, 'dr_status'] = 'late' - - eligible_for_ns_threatening = df.loc[df.is_alive & df.nc_diabetes & (df.age_years >= 40) - & (df.dr_status == 'none')] - - df.loc[eligible_for_ns_threatening, 'selected_for_regular_eye_exam'] = ( - np.random.random_sample(size=len(df[eligible_for_ns_threatening])) - < self.module.parameters['prob_reg_eye_exam']) - - # Schedule HSI event for selected individuals - selected_for_exam = df.index[df['selected_for_regular_eye_exam']] - for person_id in selected_for_exam: - self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Regular_Eye_Exam(module=self.module, person_id=person_id), - priority=0, - topen=self.sim.date, - tclose=None - ) - + df.loc[will_progress_idx, 'dr_status'] = 'mild' + + mild_to_moderate = self.module.lm['mild_moderate_dr'].predict(diabetes_and_alive_milddr, self.module.rng) + # mild_to_moderate_idx = mild_to_moderate[mild_to_moderate].index + mild_to_moderate_idx = df.index[np.where(mild_to_moderate)[0]] + df.loc[mild_to_moderate_idx, 'dr_status'] = 'moderate' + + moderate_to_severe = self.module.lm['moderate_severe_dr'].predict(diabetes_and_alive_moderatedr, + self.module.rng) + # moderate_to_severe_idx = moderate_to_severe[moderate_to_severe].index + moderate_to_severe_idx = df.index[np.where(moderate_to_severe)[0]] + df.loc[moderate_to_severe_idx, 'dr_status'] = 'severe' + + severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict(diabetes_and_alive_severedr, + self.module.rng) + # severe_to_proliferative_idx = mild_to_moderate[severe_to_proliferative].index + severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] + df.loc[severe_to_proliferative_idx, 'dr_status'] = 'severe' + + # fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) + # # fast_dr_idx = fast_dr[fast_dr].index + # fast_dr_idx = df.index[np.where(fast_dr)[0]] + # df.loc[fast_dr_idx, 'dr_status'] = 'late' + + # eligible_for_ns_threatening = df.loc[df.is_alive & df.nc_diabetes & (df.age_years >= 40) + # & (df.dr_status == 'none')] + # + # df.loc[eligible_for_ns_threatening, 'selected_for_regular_eye_exam'] = ( + # np.random.random_sample(size=len(df[eligible_for_ns_threatening])) + # < self.module.parameters['prob_reg_eye_exam']) + # + # # Schedule HSI event for selected individuals + # selected_for_exam = df.index[df['selected_for_regular_eye_exam']] + # for person_id in selected_for_exam: + # self.sim.modules['HealthSystem'].schedule_hsi_event( + # hsi_event=HSI_Regular_Eye_Exam(module=self.module, person_id=person_id), + # priority=0, + # topen=self.sim.date, + # tclose=None + # ) if len(will_progress_idx): self.sim.modules['SymptomManager'].change_symptom( @@ -273,9 +411,9 @@ def apply(self, population: Population) -> None: disease_module=self.module, ) - if len(early_to_late_idx): + if len(mild_to_moderate_idx): self.sim.modules['SymptomManager'].change_symptom( - person_id=early_to_late_idx, + person_id=mild_to_moderate_idx, symptom_string='blindness_full', add_or_remove='+', disease_module=self.module, @@ -284,11 +422,16 @@ def apply(self, population: Population) -> None: def do_at_generic_first_appt( self, person_id: int, - symptoms: List[str], + individual_properties: IndividualProperties, schedule_hsi_event: HSIEventScheduler, **kwargs, ) -> None: + has_dr = individual_properties["un_HAZ_category"] in ( + "HAZ<-3", + "-3<=HAZ<-2", + ) + if "blindness_full" in symptoms or "blindness_partial" in symptoms: event = HSI_Dr_TestingFollowingSymptoms( module=self, @@ -341,7 +484,7 @@ def apply(self, person_id, squeeze_factor): dx_tests_to_run='dilated_eye_exam_dr_blindness', hsi_event=self ) - # TODO Those in early DR must not go to start treatment since late DR Work can be managed with good blood + # TODO Those in mild and moderate DR must not go to start treatment since these can be managed with good blood # sugar control to slow the progression. if dx_result and is_cons_available: # record date of diagnosis @@ -360,7 +503,6 @@ def apply(self, person_id, squeeze_factor): ) - class HSI_Dr_DietManagement(HSI_Event, IndividualScopeEventMixin): """This is a Health System Interaction Event in which a person receives a session of diet management in the diabetes clinic. It is one of a course of 5 sessions (at months 0, 6, 12, 18, 24). If one of these HSI does not happen @@ -424,7 +566,7 @@ def apply(self, person_id, squeeze_factor): return self.sim.modules["HealthSystem"].get_blank_appt_footprint() randomly_sampled = self.module.rng.rand() - treatment_slows_progression_to_late = randomly_sampled < self.module.parameters['p_medication'] + treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] #TODO Add consumables in codition below @@ -432,24 +574,24 @@ def apply(self, person_id, squeeze_factor): # self.module.cons_item_codes['eye_injection'] # ) - if treatment_slows_progression_to_late: + if treatment_slows_progression_to_proliferative: df.at[person_id, 'dr_on_treatment'] = True df.at[person_id, 'dr_date_treatment'] = self.sim.date - # Reduce probability of progression to "late" DR - progression_chance = self.module.parameters['rate_progression_to_dr'] * ( + # Reduce probability of progression to "proliferative" DR + progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( 1 - self.module.parameters['p_medication']) # Determine if person will still progress if self.module.rng.rand() < progression_chance: - df.at[person_id, 'dr_status'] = 'late' + df.at[person_id, 'dr_status'] = 'proliferative' else: - df.at[person_id, 'dr_status'] = 'early' # Stays in early stage due to medication + df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication else: # If medication is not effective, progression happens as usual df.at[person_id, 'dr_on_treatment'] = True - df.at[person_id, 'dr_status'] = 'late' + df.at[person_id, 'dr_status'] = 'proliferative' class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): @@ -482,13 +624,12 @@ def apply(self, population): out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( df.dr_date_treatment)), 'dr_status'].value_counts().items()}) - date_now = self.sim.date date_lastlog = self.sim.date - pd.DateOffset(months=self.repeat) - n_any_dr = (df.is_alive & ((df.dr_status == "late") | (df.dr_status == "early"))).sum() + n_any_dr = (df.is_alive & ((df.dr_status == "proliferative") | (df.dr_status == "mild"))).sum() n_ever_diet_mgmt = ( - df.dr_ever_diet_mgmt & df.is_alive & ((df.dr_status == "late") | (df.dr_status == "early"))).sum() + df.dr_ever_diet_mgmt & df.is_alive & ((df.dr_status == "proliferative") | (df.dr_status == "mild"))).sum() def zero_out_nan(x): return x if not np.isnan(x) else 0.0 @@ -496,7 +637,6 @@ def zero_out_nan(x): def safe_divide(x, y): return float(x / y) if y > 0.0 else 0.0 - out.update({ 'diagnosed_since_last_log': df.dr_date_diagnosis.between(date_lastlog, date_now).sum(), 'treated_since_last_log': df.dr_date_treatment.between(date_lastlog, date_now).sum(), diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 35cbc2f498..6cb85807ff 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -91,21 +91,22 @@ def check_dtypes(sim): def zero_out_init_prev(sim): # Set initial prevalence to zero: # Change to [0.0] * 2 (or num of stages) after getting all stages from Shaffi and changing TYPE to LIST - sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = 0.0 - sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.0] * 4 + # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 return sim def make_high_init_prev(sim): # Set initial prevalence to a high value: - sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = 0.1 - sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.1] * 4 + # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 return sim def incr_rates_of_progression(sim): # Rates of DR progression: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_early_dr'] *= 5 - sim.modules['DiabeticRetinopathy'].parameters['rate_progression_to_dr'] *= 5 - sim.modules['DiabeticRetinopathy'].parameters['prob_fast_dr'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_mild_to_moderate'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_moderate_to_severe'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_severe_to_proliferative'] *= 5 return sim From 780d43854917221fe114349747cf33b0b33e3cca Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 7 Apr 2025 14:46:28 +0200 Subject: [PATCH 17/85] Remove Testing HSI --- src/tlo/methods/diabetic_retinopathy.py | 270 +++++++++++++----------- 1 file changed, 149 insertions(+), 121 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 085f884936..32724155ac 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -11,6 +11,7 @@ from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.methods.symptommanager import Symptom +from tlo.population import IndividualProperties logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -31,13 +32,13 @@ class DiabeticRetinopathy(Module): PARAMETERS = { "rate_onset_to_mild_dr": Parameter(Types.REAL, - "Probability of people who get diagnosed with mild diabetic retinopathy"), + "Probability of people who get diagnosed with mild diabetic retinopathy"), "rate_mild_to_moderate": Parameter(Types.REAL, - "Probability of people who get diagnosed with moderate diabetic retinopathy"), + "Probability of people who get diagnosed with moderate diabetic retinopathy"), "rate_moderate_to_severe": Parameter(Types.REAL, - "Probability of people who get diagnosed with severe diabetic retinopathy"), + "Probability of people who get diagnosed with severe diabetic retinopathy"), "rate_severe_to_proliferative": Parameter(Types.REAL, - "Probability of people who get diagnosed with proliferative diabetic retinopathy"), + "Probability of people who get diagnosed with proliferative diabetic retinopathy"), 'prob_fast_dr': Parameter(Types.REAL, "Probability of people who get diagnosed from none phase to proliferative diabetic " "retinopathy stage"), @@ -231,7 +232,6 @@ def initialise_population(self, population: Population) -> None: p=probs ) - # dr_stage_probs = self.parameters["init_prob_any_dr"] # Determine the stage of DR for those who have DM: # if any_dr.sum(): @@ -251,24 +251,23 @@ def initialise_population(self, population: Population) -> None: # p=prob_by_stage_of_dr_if_dr # ) - # sum_probs = sum(self.parameters['init_prob_any_dr']) - # if sum_probs > 0: - # prob_by_stage_of_dr_if_dr = [i / sum_probs for i in self.parameters['init_prob_any_dr']] - # assert (sum(prob_by_stage_of_dr_if_dr) - 1.0) < 1e-10 - # # df.loc[any_dr, "dr_status"] = self.rng.choice( - # # dr_stage_probs[1:], # exclude "none" - # # size=len(df.loc[any_dr]), - # # p=dr_stage_probs - # # ) - # df.loc[any_dr, "dr_status"] = self.rng.choice( - # [val for val in df.dr_status.cat.categories if val != 'none'], - # size=any_dr.sum(), - # p=prob_by_stage_of_dr_if_dr - # ) + # sum_probs = sum(self.parameters['init_prob_any_dr']) + # if sum_probs > 0: + # prob_by_stage_of_dr_if_dr = [i / sum_probs for i in self.parameters['init_prob_any_dr']] + # assert (sum(prob_by_stage_of_dr_if_dr) - 1.0) < 1e-10 + # # df.loc[any_dr, "dr_status"] = self.rng.choice( + # # dr_stage_probs[1:], # exclude "none" + # # size=len(df.loc[any_dr]), + # # p=dr_stage_probs + # # ) + # df.loc[any_dr, "dr_status"] = self.rng.choice( + # [val for val in df.dr_status.cat.categories if val != 'none'], + # size=any_dr.sum(), + # p=prob_by_stage_of_dr_if_dr + # ) # df.loc[~any_dr, "dr_status"] = "none" - def initialise_simulation(self, sim: Simulation) -> None: """ This is where you should include all things you want to be happening during simulation * Schedule the main polling event @@ -322,8 +321,6 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['rate_severe_to_proliferative'] ) - - self.lm['ever_diet_mgmt_initialisation'] = LinearModel( LinearModelType.MULTIPLICATIVE, intercept=self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] @@ -334,10 +331,10 @@ def look_up_consumable_item_codes(self): get_item_codes = self.sim.modules['HealthSystem'].get_item_code_from_item_name self.cons_item_codes = dict() - # self.cons_item_codes['laser_photocoagulation'] = { - # get_item_codes("Anesthetic Eye drops, 15ml"): 3, - # get_item_codes('Disposables gloves, powder free, 100 pieces per box'): 1, - # } + self.cons_item_codes['laser_photocoagulation'] = { + get_item_codes("Anesthetic Eye drops, 15ml"): 1, + get_item_codes('Disposables gloves, powder free, 100 pieces per box'): 2, + } self.cons_item_codes['eye_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes('Aflibercept, 2mg'): 3, @@ -376,10 +373,10 @@ def apply(self, population: Population) -> None: df.loc[moderate_to_severe_idx, 'dr_status'] = 'severe' severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict(diabetes_and_alive_severedr, - self.module.rng) + self.module.rng) # severe_to_proliferative_idx = mild_to_moderate[severe_to_proliferative].index severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] - df.loc[severe_to_proliferative_idx, 'dr_status'] = 'severe' + df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' # fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # # fast_dr_idx = fast_dr[fast_dr].index @@ -427,80 +424,95 @@ def do_at_generic_first_appt( **kwargs, ) -> None: - has_dr = individual_properties["un_HAZ_category"] in ( - "HAZ<-3", - "-3<=HAZ<-2", - ) - - if "blindness_full" in symptoms or "blindness_partial" in symptoms: - event = HSI_Dr_TestingFollowingSymptoms( - module=self, - person_id=person_id, - ) - schedule_hsi_event(event, priority=1, topen=self.sim.date) - - -class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): - """ - This event is scheduled by do_at_generic_first_appt_emergency following presentation for care with the symptoms - of partial and full blindness. - This event begins the investigation that may result in diagnosis of Diabetic Retinopathy and the scheduling of - treatment. - """ - - def __init__(self, module, person_id): - super().__init__(module, person_id=person_id) - - self.TREATMENT_ID = "Dr_Investigation" - self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1}) - self.ACCEPTED_FACILITY_LEVEL = '2' - self.ALERT_OTHER_DISEASES = [] - - def apply(self, person_id, squeeze_factor): - df = self.sim.population.props - # person = df.loc[person_id] - hs = self.sim.modules["HealthSystem"] - - # Ignore this event if the person is no longer alive: - if not df.at[person_id, 'is_alive']: - return hs.get_blank_appt_footprint() - - # Check that this event has been called for someone with the symptom blindness_partial - assert 'blindness_partial' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) - # Check that this event has been called for someone with the symptom blindness_full - assert 'blindness_full' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) - - # If the person is already diagnosed, then take no action: - if not pd.isnull(df.at[person_id, "dr_date_diagnosis"]): - return hs.get_blank_appt_footprint() - - df.at[person_id, 'dr_blindness_investigated'] = True - - is_cons_available = self.get_consumables( - self.module.cons_item_codes['eye_injection'] - ) - - dx_result = hs.dx_manager.run_dx_test( - dx_tests_to_run='dilated_eye_exam_dr_blindness', - hsi_event=self - ) - # TODO Those in mild and moderate DR must not go to start treatment since these can be managed with good blood - # sugar control to slow the progression. - if dx_result and is_cons_available: - # record date of diagnosis - df.at[person_id, 'dr_date_diagnosis'] = self.sim.date - # If consumables are available, add equipment used and run dx_test - self.add_equipment({'Ophthalmoscope'}) - - hs.schedule_hsi_event( - hsi_event=HSI_Dr_StartTreatment( - module=self.module, - person_id=person_id - ), - priority=0, - topen=self.sim.date, - tclose=None - ) + # get the clinical states + dr_stage = individual_properties['dr_status'] + + # No interventions if well + if dr_stage == 'none': + return + + # Interventions for MAM + elif dr_stage == 'mild' or dr_stage == 'moderate': + # schedule HSI for mild and moderate + schedule_hsi_event( + hsi_event=HSI_Dr_DietManagement(module=self, person_id=person_id), + priority=0, topen=self.sim.date) + + elif dr_stage == 'severe' or dr_stage == 'proliferative': + # Interventions for severe and proliferative + schedule_hsi_event( + hsi_event=HSI_zzzzzzzzzzzzz(module=self, person_id=person_id), + priority=0, topen=self.sim.date) + + # if "blindness_full" in symptoms or "blindness_partial" in symptoms: + # event = HSI_Dr_TestingFollowingSymptoms( + # module=self, + # person_id=person_id, + # ) + # schedule_hsi_event(event, priority=1, topen=self.sim.date) + + +# class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): +# """ +# This event is scheduled by do_at_generic_first_appt_emergency following presentation for care with the symptoms +# of partial and full blindness. +# This event begins the investigation that may result in diagnosis of Diabetic Retinopathy and the scheduling of +# treatment. +# """ +# +# def __init__(self, module, person_id): +# super().__init__(module, person_id=person_id) +# +# self.TREATMENT_ID = "Dr_Investigation" +# self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1}) +# self.ACCEPTED_FACILITY_LEVEL = '2' +# self.ALERT_OTHER_DISEASES = [] +# +# def apply(self, person_id, squeeze_factor): +# df = self.sim.population.props +# # person = df.loc[person_id] +# hs = self.sim.modules["HealthSystem"] +# +# # Ignore this event if the person is no longer alive: +# if not df.at[person_id, 'is_alive']: +# return hs.get_blank_appt_footprint() +# +# # Check that this event has been called for someone with the symptom blindness_partial +# assert 'blindness_partial' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) +# # Check that this event has been called for someone with the symptom blindness_full +# assert 'blindness_full' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) +# +# # If the person is already diagnosed, then take no action: +# if not pd.isnull(df.at[person_id, "dr_date_diagnosis"]): +# return hs.get_blank_appt_footprint() +# +# df.at[person_id, 'dr_blindness_investigated'] = True +# +# is_cons_available = self.get_consumables( +# self.module.cons_item_codes['eye_injection'] +# ) +# +# dx_result = hs.dx_manager.run_dx_test( +# dx_tests_to_run='dilated_eye_exam_dr_blindness', +# hsi_event=self +# ) +# # TODO Those in mild and moderate DR must not go to start treatment since these can be managed with good blood +# # sugar control to slow the progression. +# if dx_result and is_cons_available: +# # record date of diagnosis +# df.at[person_id, 'dr_date_diagnosis'] = self.sim.date +# # If consumables are available, add equipment used and run dx_test +# self.add_equipment({'Ophthalmoscope'}) +# +# hs.schedule_hsi_event( +# hsi_event=HSI_Dr_StartTreatment( +# module=self.module, +# person_id=person_id +# ), +# priority=0, +# topen=self.sim.date, +# tclose=None +# ) class HSI_Dr_DietManagement(HSI_Event, IndividualScopeEventMixin): @@ -556,6 +568,7 @@ def apply(self, person_id, squeeze_factor): data=f'This is HSI_Dr_StartTreatment: initiating treatment for person {person_id}') df = self.sim.population.props person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint @@ -568,30 +581,45 @@ def apply(self, person_id, squeeze_factor): randomly_sampled = self.module.rng.rand() treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] - #TODO Add consumables in codition below + df.at[person_id, 'dr_blindness_investigated'] = True - # is_cons_available = self.get_consumables( - # self.module.cons_item_codes['eye_injection'] - # ) + is_cons_available = self.get_consumables( + self.module.cons_item_codes['laser_photocoagulation'] + ) - if treatment_slows_progression_to_proliferative: - df.at[person_id, 'dr_on_treatment'] = True - df.at[person_id, 'dr_date_treatment'] = self.sim.date + dx_result = hs.dx_manager.run_dx_test( + dx_tests_to_run='dilated_eye_exam_dr_blindness', + hsi_event=self + ) - # Reduce probability of progression to "proliferative" DR - progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( - 1 - self.module.parameters['p_medication']) + if dx_result and is_cons_available: + # record date of diagnosis + df.at[person_id, 'dr_date_diagnosis'] = self.sim.date + # If consumables are available, add equipment used and run dx_test + self.add_equipment({'Ophthalmoscope'}) - # Determine if person will still progress - if self.module.rng.rand() < progression_chance: - df.at[person_id, 'dr_status'] = 'proliferative' - else: - df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication + if person.dr_status = 'severe': + #determine_effectiveness + if prob_success > self.rng.random_sample(): + + if treatment_slows_progression_to_proliferative: + df.at[person_id, 'dr_on_treatment'] = True + df.at[person_id, 'dr_date_treatment'] = self.sim.date - else: - # If medication is not effective, progression happens as usual - df.at[person_id, 'dr_on_treatment'] = True - df.at[person_id, 'dr_status'] = 'proliferative' + # Reduce probability of progression to "proliferative" DR + progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( + 1 - self.module.parameters['p_medication']) + + # Determine if person will still progress + if self.module.rng.rand() < progression_chance: + df.at[person_id, 'dr_status'] = 'proliferative' + else: + df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication + + else: + # If medication is not effective, progression happens as usual + df.at[person_id, 'dr_on_treatment'] = True + df.at[person_id, 'dr_status'] = 'proliferative' class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): From ad861fe7492c6fcfaf586a60242e51cbc9ca41a7 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 7 Apr 2025 17:20:29 +0200 Subject: [PATCH 18/85] Consumables and severe stage regression, zero prev test logic --- ...rceFile_Consumables_Items_and_Packages.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 117 ++++++++++-------- tests/test_diabetic_retinopathy.py | 3 +- 3 files changed, 68 insertions(+), 56 deletions(-) diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index ee72f95b7b..fc404c9149 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:db947ae71c8c2914191654fcb1cbdaec24f3d0953a29ac8e5215e3cb8a3ad3d9 -size 246682 +oid sha256:7c0c788b32e2c67fb791069ccee50f23e357a011c833bc10a5c1f4cd8c7cdbea +size 246722 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 32724155ac..d375b012c7 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,5 +1,5 @@ from pathlib import Path -from typing import List +from typing import List, Union import numpy as np import pandas as pd @@ -69,6 +69,9 @@ class DiabeticRetinopathy(Module): "rp_dr_urban": Parameter( Types.REAL, "relative prevalence at baseline of diabetic retinopathy if urban" ), + 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( + Types.REAL, + 'Probability of severe diabetic retinopathy regressing to moderate.'), } PROPERTIES = { @@ -142,6 +145,7 @@ def read_parameters(self, data_folder: str | Path) -> None: # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] # self.parameters['init_prob_proliferative_dr'] = 0.09 self.parameters['p_medication'] = 0.8 + self.parameters['effectiveness_of_laser_photocoagulation_in_severe_regression'] = 0.21 self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] = 0.1 self.parameters['prob_reg_eye_exam'] = 0.05 @@ -180,9 +184,7 @@ def initialise_population(self, population: Population) -> None: # write to property: df.loc[df.is_alive & ~df.nc_diabetes, 'dr_status'] = 'none' - # df.loc[list(no_dr_idx), 'dr_status'] = 'none' - # df.loc[list(mild_dr_idx), "dr_status"] = "mild" - # df.loc[list(proliferative_dr_idx), "dr_status"] = "proliferative" + df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT @@ -333,13 +335,30 @@ def look_up_consumable_item_codes(self): self.cons_item_codes = dict() self.cons_item_codes['laser_photocoagulation'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, - get_item_codes('Disposables gloves, powder free, 100 pieces per box'): 2, + get_item_codes('Gloves, exam, latex, disposable, pair'): 4, + get_item_codes('Contact lens'): 7 } self.cons_item_codes['eye_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, - get_item_codes('Aflibercept, 2mg'): 3, + get_item_codes('Aflibercept, 2mg'): 3 } + def do_recovery(self, idx: Union[list, pd.Index]): + """Represent the recovery from diabetic retinopathy for the person_id given in `idx`. + Recovery causes the person to move from severe to moderate""" + df = self.sim.population.props + + # Getting those with severe and updating to moderate + mask = df.loc[idx, 'dr_status'] == 'severe' + df.loc[idx[mask], 'dr_status'] = 'moderate' + df.loc[idx[mask], 'dr_date_treatment'] = self.sim.date + df.loc[idx[mask], 'dr_on_treatment'] = True + + def do_treatment(self, person_id, prob_success): + """For treatment of individuals with Severe DR status. If treatment is successful, regress to moderate.""" + if prob_success > self.rng.random_sample(): + self.do_recovery([person_id]) + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis @@ -400,21 +419,21 @@ def apply(self, population: Population) -> None: # tclose=None # ) - if len(will_progress_idx): - self.sim.modules['SymptomManager'].change_symptom( - person_id=will_progress_idx, - symptom_string='blindness_partial', - add_or_remove='+', - disease_module=self.module, - ) - - if len(mild_to_moderate_idx): - self.sim.modules['SymptomManager'].change_symptom( - person_id=mild_to_moderate_idx, - symptom_string='blindness_full', - add_or_remove='+', - disease_module=self.module, - ) + # if len(will_progress_idx): + # self.sim.modules['SymptomManager'].change_symptom( + # person_id=will_progress_idx, + # symptom_string='blindness_partial', + # add_or_remove='+', + # disease_module=self.module, + # ) + # + # if len(mild_to_moderate_idx): + # self.sim.modules['SymptomManager'].change_symptom( + # person_id=mild_to_moderate_idx, + # symptom_string='blindness_full', + # add_or_remove='+', + # disease_module=self.module, + # ) def do_at_generic_first_appt( self, @@ -441,15 +460,9 @@ def do_at_generic_first_appt( elif dr_stage == 'severe' or dr_stage == 'proliferative': # Interventions for severe and proliferative schedule_hsi_event( - hsi_event=HSI_zzzzzzzzzzzzz(module=self, person_id=person_id), + hsi_event=HSI_Dr_StartTreatment(module=self, person_id=person_id), priority=0, topen=self.sim.date) - # if "blindness_full" in symptoms or "blindness_partial" in symptoms: - # event = HSI_Dr_TestingFollowingSymptoms( - # module=self, - # person_id=person_id, - # ) - # schedule_hsi_event(event, priority=1, topen=self.sim.date) # class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): @@ -496,8 +509,7 @@ def do_at_generic_first_appt( # dx_tests_to_run='dilated_eye_exam_dr_blindness', # hsi_event=self # ) -# # TODO Those in mild and moderate DR must not go to start treatment since these can be managed with good blood -# # sugar control to slow the progression. +# # if dx_result and is_cons_available: # # record date of diagnosis # df.at[person_id, 'dr_date_diagnosis'] = self.sim.date @@ -588,7 +600,7 @@ def apply(self, person_id, squeeze_factor): ) dx_result = hs.dx_manager.run_dx_test( - dx_tests_to_run='dilated_eye_exam_dr_blindness', + dx_tests_to_run='dilated_eye_exam_dr', hsi_event=self ) @@ -598,28 +610,29 @@ def apply(self, person_id, squeeze_factor): # If consumables are available, add equipment used and run dx_test self.add_equipment({'Ophthalmoscope'}) - if person.dr_status = 'severe': + if person.dr_status == 'severe': #determine_effectiveness - if prob_success > self.rng.random_sample(): - - if treatment_slows_progression_to_proliferative: - df.at[person_id, 'dr_on_treatment'] = True - df.at[person_id, 'dr_date_treatment'] = self.sim.date - - # Reduce probability of progression to "proliferative" DR - progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( - 1 - self.module.parameters['p_medication']) - - # Determine if person will still progress - if self.module.rng.rand() < progression_chance: - df.at[person_id, 'dr_status'] = 'proliferative' - else: - df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication - - else: - # If medication is not effective, progression happens as usual - df.at[person_id, 'dr_on_treatment'] = True - df.at[person_id, 'dr_status'] = 'proliferative' + self.module.do_treatment(person_id, prob_success=self.module.parameters[ + 'effectiveness_of_laser_photocoagulation_in_severe_regression']) + + # if treatment_slows_progression_to_proliferative: + # df.at[person_id, 'dr_on_treatment'] = True + # df.at[person_id, 'dr_date_treatment'] = self.sim.date + # + # # Reduce probability of progression to "proliferative" DR + # progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( + # 1 - self.module.parameters['p_medication']) + # + # # Determine if person will still progress + # if self.module.rng.rand() < progression_chance: + # df.at[person_id, 'dr_status'] = 'proliferative' + # else: + # df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication + # + # else: + # # If medication is not effective, progression happens as usual + # df.at[person_id, 'dr_on_treatment'] = True + # df.at[person_id, 'dr_status'] = 'proliferative' class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 6cb85807ff..9de26f7256 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -90,7 +90,6 @@ def check_dtypes(sim): def zero_out_init_prev(sim): # Set initial prevalence to zero: - # Change to [0.0] * 2 (or num of stages) after getting all stages from Shaffi and changing TYPE to LIST sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.0] * 4 # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 return sim @@ -150,7 +149,7 @@ def test_initial_config_of_pop_zero_prevalence(seed): check_dtypes(sim) check_configuration_of_population(sim) df = sim.population.props - assert (df.loc[df.is_alive].dr_status == 'none').all() + assert (df.loc[df.is_alive & ~df.nc_diabetes].dr_status == 'none').all() def test_initial_config_of_pop_high_prevalence(seed): From f307e0be34bb991b64fdfa2b4c755481982328b1 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 8 Apr 2025 16:01:45 +0200 Subject: [PATCH 19/85] tidy up --- src/tlo/methods/diabetic_retinopathy.py | 103 ++---------------------- tests/test_diabetic_retinopathy.py | 38 ++++++++- 2 files changed, 44 insertions(+), 97 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index d375b012c7..172945d88a 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -77,20 +77,9 @@ class DiabeticRetinopathy(Module): PROPERTIES = { "dr_status": Property( Types.CATEGORICAL, - categories=[ - "none", - "mild", # was early - "moderate", - "severe", - "proliferative", # was late - ], - description="dr status", + "DR status", + categories=["none", "mild", "moderate", "severe", "proliferative"], ), - # "dr_status": Property( - # Types.CATEGORICAL, - # "DR status", - # categories=["none", "mild", "moderate", "severe", "proliferative"], - # ), "dr_on_treatment": Property( Types.BOOL, "Whether this person is on diabetic retinopathy treatment", ), @@ -207,8 +196,8 @@ def initialise_population(self, population: Population) -> None: Predictor('li_urban').when(True, self.parameters['rp_dr_urban']), ) - any_dr = \ - lm_init_dr_status_any_dr.predict(df.loc[df.is_alive & df.nc_diabetes], self.rng) + # any_dr = \ + # lm_init_dr_status_any_dr.predict(df.loc[df.is_alive & df.nc_diabetes], self.rng) # Get boolean Series of who has DR has_dr = lm_init_dr_status_any_dr.predict(df.loc[df.is_alive & df.nc_diabetes], self.rng) @@ -419,22 +408,6 @@ def apply(self, population: Population) -> None: # tclose=None # ) - # if len(will_progress_idx): - # self.sim.modules['SymptomManager'].change_symptom( - # person_id=will_progress_idx, - # symptom_string='blindness_partial', - # add_or_remove='+', - # disease_module=self.module, - # ) - # - # if len(mild_to_moderate_idx): - # self.sim.modules['SymptomManager'].change_symptom( - # person_id=mild_to_moderate_idx, - # symptom_string='blindness_full', - # add_or_remove='+', - # disease_module=self.module, - # ) - def do_at_generic_first_appt( self, person_id: int, @@ -464,69 +437,6 @@ def do_at_generic_first_appt( priority=0, topen=self.sim.date) - -# class HSI_Dr_TestingFollowingSymptoms(HSI_Event, IndividualScopeEventMixin): -# """ -# This event is scheduled by do_at_generic_first_appt_emergency following presentation for care with the symptoms -# of partial and full blindness. -# This event begins the investigation that may result in diagnosis of Diabetic Retinopathy and the scheduling of -# treatment. -# """ -# -# def __init__(self, module, person_id): -# super().__init__(module, person_id=person_id) -# -# self.TREATMENT_ID = "Dr_Investigation" -# self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1}) -# self.ACCEPTED_FACILITY_LEVEL = '2' -# self.ALERT_OTHER_DISEASES = [] -# -# def apply(self, person_id, squeeze_factor): -# df = self.sim.population.props -# # person = df.loc[person_id] -# hs = self.sim.modules["HealthSystem"] -# -# # Ignore this event if the person is no longer alive: -# if not df.at[person_id, 'is_alive']: -# return hs.get_blank_appt_footprint() -# -# # Check that this event has been called for someone with the symptom blindness_partial -# assert 'blindness_partial' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) -# # Check that this event has been called for someone with the symptom blindness_full -# assert 'blindness_full' in self.sim.modules['SymptomManager'].has_what(person_id=person_id) -# -# # If the person is already diagnosed, then take no action: -# if not pd.isnull(df.at[person_id, "dr_date_diagnosis"]): -# return hs.get_blank_appt_footprint() -# -# df.at[person_id, 'dr_blindness_investigated'] = True -# -# is_cons_available = self.get_consumables( -# self.module.cons_item_codes['eye_injection'] -# ) -# -# dx_result = hs.dx_manager.run_dx_test( -# dx_tests_to_run='dilated_eye_exam_dr_blindness', -# hsi_event=self -# ) -# -# if dx_result and is_cons_available: -# # record date of diagnosis -# df.at[person_id, 'dr_date_diagnosis'] = self.sim.date -# # If consumables are available, add equipment used and run dx_test -# self.add_equipment({'Ophthalmoscope'}) -# -# hs.schedule_hsi_event( -# hsi_event=HSI_Dr_StartTreatment( -# module=self.module, -# person_id=person_id -# ), -# priority=0, -# topen=self.sim.date, -# tclose=None -# ) - - class HSI_Dr_DietManagement(HSI_Event, IndividualScopeEventMixin): """This is a Health System Interaction Event in which a person receives a session of diet management in the diabetes clinic. It is one of a course of 5 sessions (at months 0, 6, 12, 18, 24). If one of these HSI does not happen @@ -562,7 +472,8 @@ def apply(self, person_id, squeeze_factor): class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ - This event initiates the treatment of DR. + This event initiates the treatment of DR for severe and proliferative stages. + This event is scheduled by HSI_GenericFirstAppt. """ def __init__(self, module, person_id): @@ -591,7 +502,7 @@ def apply(self, person_id, squeeze_factor): return self.sim.modules["HealthSystem"].get_blank_appt_footprint() randomly_sampled = self.module.rng.rand() - treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] + # treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] df.at[person_id, 'dr_blindness_investigated'] = True diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 9de26f7256..9a119e8ff7 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -81,6 +81,26 @@ def get_simulation_healthsystemdisabled(seed): ) return sim +def get_simulation_nohsi(seed): + """Make the simulation with: + * the healthsystem enabled but with no service availabilty (so no HSI run) + """ + sim = Simulation(start_date=start_date, seed=seed) + + # Register the appropriate modules + sim.register(demography.Demography(resourcefilepath=resourcefilepath), + simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), + enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), + healthsystem.HealthSystem(resourcefilepath=resourcefilepath, service_availability=[]), + symptommanager.SymptomManager(resourcefilepath=resourcefilepath), + healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath), + healthburden.HealthBurden(resourcefilepath=resourcefilepath), + cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + diabetic_retinopathy.DiabeticRetinopathy(), + depression.Depression(resourcefilepath=resourcefilepath) + ) + return sim + def check_dtypes(sim): df = sim.population.props @@ -100,6 +120,16 @@ def make_high_init_prev(sim): # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 return sim +def incr_rate_of_onset_mild(sim): + # Rate of cancer onset per # months: + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.05 + return sim + +def zero_rate_of_onset_mild(sim): + # Rate of cancer onset per # months: + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.00 + return sim + def incr_rates_of_progression(sim): # Rates of DR progression: sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] *= 5 @@ -140,9 +170,15 @@ def test_basic_run(seed): sim.simulate(end_date=Date(2010, 5, 1)) check_dtypes(sim) +def test_initial_config_of_pop_usual_prevalence(seed): + """Tests the way the population is configured: with usual initial prevalence values""" + sim = get_simulation_healthsystemdisabled(seed=seed) + sim.make_initial_population(n=popsize) + check_dtypes(sim) + check_configuration_of_population(sim) def test_initial_config_of_pop_zero_prevalence(seed): - """Tests of the way the population is configured: with zero initial prevalence values """ + """Tests the way the population is configured: with zero initial prevalence values """ sim = get_simulation_healthsystemdisabled(seed=seed) sim = zero_out_init_prev(sim) sim.make_initial_population(n=popsize) From ac614b9b5731957936809d1ec41f5304723c3f7e Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 6 May 2025 09:39:38 +0200 Subject: [PATCH 20/85] declare has_dmo, and has_csdmo_ncsdmo --- src/tlo/methods/diabetic_retinopathy.py | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 172945d88a..9e82c51751 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -98,15 +98,21 @@ class DiabeticRetinopathy(Module): ), "dr_date_diagnosis": Property( Types.DATE, - "the date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" + "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" ), "dr_blindness_investigated": Property( Types.BOOL, - "whether blindness has been investigated, and diabetic retinopathy missed" + "Whether blindness has been investigated, and diabetic retinopathy missed" ), "dr_ever_diet_mgmt": Property(Types.BOOL, - "whether this person has ever had a diabetic retinopathy diet management" + "Whether this person has ever had a diabetic retinopathy diet management" "session in the diabetic clinic"), + "has_dmo": Property(Types.BOOL, + "Whether this person has any form of diabetic macular oedema"), + "has_csdmo_or_ncsdmo": Property(Types.BOOL, + "Whether this person has clinically significant diabetic macular oedema if " + "true," + "or person has non clinically significant diabetic macular oedema"), } @@ -180,6 +186,8 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False + df.loc[list(alive_diabetes_idx), "has_dmo"] = False + df.loc[list(alive_diabetes_idx), "has_csdmo_or_ncsdmo"] = False # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -284,6 +292,8 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False self.sim.population.props.at[child_id, 'dr_ever_diet_mgmt'] = False + self.sim.population.props.at[child_id, 'has_dmo'] = False + self.sim.population.props.at[child_id, 'has_csdmo_or_ncsdmo'] = False def on_simulation_end(self) -> None: pass From b06af990cc22aba96fbda4d1f6aa259274d3e0b7 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 6 May 2025 09:47:25 +0200 Subject: [PATCH 21/85] remove unused variable and import --- src/tlo/methods/diabetic_retinopathy.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 9e82c51751..4e998b2562 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,5 +1,5 @@ from pathlib import Path -from typing import List, Union +from typing import Union import numpy as np import pandas as pd @@ -511,7 +511,7 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() - randomly_sampled = self.module.rng.rand() + # randomly_sampled = self.module.rng.rand() # treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] df.at[person_id, 'dr_blindness_investigated'] = True From 76b633c5ff460d3d4f6e2551be15f035c175e357 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 6 May 2025 10:22:51 +0200 Subject: [PATCH 22/85] remove Dr_Investigation --- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 4 ++-- .../ClinicallyVulnerable.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 4 ++-- .../VerticalProgrammes.csv | 4 ++-- 10 files changed, 20 insertions(+), 20 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index d6dec096ca..35f7c80663 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:6fcf65f3c87f7f8e3fdd8b6cc44c01ffa9071a11dd5e6d2d09d2d74f98c4418b -size 3692 +oid sha256:1186c9c0588309faea730c4cac3b145ad7598f30f189ee6e81aec98d846796f1 +size 3660 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index b69289e834..747f3b082f 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:9702fc9746ffaa1215068a909c4feb7b0413c81783a885ca2dc745e8949af8b8 -size 3352 +oid sha256:bfe2657a33e13f9833ad76bd99352ea686f474ca15e8a241adcf9246c0b6ea67 +size 3320 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index a0c9cecbab..686871c234 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:a37e328872a5abcd130d21545a5323a3e74a69352ad099350b700f886e4b56ee -size 3694 +oid sha256:cb5f2f5eb670cfb23b3b314accfeafa1cc4eb987c38f8fd8735b4846da5da717 +size 3662 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 803c8f02c0..677ec2032f 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:a7c5300bfc989596f8b4b09b81b66367ec00e06cc138e01ab25178af8dc615ab -size 3693 +oid sha256:466dae64860a8a3b036a039bc64f3a9b667afab7221a64d8c84282a8ff16b85e +size 3661 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 20b3c71800..9222caaf81 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:a0c8192848d16e383928bb8153dffbdbf4a4d1a8e512626dc5b9758214bbbd47 -size 3692 +oid sha256:dce641dfbc3e7b6fd9a65c52a94080b5b81ddf4c83f1a7d62d8ab8e739bf6365 +size 3660 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index 616ab663a1..bc5b51859d 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:613859532affc86192a53efaf681e55a60a866435522da9673ce991c1e1d828f -size 3692 +oid sha256:c50703e360d1a788af608a24781f9fe8b9e50c108a49381b4e1030e9349c58ee +size 3660 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 57f0e08304..dc21fa8ef6 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:2481aeb6d5a954afe810bb7985eadccc88c10a14392fa13d96e101abc2faa7d4 -size 3677 +oid sha256:5a4537bb37503a0df87342ed061616c1956c82eacad0c60bcda8cecf6e276088 +size 3645 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 2f064550b6..cd14e12f47 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:97e88ec0bdfa7fbb4793dcaa173d93fd24057a9cc6607299e4b07ba4885cc58d -size 3694 +oid sha256:560bb29b106f518a88c01ee14b39c604347ff818fafe21c0066d0e51a29f42cf +size 3662 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 48b3d0fcfb..ae0068bf09 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:1115b157ed0b031467ebca6ea3a205f025cfff04636feb29f9d34c0f2f1389d7 -size 3694 +oid sha256:cf6a3ad3c0c72186498b03d53dda4382d3840fa1d117d0c7d6056ae8d4458576 +size 3662 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 0dae174ec6..fb59435e29 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:e895d941bac75771fa64b8c518c5646ff3072b0446890672fbe937f4a4175882 -size 3692 +oid sha256:0c6bdebede66b7dd299f3bb906b268e14eebe60e742f72adb42b11b340023e15 +size 3660 From d0fc275d22f517848d387569e97f7c2faaace110 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 26 May 2025 09:04:27 +0200 Subject: [PATCH 23/85] prob matrix for dmo_status --- src/tlo/methods/diabetic_retinopathy.py | 46 +++++++++++++++++-------- 1 file changed, 32 insertions(+), 14 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 4e998b2562..37deb7934c 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -38,14 +38,17 @@ class DiabeticRetinopathy(Module): "rate_moderate_to_severe": Parameter(Types.REAL, "Probability of people who get diagnosed with severe diabetic retinopathy"), "rate_severe_to_proliferative": Parameter(Types.REAL, - "Probability of people who get diagnosed with proliferative diabetic retinopathy"), + "Probability of people who get diagnosed with proliferative " + "diabetic retinopathy"), 'prob_fast_dr': Parameter(Types.REAL, "Probability of people who get diagnosed from none phase to proliferative diabetic " "retinopathy stage"), - #TODO Change init_prob_any_dr to LIST + # TODO Change init_prob_any_dr to LIST "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), - # "init_prob_proliferative_dr": Parameter(Types.REAL, - # "Initial probability of people with diabetic retinopathy in the proliferative stage"), + "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having Diabetic " + "Macular Oedema (DMO)"), + # "init_prob_proliferative_dr": Parameter(Types.REAL, "Initial probability of people with diabetic + # retinopathy in the proliferative stage"), "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), "init_prob_ever_diet_mgmt_if_diagnosed": Parameter( Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " @@ -72,6 +75,8 @@ class DiabeticRetinopathy(Module): 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( Types.REAL, 'Probability of severe diabetic retinopathy regressing to moderate.'), + "probs_for_dmo_non": Parameter( + Types.LIST, "probability of no DMO moving between states: mild, moderate, severe, proliferative "), } PROPERTIES = { @@ -80,6 +85,11 @@ class DiabeticRetinopathy(Module): "DR status", categories=["none", "mild", "moderate", "severe", "proliferative"], ), + "dmo_status": Property( + Types.CATEGORICAL, + "DMO status. Only occurs to people with any type of DIabetic Retinopathy.", + categories=["none", "clinically_significant", "non_clnincally_significant"], + ), "dr_on_treatment": Property( Types.BOOL, "Whether this person is on diabetic retinopathy treatment", ), @@ -107,12 +117,6 @@ class DiabeticRetinopathy(Module): "dr_ever_diet_mgmt": Property(Types.BOOL, "Whether this person has ever had a diabetic retinopathy diet management" "session in the diabetic clinic"), - "has_dmo": Property(Types.BOOL, - "Whether this person has any form of diabetic macular oedema"), - "has_csdmo_or_ncsdmo": Property(Types.BOOL, - "Whether this person has clinically significant diabetic macular oedema if " - "true," - "or person has non clinically significant diabetic macular oedema"), } @@ -137,6 +141,10 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['prob_fast_dr'] = 0.5 self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.2] + self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] + + self.parameters['probs_for_dmo_non'] = [0.9, 0.1, 0.0, 0.0] + # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] # self.parameters['init_prob_proliferative_dr'] = 0.09 self.parameters['p_medication'] = 0.8 @@ -179,6 +187,7 @@ def initialise_population(self, population: Population) -> None: # write to property: df.loc[df.is_alive & ~df.nc_diabetes, 'dr_status'] = 'none' + df.loc[df.is_alive & ~df.nc_diabetes, 'dmo_status'] = 'none' df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False @@ -186,8 +195,6 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False - df.loc[list(alive_diabetes_idx), "has_dmo"] = False - df.loc[list(alive_diabetes_idx), "has_csdmo_or_ncsdmo"] = False # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -286,14 +293,13 @@ def on_birth(self, mother_id: int, child_id: int) -> None: :param child_id: the new child """ self.sim.population.props.at[child_id, 'dr_status'] = 'none' + self.sim.population.props.at[child_id, 'dmo_status'] = 'none' self.sim.population.props.at[child_id, 'dr_on_treatment'] = False self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False self.sim.population.props.at[child_id, 'dr_ever_diet_mgmt'] = False - self.sim.population.props.at[child_id, 'has_dmo'] = False - self.sim.population.props.at[child_id, 'has_csdmo_or_ncsdmo'] = False def on_simulation_end(self) -> None: pass @@ -396,6 +402,18 @@ def apply(self, population: Population) -> None: severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' + # Setting DMO status + # Get people with any DR (i.e., not none) in index, since DMO is only for people with DR + + prob_matrix = pd.DataFrame( + columns=df.dmo_status, + index=df.loc[df.dr_status != 'none', 'dr_status'] + ) + + prob_matrix['none'] = self.parameters['probs_for_dmo_non'] + prob_matrix['clinically_significant'] = [0.2, 0.2, 0.6, 0.0] + prob_matrix['non_clinically_significant'] = [0.0, 0.2, 0.6, 0.2] + # fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # # fast_dr_idx = fast_dr[fast_dr].index # fast_dr_idx = df.index[np.where(fast_dr)[0]] From bcc95f2cdc45c0dd794ce165a011071674f68343 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 26 May 2025 09:06:00 +0200 Subject: [PATCH 24/85] remove List todo --- src/tlo/methods/diabetic_retinopathy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 37deb7934c..cf3eef3723 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -43,7 +43,7 @@ class DiabeticRetinopathy(Module): 'prob_fast_dr': Parameter(Types.REAL, "Probability of people who get diagnosed from none phase to proliferative diabetic " "retinopathy stage"), - # TODO Change init_prob_any_dr to LIST + "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having Diabetic " "Macular Oedema (DMO)"), From 63eea541d2afa1e2b5bbb106e942a81b9def7a03 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 27 May 2025 14:44:52 +0200 Subject: [PATCH 25/85] Mapping dmo_status to dr_status using probs --- .../diabetic_retinopathy_analyses.py | 30 ++++--- src/tlo/methods/diabetic_retinopathy.py | 79 +++++++++++++++---- 2 files changed, 81 insertions(+), 28 deletions(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 5f9ae773b4..040749f1b1 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -185,15 +185,21 @@ def plot_dr_incidence(incidence_by_stage, title): plt.tight_layout() plt.show() -logfile_with_healthsystem = run_sim(service_availability=['*']) -results_with_healthsystem = get_summary_stats(logfile_with_healthsystem) - -logfile_no_healthsystem = run_sim(service_availability=[]) -results_no_healthsystem = get_summary_stats(logfile_no_healthsystem) - -plot_dr_progression(results_with_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (With Health System)") -plot_dr_progression(results_no_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (No Health System)") -plot_treatment_cascade(results_with_healthsystem['counts_by_cascade'], "Treatment Status Over Time (With Health System)") -plot_treatment_cascade(results_no_healthsystem['counts_by_cascade'], "Treatment Status Over Time (No Health System)") -# plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") -# plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") + +try: + logfile_with_healthsystem = run_sim(service_availability=['*']) + results_with_healthsystem = get_summary_stats(logfile_with_healthsystem) + + logfile_no_healthsystem = run_sim(service_availability=[]) + results_no_healthsystem = get_summary_stats(logfile_no_healthsystem) + + plot_dr_progression(results_with_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (With Health System)") + plot_dr_progression(results_no_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (No Health System)") + plot_treatment_cascade(results_with_healthsystem['counts_by_cascade'], "Treatment Status Over Time (With Health System)") + plot_treatment_cascade(results_no_healthsystem['counts_by_cascade'], "Treatment Status Over Time (No Health System)") + # plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") + # plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") + +except Exception as e: + print(f"Error running simulation: {str(e)}") + raise diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index cf3eef3723..2bb62da510 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -12,6 +12,7 @@ from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.methods.symptommanager import Symptom from tlo.population import IndividualProperties +from tlo.util import transition_states logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -75,8 +76,14 @@ class DiabeticRetinopathy(Module): 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( Types.REAL, 'Probability of severe diabetic retinopathy regressing to moderate.'), - "probs_for_dmo_non": Parameter( - Types.LIST, "probability of no DMO moving between states: mild, moderate, severe, proliferative "), + "probs_for_dmo_when_dr_status_mild": Parameter( + Types.LIST, "probability of having a DMO state when an individual has mild Diabetic Retinopathy "), + "probs_for_dmo_when_dr_status_moderate": Parameter( + Types.LIST, "probability of having a DMO state when an individual has mild Diabetic Retinopathy "), + "probs_for_dmo_when_dr_status_severe": Parameter( + Types.LIST, "probability of having a DMO state when an individual has severe Diabetic Retinopathy "), + "probs_for_dmo_when_dr_status_proliferative": Parameter( + Types.LIST, "probability of having a DMO state when an individual has proliferative Diabetic Retinopathy "), } PROPERTIES = { @@ -87,8 +94,8 @@ class DiabeticRetinopathy(Module): ), "dmo_status": Property( Types.CATEGORICAL, - "DMO status. Only occurs to people with any type of DIabetic Retinopathy.", - categories=["none", "clinically_significant", "non_clnincally_significant"], + "DMO status. Only occurs to people with any type of Diabetic Retinopathy.", + categories=["none", "clinically_significant", "non_clinically_significant"], ), "dr_on_treatment": Property( Types.BOOL, "Whether this person is on diabetic retinopathy treatment", @@ -143,7 +150,10 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.2] self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] - self.parameters['probs_for_dmo_non'] = [0.9, 0.1, 0.0, 0.0] + self.parameters['probs_for_dmo_when_dr_status_mild'] = [0.7, 0.1, 0.2] + self.parameters['probs_for_dmo_when_dr_status_moderate'] = [0.5, 0.3, 0.2] + self.parameters['probs_for_dmo_when_dr_status_severe'] = [0.3, 0.5, 0.2] + self.parameters['probs_for_dmo_when_dr_status_proliferative'] = [0.1, 0.7, 0.2] # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] # self.parameters['init_prob_proliferative_dr'] = 0.09 @@ -364,6 +374,52 @@ def do_treatment(self, person_id, prob_success): if prob_success > self.rng.random_sample(): self.do_recovery([person_id]) + def update_dmo_status(self): + """Update DMO status for people with diabetic retinopathy. + Ensures dmo_status is none when dr_status is none/nan.""" + df = self.sim.population.props + + # First reset dmo_status to 'none' for anyone without DR + no_dr_mask = (df.dr_status == 'none') | df.dr_status.isna() + df.loc[no_dr_mask, 'dmo_status'] = 'none' + + # Now only process people with valid DR status + valid_dr_statuses = ['mild', 'moderate', 'severe', 'proliferative'] + dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses)].index + + if not dr_idx.empty: + for person in dr_idx: + dr_stage = df.at[person, 'dr_status'] + + if dr_stage == 'mild': + probs = self.parameters['probs_for_dmo_when_dr_status_mild'] + elif dr_stage == 'moderate': + probs = self.parameters['probs_for_dmo_when_dr_status_moderate'] + elif dr_stage == 'severe': + probs = self.parameters['probs_for_dmo_when_dr_status_severe'] + elif dr_stage == 'proliferative': + probs = self.parameters['probs_for_dmo_when_dr_status_proliferative'] + + df.at[person, 'dmo_status'] = self.rng.choice( + ['none', 'clinically_significant', 'non_clinically_significant'], + p=probs + ) + + # verification for some people. To be deleted + sample_people = dr_idx[:5] if len(dr_idx) >= 5 else dr_idx + for person in sample_people: + print( + f"Person {person}: dr_status={df.at[person, 'dr_status']}, dmo_status={df.at[person, 'dmo_status']}") + + invalid_cases = df[ + ((df.dr_status == 'none') | df.dr_status.isna()) & + (df.dmo_status.isin(['clinically_significant', 'non_clinically_significant'])) + ] + assert len(invalid_cases) == 0, ( + f"Found {len(invalid_cases)} cases where people with no DR " + f"have DMO status: {invalid_cases[['dr_status', 'dmo_status']].to_dict()}" + ) + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis @@ -402,17 +458,8 @@ def apply(self, population: Population) -> None: severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' - # Setting DMO status - # Get people with any DR (i.e., not none) in index, since DMO is only for people with DR - - prob_matrix = pd.DataFrame( - columns=df.dmo_status, - index=df.loc[df.dr_status != 'none', 'dr_status'] - ) - - prob_matrix['none'] = self.parameters['probs_for_dmo_non'] - prob_matrix['clinically_significant'] = [0.2, 0.2, 0.6, 0.0] - prob_matrix['non_clinically_significant'] = [0.0, 0.2, 0.6, 0.2] + # Update DMO status + self.module.update_dmo_status() # fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # # fast_dr_idx = fast_dr[fast_dr].index From c7ec0e83f16aae7c9566938a2d3db1c69cf7f050 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 28 May 2025 13:30:11 +0200 Subject: [PATCH 26/85] Use HSI_CardioMetabolicDisorders_StartWeightLossAndMedication in first appt --- src/tlo/methods/diabetic_retinopathy.py | 21 +++++++++++---------- 1 file changed, 11 insertions(+), 10 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 2bb62da510..dc6fb700fb 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -7,7 +7,7 @@ from tlo import DateOffset, Module, Parameter, Population, Property, Simulation, Types, logging from tlo.events import IndividualScopeEventMixin, PopulationScopeEventMixin, RegularEvent from tlo.lm import LinearModel, LinearModelType, Predictor -from tlo.methods import Metadata +from tlo.methods import Metadata, cardio_metabolic_disorders from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.methods.symptommanager import Symptom @@ -405,12 +405,6 @@ def update_dmo_status(self): p=probs ) - # verification for some people. To be deleted - sample_people = dr_idx[:5] if len(dr_idx) >= 5 else dr_idx - for person in sample_people: - print( - f"Person {person}: dr_status={df.at[person, 'dr_status']}, dmo_status={df.at[person, 'dmo_status']}") - invalid_cases = df[ ((df.dr_status == 'none') | df.dr_status.isna()) & (df.dmo_status.isin(['clinically_significant', 'non_clinically_significant'])) @@ -501,9 +495,16 @@ def do_at_generic_first_appt( # Interventions for MAM elif dr_stage == 'mild' or dr_stage == 'moderate': # schedule HSI for mild and moderate - schedule_hsi_event( - hsi_event=HSI_Dr_DietManagement(module=self, person_id=person_id), - priority=0, topen=self.sim.date) + self.sim.modules["HealthSystem"].schedule_hsi_event( + hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( + person_id=person_id, + module=self.sim.modules["CardioMetabolicDisorders"], + condition='diabetes', + ), + priority=0, + topen=self.sim.date + ) + elif dr_stage == 'severe' or dr_stage == 'proliferative': # Interventions for severe and proliferative From e5b2fdb4213e2f7ef8d1d95979d6a56373453b09 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 29 May 2025 10:25:46 +0200 Subject: [PATCH 27/85] HSI for DR and DMO. Disconnected. Removed Health Mgmt --- .../CVD.csv | 4 +- .../ClinicallyVulnerable.csv | 4 +- .../Default.csv | 4 +- .../EHP_III.csv | 4 +- .../LCOA_EHP.csv | 4 +- .../Naive.csv | 4 +- .../RMNCH.csv | 4 +- .../Test Mode 1.csv | 4 +- .../Test.csv | 4 +- .../VerticalProgrammes.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 84 +++++++++++-------- 11 files changed, 68 insertions(+), 56 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 35f7c80663..30bc02d7fa 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:1186c9c0588309faea730c4cac3b145ad7598f30f189ee6e81aec98d846796f1 -size 3660 +oid sha256:739a43f358304fbe2293b7324e6911129c95be359aea562e1fed1015604b9c1c +size 3664 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index 747f3b082f..9ab2e7aa76 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:bfe2657a33e13f9833ad76bd99352ea686f474ca15e8a241adcf9246c0b6ea67 -size 3320 +oid sha256:339aa228b4dd1dfc74d90b2bb0b4f561e3eb92c57dc1b6e25d16cf9010c075e6 +size 3324 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 686871c234..af14057a60 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cb5f2f5eb670cfb23b3b314accfeafa1cc4eb987c38f8fd8735b4846da5da717 -size 3662 +oid sha256:fb3778a01a26b84ff18ce01b07a1b6747eb39ee6908aefc99c9c5cf2ecd884c4 +size 3666 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 677ec2032f..7b6addb8b4 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:466dae64860a8a3b036a039bc64f3a9b667afab7221a64d8c84282a8ff16b85e -size 3661 +oid sha256:3b0065aa7ab09db8e282af93f5aa2e032e5c239e0e991c83fa6f2d1c3e5746bd +size 3665 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 9222caaf81..783b97daa1 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:dce641dfbc3e7b6fd9a65c52a94080b5b81ddf4c83f1a7d62d8ab8e739bf6365 -size 3660 +oid sha256:46635a4b86396b7de95a8452d0faa10de150b2de155939ff2e961eec272f4ff7 +size 3664 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index bc5b51859d..7c6189e934 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:c50703e360d1a788af608a24781f9fe8b9e50c108a49381b4e1030e9349c58ee -size 3660 +oid sha256:02032d248b58a8c13801fe6640c3d8d7f77a5bb0bcc10a4ad276f8789e8ba5d6 +size 3664 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index dc21fa8ef6..8b98867375 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:5a4537bb37503a0df87342ed061616c1956c82eacad0c60bcda8cecf6e276088 -size 3645 +oid sha256:7c560eb936981684d6cf14009d9aa904ac867243fe6a4834035f54198d982886 +size 3649 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index cd14e12f47..bca7dfd1ef 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:560bb29b106f518a88c01ee14b39c604347ff818fafe21c0066d0e51a29f42cf -size 3662 +oid sha256:b30457c05c9970dc6799944bb375b1d76ba5d42eec4601605f77928b30d41d1f +size 3666 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index ae0068bf09..37af670f17 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cf6a3ad3c0c72186498b03d53dda4382d3840fa1d117d0c7d6056ae8d4458576 -size 3662 +oid sha256:ca223330aeb1cc05efeee6527ae93a76a72c12493d05c20ccec3ac6211623e05 +size 3666 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index fb59435e29..75bc4b5632 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:0c6bdebede66b7dd299f3bb906b268e14eebe60e742f72adb42b11b340023e15 -size 3660 +oid sha256:199892a625598b20e18442c252d1ac98487eeac4e7ef273aa9b44e902531e416 +size 3664 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index dc6fb700fb..ce25202150 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -12,7 +12,6 @@ from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.methods.symptommanager import Symptom from tlo.population import IndividualProperties -from tlo.util import transition_states logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -353,7 +352,7 @@ def look_up_consumable_item_codes(self): get_item_codes('Gloves, exam, latex, disposable, pair'): 4, get_item_codes('Contact lens'): 7 } - self.cons_item_codes['eye_injection'] = { + self.cons_item_codes['anti_vegf_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes('Aflibercept, 2mg'): 3 } @@ -505,7 +504,6 @@ def do_at_generic_first_appt( topen=self.sim.date ) - elif dr_stage == 'severe' or dr_stage == 'proliferative': # Interventions for severe and proliferative schedule_hsi_event( @@ -513,39 +511,6 @@ def do_at_generic_first_appt( priority=0, topen=self.sim.date) -class HSI_Dr_DietManagement(HSI_Event, IndividualScopeEventMixin): - """This is a Health System Interaction Event in which a person receives a session of diet management in the - diabetes clinic. It is one of a course of 5 sessions (at months 0, 6, 12, 18, 24). If one of these HSI does not happen - then no further sessions occur. Sessions after the first have no direct effect, as the only property affected is - reflects ever having had one session of talking therapy.""" - - def __init__(self, module, person_id): - super().__init__(module, person_id=person_id) - - self.TREATMENT_ID = 'Dr_DietManagement' - self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) - self.ACCEPTED_FACILITY_LEVEL = '2' - self.num_of_sessions_had = 0 # A counter for the number of diet management sessions had - - def apply(self, person_id, squeeze_factor): - """Set the property `dr_ever_diet_mgmt` to be True and schedule the next session in the course if the person - has not yet had 5 sessions.""" - - self.num_of_sessions_had += 1 - - df = self.sim.population.props - if not df.at[person_id, 'dr_ever_diet_mgmt']: - df.at[person_id, 'dr_ever_diet_mgmt'] = True - - if self.num_of_sessions_had < 5: - self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=self, - topen=self.sim.date + pd.DateOffset(months=6), - tclose=None, - priority=1 - ) - - class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): """ This event initiates the treatment of DR for severe and proliferative stages. @@ -622,6 +587,53 @@ def apply(self, person_id, squeeze_factor): # df.at[person_id, 'dr_status'] = 'proliferative' +class HSI_Dr_Dmo_AdvancedTreatment(HSI_Event, IndividualScopeEventMixin): + """ + This is the event when a person undergoes the optical coherence topography before being given the anti-vegf + injection + """ + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + assert isinstance(module, DiabeticRetinopathy) + + # Define the necessary information for an HSI + self.TREATMENT_ID = 'Dr_Advanced_Treatment' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) + self.ACCEPTED_FACILITY_LEVEL = '3' + self.ALERT_OTHER_DISEASES = [] + + def apply(self, person_id, squeeze_factor): + logger.debug(key='debug', + data=f'This is HSI_Dr_Dmo_AdvancedTreatment for person {person_id}') + df = self.sim.population.props + person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + df.at[person_id, 'dr_blindness_investigated'] = True + + is_cons_available = self.get_consumables( + self.module.cons_item_codes['anti_vegf_injection'] + ) + + dx_result = hs.dx_manager.run_dx_test( + dx_tests_to_run='optical_coherence_topography_dr_dmo', + hsi_event=self + ) + + if dx_result and is_cons_available: + # Will probably slow progression to proliferative if severe. + pass + + class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): """The only logging event for this module""" From a67bdd18a450afb1be779b1938c78df8786d8ae6 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 17 Jun 2025 16:09:31 +0200 Subject: [PATCH 28/85] Modifying LM --- src/tlo/methods/diabetic_retinopathy.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index ce25202150..00f402e4a9 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -322,6 +322,16 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['rate_onset_to_mild_dr'] ) + ##### Start from here ##### + self.lm['onset_mild_dr'] = LinearModel( + LinearModelType.MULTIPLICATIVE, + self.parameters['rate_onset_to_mild_dr'], + Predictor('had_treatment_during_this_stage', + external=True).when(True, p['rr_metastatic_prostate_ca_undergone_curative_treatment']), + Predictor('pc_status').when('local_ln', 1.0) + .otherwise(0.0) + ) + self.lm['mild_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, intercept=self.parameters['rate_mild_to_moderate'] From 4fa42d82d2ed716cb93935e661e79d460bbeacbe Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 25 Jun 2025 10:57:46 +0200 Subject: [PATCH 29/85] Add LM Predictor for people ever been treated. Remove resourcefilepath in test --- src/tlo/methods/diabetic_retinopathy.py | 54 ++++++++++----- tests/test_diabetic_retinopathy.py | 87 +++++++++++++------------ 2 files changed, 82 insertions(+), 59 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 00f402e4a9..9ac75622dc 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -103,6 +103,11 @@ class DiabeticRetinopathy(Module): Types.DATE, "date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)" ), + "dr_stage_at_which_treatment_given": Property( + Types.CATEGORICAL, + "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", + categories=["none", "mild", "moderate", "severe", "proliferative"] + ), "dr_mild_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with mild diabetic retinopathy" ), @@ -201,6 +206,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False @@ -305,6 +311,7 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dmo_status'] = 'none' self.sim.population.props.at[child_id, 'dr_on_treatment'] = False self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT + self.sim.population.props.at[child_id, 'dr_stage_at_which_treatment_given'] = 'none' self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False @@ -322,29 +329,25 @@ def make_the_linear_models(self) -> None: intercept=self.parameters['rate_onset_to_mild_dr'] ) - ##### Start from here ##### - self.lm['onset_mild_dr'] = LinearModel( - LinearModelType.MULTIPLICATIVE, - self.parameters['rate_onset_to_mild_dr'], - Predictor('had_treatment_during_this_stage', - external=True).when(True, p['rr_metastatic_prostate_ca_undergone_curative_treatment']), - Predictor('pc_status').when('local_ln', 1.0) - .otherwise(0.0) - ) - self.lm['mild_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_mild_to_moderate'] + self.parameters['rate_mild_to_moderate'], + Predictor('had_treatment_during_this_stage', external=True) + .when(True, 0.0).otherwise(1.0) ) self.lm['moderate_severe_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_moderate_to_severe'] + self.parameters['rate_moderate_to_severe'], + Predictor('had_treatment_during_this_stage', external=True) + .when(True, 0.0).otherwise(1.0) ) self.lm['severe_proliferative_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_severe_to_proliferative'] + self.parameters['rate_severe_to_proliferative'], + Predictor('had_treatment_during_this_stage', external=True) + .when(True, 0.0).otherwise(1.0) ) self.lm['ever_diet_mgmt_initialisation'] = LinearModel( @@ -434,6 +437,10 @@ def __init__(self, module): def apply(self, population: Population) -> None: df = population.props + had_treatment_during_this_stage = \ + df.is_alive & ~pd.isnull(df.dr_date_treatment) & \ + (df.dr_status == df.dr_stage_at_which_treatment_given) + diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] diabetes_and_alive_milddr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'mild')] diabetes_and_alive_moderatedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'moderate')] @@ -444,19 +451,26 @@ def apply(self, population: Population) -> None: will_progress_idx = df.index[np.where(will_progress)[0]] df.loc[will_progress_idx, 'dr_status'] = 'mild' - mild_to_moderate = self.module.lm['mild_moderate_dr'].predict(diabetes_and_alive_milddr, self.module.rng) + mild_to_moderate = self.module.lm['mild_moderate_dr'].predict( + diabetes_and_alive_milddr, + self.module.rng, + had_treatment_during_this_stage=had_treatment_during_this_stage) # mild_to_moderate_idx = mild_to_moderate[mild_to_moderate].index mild_to_moderate_idx = df.index[np.where(mild_to_moderate)[0]] df.loc[mild_to_moderate_idx, 'dr_status'] = 'moderate' - moderate_to_severe = self.module.lm['moderate_severe_dr'].predict(diabetes_and_alive_moderatedr, - self.module.rng) + moderate_to_severe = self.module.lm['moderate_severe_dr'].predict( + diabetes_and_alive_moderatedr, + self.module.rng, + had_treatment_during_this_stage=had_treatment_during_this_stage) # moderate_to_severe_idx = moderate_to_severe[moderate_to_severe].index moderate_to_severe_idx = df.index[np.where(moderate_to_severe)[0]] df.loc[moderate_to_severe_idx, 'dr_status'] = 'severe' - severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict(diabetes_and_alive_severedr, - self.module.rng) + severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict( + diabetes_and_alive_severedr, + self.module.rng, + had_treatment_during_this_stage=had_treatment_during_this_stage) # severe_to_proliferative_idx = mild_to_moderate[severe_to_proliferative].index severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' @@ -552,6 +566,8 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + assert pd.isnull(df.at[person_id, 'dr_date_treatment']) + # randomly_sampled = self.module.rng.rand() # treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] @@ -569,6 +585,8 @@ def apply(self, person_id, squeeze_factor): if dx_result and is_cons_available: # record date of diagnosis df.at[person_id, 'dr_date_diagnosis'] = self.sim.date + df.at[person_id, 'dr_date_treatment'] = self.sim.date + df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] # If consumables are available, add equipment used and run dx_test self.add_equipment({'Ophthalmoscope'}) diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 9a119e8ff7..b425e303ec 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -32,25 +32,23 @@ def get_simulation(seed): """Return simulation objection with Diabetic Retinopathy and other necessary modules registered.""" sim = Simulation( - start_date=start_date, - seed=seed, - ) - - sim.register(demography.Demography(resourcefilepath=resourcefilepath), - simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), - enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), - healthsystem.HealthSystem(resourcefilepath=resourcefilepath, - disable=False, - cons_availability='all'), - symptommanager.SymptomManager(resourcefilepath=resourcefilepath), - healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath, - # force symptoms to lead to health care seeking: - force_any_symptom_to_lead_to_healthcareseeking=True - ), - healthburden.HealthBurden(resourcefilepath=resourcefilepath), - cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + start_date=start_date, + seed=seed, + resourcefilepath=resourcefilepath + ) + + sim.register(demography.Demography(), + simplified_births.SimplifiedBirths(), + enhanced_lifestyle.Lifestyle(), + healthsystem.HealthSystem(disable=False, cons_availability='all'), + symptommanager.SymptomManager(), + healthseekingbehaviour.HealthSeekingBehaviour( # force symptoms to lead to health care seeking: + force_any_symptom_to_lead_to_healthcareseeking=True + ), + healthburden.HealthBurden(), + cardio_metabolic_disorders.CardioMetabolicDisorders(), diabetic_retinopathy.DiabeticRetinopathy(), - depression.Depression(resourcefilepath=resourcefilepath), + depression.Depression(), ) return sim @@ -61,43 +59,43 @@ def get_simulation_healthsystemdisabled(seed): sim = Simulation( start_date=start_date, seed=seed, + resourcefilepath=resourcefilepath ) # Register the appropriate modules - sim.register(demography.Demography(resourcefilepath=resourcefilepath), - simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), - enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), - healthsystem.HealthSystem(resourcefilepath=resourcefilepath, - disable=True), - symptommanager.SymptomManager(resourcefilepath=resourcefilepath), - healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath, - # force symptoms to lead to health care seeking: - force_any_symptom_to_lead_to_healthcareseeking=False - ), - healthburden.HealthBurden(resourcefilepath=resourcefilepath), - cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + sim.register(demography.Demography(), + simplified_births.SimplifiedBirths(), + enhanced_lifestyle.Lifestyle(), + healthsystem.HealthSystem(disable=True), + symptommanager.SymptomManager(), + healthseekingbehaviour.HealthSeekingBehaviour( # force symptoms to lead to health care seeking: + force_any_symptom_to_lead_to_healthcareseeking=False + ), + healthburden.HealthBurden(), + cardio_metabolic_disorders.CardioMetabolicDisorders(), diabetic_retinopathy.DiabeticRetinopathy(), - depression.Depression(resourcefilepath=resourcefilepath), + depression.Depression(), ) return sim + def get_simulation_nohsi(seed): """Make the simulation with: * the healthsystem enabled but with no service availabilty (so no HSI run) """ - sim = Simulation(start_date=start_date, seed=seed) + sim = Simulation(start_date=start_date, seed=seed, resourcefilepath=resourcefilepath) # Register the appropriate modules - sim.register(demography.Demography(resourcefilepath=resourcefilepath), - simplified_births.SimplifiedBirths(resourcefilepath=resourcefilepath), - enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), - healthsystem.HealthSystem(resourcefilepath=resourcefilepath, service_availability=[]), - symptommanager.SymptomManager(resourcefilepath=resourcefilepath), - healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath), - healthburden.HealthBurden(resourcefilepath=resourcefilepath), - cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), + sim.register(demography.Demography(), + simplified_births.SimplifiedBirths(), + enhanced_lifestyle.Lifestyle(), + healthsystem.HealthSystem(service_availability=[]), + symptommanager.SymptomManager(), + healthseekingbehaviour.HealthSeekingBehaviour(), + healthburden.HealthBurden(), + cardio_metabolic_disorders.CardioMetabolicDisorders(), diabetic_retinopathy.DiabeticRetinopathy(), - depression.Depression(resourcefilepath=resourcefilepath) + depression.Depression() ) return sim @@ -114,22 +112,26 @@ def zero_out_init_prev(sim): # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 return sim + def make_high_init_prev(sim): # Set initial prevalence to a high value: sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.1] * 4 # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 return sim + def incr_rate_of_onset_mild(sim): # Rate of cancer onset per # months: sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.05 return sim + def zero_rate_of_onset_mild(sim): # Rate of cancer onset per # months: sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.00 return sim + def incr_rates_of_progression(sim): # Rates of DR progression: sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] *= 5 @@ -170,6 +172,7 @@ def test_basic_run(seed): sim.simulate(end_date=Date(2010, 5, 1)) check_dtypes(sim) + def test_initial_config_of_pop_usual_prevalence(seed): """Tests the way the population is configured: with usual initial prevalence values""" sim = get_simulation_healthsystemdisabled(seed=seed) @@ -177,6 +180,7 @@ def test_initial_config_of_pop_usual_prevalence(seed): check_dtypes(sim) check_configuration_of_population(sim) + def test_initial_config_of_pop_zero_prevalence(seed): """Tests the way the population is configured: with zero initial prevalence values """ sim = get_simulation_healthsystemdisabled(seed=seed) @@ -196,6 +200,7 @@ def test_initial_config_of_pop_high_prevalence(seed): check_dtypes(sim) check_configuration_of_population(sim) + @pytest.mark.slow def test_run_sim_from_high_prevalence(seed): """Run the simulation from the usual prevalence values and high rates of incidence and check configuration of From 0de5c4cc85dec7b0b195e1dc762311b3d1a27ddb Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 25 Jun 2025 14:21:03 +0200 Subject: [PATCH 30/85] Calling HSI_Dr_Dmo_AdvancedTreatment --- src/tlo/methods/diabetic_retinopathy.py | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 9ac75622dc..c516140b94 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -658,8 +658,21 @@ def apply(self, person_id, squeeze_factor): ) if dx_result and is_cons_available: - # Will probably slow progression to proliferative if severe. - pass + if person.dr_status == "severe": + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self.module, person_id=person_id), + topen=self.sim.date + DateOffset(months=3), + tclose=None, + priority=0 + ) + + elif person.dr_status == 'proliferative': + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self.module, person_id=person_id), + topen=self.sim.date + DateOffset(months=1), + tclose=None, + priority=0 + ) class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): From 01c5de253a93a6eefc01d1752f91c0e5ad11c092 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 26 Jun 2025 08:54:16 +0200 Subject: [PATCH 31/85] Tidy up --- src/tlo/methods/diabetic_retinopathy.py | 55 ++++++++----------------- 1 file changed, 17 insertions(+), 38 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index c516140b94..08935bed01 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -18,7 +18,7 @@ class DiabeticRetinopathy(Module): - """ This is Diabetic Retinopathy module. It seeks to model of blindness due to diabetes. """ + """ This is Diabetic Retinopathy (DR) module. It seeks to model of DR effects. """ INIT_DEPENDENCIES = {'SymptomManager', 'Lifestyle', 'HealthSystem', 'CardioMetabolicDisorders'} ADDITIONAL_DEPENDENCIES = set() @@ -32,23 +32,24 @@ class DiabeticRetinopathy(Module): PARAMETERS = { "rate_onset_to_mild_dr": Parameter(Types.REAL, - "Probability of people who get diagnosed with mild diabetic retinopathy"), + "Probability of people who get diagnosed with mild " + "diabetic retinopathy"), "rate_mild_to_moderate": Parameter(Types.REAL, - "Probability of people who get diagnosed with moderate diabetic retinopathy"), + "Probability of people who get diagnosed with moderate " + "diabetic retinopathy"), "rate_moderate_to_severe": Parameter(Types.REAL, - "Probability of people who get diagnosed with severe diabetic retinopathy"), + "Probability of people who get diagnosed with severe " + "diabetic retinopathy"), "rate_severe_to_proliferative": Parameter(Types.REAL, - "Probability of people who get diagnosed with proliferative " - "diabetic retinopathy"), + "Probability of people who get diagnosed with " + "proliferative diabetic retinopathy"), 'prob_fast_dr': Parameter(Types.REAL, - "Probability of people who get diagnosed from none phase to proliferative diabetic " - "retinopathy stage"), + "Probability of people who get diagnosed from none phase to " + "proliferative diabetic retinopathy stage"), "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), - "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having Diabetic " - "Macular Oedema (DMO)"), - # "init_prob_proliferative_dr": Parameter(Types.REAL, "Initial probability of people with diabetic - # retinopathy in the proliferative stage"), + "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having " + "Diabetic Macular Oedema (DMO)"), "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), "init_prob_ever_diet_mgmt_if_diagnosed": Parameter( Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " @@ -82,7 +83,8 @@ class DiabeticRetinopathy(Module): "probs_for_dmo_when_dr_status_severe": Parameter( Types.LIST, "probability of having a DMO state when an individual has severe Diabetic Retinopathy "), "probs_for_dmo_when_dr_status_proliferative": Parameter( - Types.LIST, "probability of having a DMO state when an individual has proliferative Diabetic Retinopathy "), + Types.LIST, "probability of having a DMO state when an individual has " + "proliferative Diabetic Retinopathy "), } PROPERTIES = { @@ -125,10 +127,6 @@ class DiabeticRetinopathy(Module): Types.BOOL, "Whether blindness has been investigated, and diabetic retinopathy missed" ), - "dr_ever_diet_mgmt": Property(Types.BOOL, - "Whether this person has ever had a diabetic retinopathy diet management" - "session in the diabetic clinic"), - } def __init__(self): @@ -163,7 +161,6 @@ def read_parameters(self, data_folder: str | Path) -> None: # self.parameters['init_prob_proliferative_dr'] = 0.09 self.parameters['p_medication'] = 0.8 self.parameters['effectiveness_of_laser_photocoagulation_in_severe_regression'] = 0.21 - self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] = 0.1 self.parameters['prob_reg_eye_exam'] = 0.05 self.parameters['rp_dr_ex_alc'] = 1.1 @@ -209,7 +206,6 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False - df.loc[list(alive_diabetes_idx), "dr_ever_diet_mgmt"] = False # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -315,7 +311,6 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False - self.sim.population.props.at[child_id, 'dr_ever_diet_mgmt'] = False def on_simulation_end(self) -> None: pass @@ -350,11 +345,6 @@ def make_the_linear_models(self) -> None: .when(True, 0.0).otherwise(1.0) ) - self.lm['ever_diet_mgmt_initialisation'] = LinearModel( - LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['init_prob_ever_diet_mgmt_if_diagnosed'] - ) - def look_up_consumable_item_codes(self): """Look up the item codes used in the HSI of this module""" get_item_codes = self.sim.modules['HealthSystem'].get_item_code_from_item_name @@ -529,9 +519,9 @@ def do_at_generic_first_appt( ) elif dr_stage == 'severe' or dr_stage == 'proliferative': - # Interventions for severe and proliferative + # Intervention for severe and proliferative schedule_hsi_event( - hsi_event=HSI_Dr_StartTreatment(module=self, person_id=person_id), + hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self, person_id=person_id), priority=0, topen=self.sim.date) @@ -708,20 +698,9 @@ def apply(self, population): date_now = self.sim.date date_lastlog = self.sim.date - pd.DateOffset(months=self.repeat) - n_any_dr = (df.is_alive & ((df.dr_status == "proliferative") | (df.dr_status == "mild"))).sum() - n_ever_diet_mgmt = ( - df.dr_ever_diet_mgmt & df.is_alive & ((df.dr_status == "proliferative") | (df.dr_status == "mild"))).sum() - - def zero_out_nan(x): - return x if not np.isnan(x) else 0.0 - - def safe_divide(x, y): - return float(x / y) if y > 0.0 else 0.0 - out.update({ 'diagnosed_since_last_log': df.dr_date_diagnosis.between(date_lastlog, date_now).sum(), 'treated_since_last_log': df.dr_date_treatment.between(date_lastlog, date_now).sum(), - 'prop_ever_diet_mgmt_if_any_dr': zero_out_nan(safe_divide(n_ever_diet_mgmt, n_any_dr)), }) logger.info(key='summary_stats', data=out) From 7d981df2f09948d7b7a0e9389cf721d1f22243e1 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 26 Jun 2025 08:55:31 +0200 Subject: [PATCH 32/85] tidy up --- src/tlo/methods/diabetic_retinopathy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 08935bed01..d1bd3621d5 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -18,7 +18,7 @@ class DiabeticRetinopathy(Module): - """ This is Diabetic Retinopathy (DR) module. It seeks to model of DR effects. """ + """ This is Diabetic Retinopathy (DR) module. It seeks to model DR effects. """ INIT_DEPENDENCIES = {'SymptomManager', 'Lifestyle', 'HealthSystem', 'CardioMetabolicDisorders'} ADDITIONAL_DEPENDENCIES = set() From 85d8691742958cb3b0f33059d4b1a12a3de56995 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 10 Jul 2025 10:12:44 +0200 Subject: [PATCH 33/85] Parameters for controlled diabetes --- src/tlo/methods/diabetic_retinopathy.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index d1bd3621d5..2e52df3772 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -73,6 +73,14 @@ class DiabeticRetinopathy(Module): "rp_dr_urban": Parameter( Types.REAL, "relative prevalence at baseline of diabetic retinopathy if urban" ), + "prob_diabetes_controlled": Parameter( + Types.REAL, + "Probability that a person with mild DR has controlled diabetes" + ), + "prob_mild_to_none_if_controlled_diabetes": Parameter( + Types.REAL, + "Probability that people with mild DR and controlled diabetes regress to 'none'" + ), 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( Types.REAL, 'Probability of severe diabetic retinopathy regressing to moderate.'), @@ -161,6 +169,8 @@ def read_parameters(self, data_folder: str | Path) -> None: # self.parameters['init_prob_proliferative_dr'] = 0.09 self.parameters['p_medication'] = 0.8 self.parameters['effectiveness_of_laser_photocoagulation_in_severe_regression'] = 0.21 + self.parameters["prob_diabetes_controlled"] = 0.5 + self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 self.parameters['prob_reg_eye_exam'] = 0.05 self.parameters['rp_dr_ex_alc'] = 1.1 From 813ce1bd1397f46e2c63218d25ce8e779921ed09 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 10 Jul 2025 14:40:03 +0200 Subject: [PATCH 34/85] Controlled diabetes regression to "none" in polling event --- src/tlo/methods/diabetic_retinopathy.py | 37 +++++++++++-------------- 1 file changed, 16 insertions(+), 21 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 2e52df3772..31161aa147 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -478,27 +478,22 @@ def apply(self, population: Population) -> None: # Update DMO status self.module.update_dmo_status() - # fast_dr = self.module.lm['onset_fast_dr'].predict(diabetes_and_alive_nodr, self.module.rng) - # # fast_dr_idx = fast_dr[fast_dr].index - # fast_dr_idx = df.index[np.where(fast_dr)[0]] - # df.loc[fast_dr_idx, 'dr_status'] = 'late' - - # eligible_for_ns_threatening = df.loc[df.is_alive & df.nc_diabetes & (df.age_years >= 40) - # & (df.dr_status == 'none')] - # - # df.loc[eligible_for_ns_threatening, 'selected_for_regular_eye_exam'] = ( - # np.random.random_sample(size=len(df[eligible_for_ns_threatening])) - # < self.module.parameters['prob_reg_eye_exam']) - # - # # Schedule HSI event for selected individuals - # selected_for_exam = df.index[df['selected_for_regular_eye_exam']] - # for person_id in selected_for_exam: - # self.sim.modules['HealthSystem'].schedule_hsi_event( - # hsi_event=HSI_Regular_Eye_Exam(module=self.module, person_id=person_id), - # priority=0, - # topen=self.sim.date, - # tclose=None - # ) + mild_dr_individuals = diabetes_and_alive_milddr + # Get those who are currently on diabetes weight loss medication from cardiometabolicdisorders + mild_dr_individuals_eligible = mild_dr_individuals[mild_dr_individuals.nc_diabetes_on_medication] + # Get those with controlled diabetes among those with mild dr_status + selected_individuals_with_controlled_and_mild = ( + self.module.rng.random_sample(len(mild_dr_individuals_eligible)) + < self.module.parameters['prob_diabetes_controlled']) + controlled_and_mild_idx = mild_dr_individuals_eligible.index[selected_individuals_with_controlled_and_mild] + + # Get those who will regress to none dr_status among those with mild dr_status and controlled diabetes + selected_to_regress_to_none = (self.module.rng.random_sample(len(controlled_and_mild_idx)) + < self.module.parameters['prob_mild_to_none_if_controlled_diabetes']) + regress_to_none_idx = controlled_and_mild_idx[selected_to_regress_to_none] + + df.loc[regress_to_none_idx, "dr_status"] = "none" + # df.loc[regress_to_none_idx, "dmo_status"] = "none" def do_at_generic_first_appt( self, From c67b6060205a4a7d2d870a7e21734952b955a330 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 10 Jul 2025 15:00:27 +0200 Subject: [PATCH 35/85] tidy up --- src/tlo/methods/diabetic_retinopathy.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 31161aa147..069d676bb8 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -310,7 +310,7 @@ def report_daly_values(self) -> pd.Series: return pd.Series(index=self.sim.population.props.index, data=0.0) def on_birth(self, mother_id: int, child_id: int) -> None: - """ set properties of a child when they are born. + """ Set properties of a child when they are born. :param child_id: the new child """ self.sim.population.props.at[child_id, 'dr_status'] = 'none' @@ -510,7 +510,6 @@ def do_at_generic_first_appt( if dr_stage == 'none': return - # Interventions for MAM elif dr_stage == 'mild' or dr_stage == 'moderate': # schedule HSI for mild and moderate self.sim.modules["HealthSystem"].schedule_hsi_event( @@ -530,10 +529,10 @@ def do_at_generic_first_appt( priority=0, topen=self.sim.date) -class HSI_Dr_StartTreatment(HSI_Event, IndividualScopeEventMixin): +class HSI_Dr_LaserTreatment(HSI_Event, IndividualScopeEventMixin): """ - This event initiates the treatment of DR for severe and proliferative stages. - This event is scheduled by HSI_GenericFirstAppt. + This is the Laser treatment of DR for dr_status mild and moderate stages. Given to individuals + who have gone through HSI_CardioMetabolicDisorders_StartWeightLossAndMedication but condition did not person. """ def __init__(self, module, person_id): @@ -587,8 +586,9 @@ def apply(self, person_id, squeeze_factor): if person.dr_status == 'severe': #determine_effectiveness - self.module.do_treatment(person_id, prob_success=self.module.parameters[ - 'effectiveness_of_laser_photocoagulation_in_severe_regression']) + pass + # self.module.do_treatment(person_id, prob_success=self.module.parameters[ + # 'effectiveness_of_laser_photocoagulation_in_severe_regression']) # if treatment_slows_progression_to_proliferative: # df.at[person_id, 'dr_on_treatment'] = True @@ -613,7 +613,7 @@ def apply(self, person_id, squeeze_factor): class HSI_Dr_Dmo_AdvancedTreatment(HSI_Event, IndividualScopeEventMixin): """ This is the event when a person undergoes the optical coherence topography before being given the anti-vegf - injection + injection. Given to individuals with dr_status of severe and proliferative """ def __init__(self, module, person_id): From 74ff6ddc7ea328ef2a575fc569afdabddf0095b3 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 10 Jul 2025 16:09:56 +0200 Subject: [PATCH 36/85] Resource file. Not populated --- .../ResourceFile_Diabetic_Retinopathy/Parameter_values.csv | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv new file mode 100644 index 0000000000..b693705694 --- /dev/null +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:75b53759d6d906a447a56effe9abcf74fe1453a521c10f824d9b42663d2dce12 +size 91 From 104f4a49d711100a7c5b4419803752fe87eecbac Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 14 Jul 2025 16:49:50 +0200 Subject: [PATCH 37/85] resolve conflict --- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 4 ++-- .../ClinicallyVulnerable.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 4 ++-- .../VerticalProgrammes.csv | 4 ++-- 10 files changed, 20 insertions(+), 20 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 30bc02d7fa..e62b67a48c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid 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a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index af14057a60..cf4c56df02 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:fb3778a01a26b84ff18ce01b07a1b6747eb39ee6908aefc99c9c5cf2ecd884c4 -size 3666 +oid sha256:430dc1281920f9151f537c5d0e0a040288ccf085f29313c423e86388b42391cc +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 7b6addb8b4..7ea61098c3 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:3b0065aa7ab09db8e282af93f5aa2e032e5c239e0e991c83fa6f2d1c3e5746bd -size 3665 +oid sha256:56694ed7f757b9964e60f5e99c92899c7ce73ee44860281f7fdc454938cc3304 +size 3693 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 783b97daa1..8cd3747f3c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid 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b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:b30457c05c9970dc6799944bb375b1d76ba5d42eec4601605f77928b30d41d1f -size 3666 +oid sha256:fd7a981b69eff0587a5293624cc31b541cd1d9657bdbab2a5502244d817050e9 +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 37af670f17..d64947bc8f 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:ca223330aeb1cc05efeee6527ae93a76a72c12493d05c20ccec3ac6211623e05 -size 3666 +oid sha256:e7221483474a73c90e38e4967f9823fa379fa94ae5151b55899e2c2bb8440f2d +size 3694 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 75bc4b5632..3bf7850a3c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:199892a625598b20e18442c252d1ac98487eeac4e7ef273aa9b44e902531e416 -size 3664 +oid sha256:723699b772186ad9dd6f9e12a1960e479dede0c7efdf1093db9be7810f8c9f37 +size 3692 From 8c41334ef86e0466e801d3601195bbdd4495c7ae Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 15 Jul 2025 08:53:29 +0200 Subject: [PATCH 38/85] resolve conflicts --- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 4 ---- .../ClinicallyVulnerable.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv | 3 --- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 3 --- .../VerticalProgrammes.csv | 3 --- 10 files changed, 31 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 201987230f..e62b67a48c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,7 +1,3 @@ version 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a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 783b70631b..cf4c56df02 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:430dc1281920f9151f537c5d0e0a040288ccf085f29313c423e86388b42391cc size 3694 -======= -oid sha256:7df7846551d800f4d5ef180ca3c5e86ef5e34abed0ac729d62f1ccc5cbcb06eb -size 3616 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 8ee82eab4f..7ea61098c3 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:56694ed7f757b9964e60f5e99c92899c7ce73ee44860281f7fdc454938cc3304 size 3693 -======= -oid sha256:8a0022f7f61e196c47eb1ceefdc8242cdd68f3a04201d9ae8774b4c38f915d6a -size 3615 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 42b19b70a7..8cd3747f3c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:95aaa121e9c2e1cdbb8fce6964a879156c50188f51c2ec9684e4c371f582d01e size 3692 -======= -oid sha256:8b03d29cb18dc1c17bbe211938d5316f54bd3214ead8747998d053fab02c5e05 -size 3614 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index 791e13b803..7a245f8f57 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:20f8ec68806b762bd9f581a8a12d3f9b090c6221cd8f597cb26203de89df7072 size 3692 -======= -oid sha256:70bdd1c463e284153cece90157d5c0031f4d4502278f76f077e6fd6b823f53d7 -size 3614 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 38fc52d9b3..2ec5208f66 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:f46dcc37b14fe0bc235f5db436725e900630805620141a4383fa596f4fc1b693 size 3676 -======= -oid sha256:1288fe944f94418ae128a05dfe5fb14cd93c486a3af4a688d489d84acd633cc1 -size 3598 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 274bbce22a..c35967bab8 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:fd7a981b69eff0587a5293624cc31b541cd1d9657bdbab2a5502244d817050e9 size 3694 -======= -oid sha256:5e12c9a0cdb23828cd84376456af8496976eaaa963f0e1b034e6b6583388465c -size 3616 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index ba03ecb4d5..d64947bc8f 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:e7221483474a73c90e38e4967f9823fa379fa94ae5151b55899e2c2bb8440f2d size 3694 -======= -oid sha256:3053ab044843295219869e80c52c104ad46a074b9b99b444e7226499483f5654 -size 3616 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 1d71547727..3bf7850a3c 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,6 +1,3 @@ version https://git-lfs.github.com/spec/v1 oid sha256:723699b772186ad9dd6f9e12a1960e479dede0c7efdf1093db9be7810f8c9f37 size 3692 -======= -oid sha256:edae26838f12db8de9ba8dc08d439069ee01d80e2d1106c167d5cf242d8fa8bd -size 3614 From 01d27391920e15bc49e911c4066d6b802bf45311 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 15 Jul 2025 10:09:15 +0200 Subject: [PATCH 39/85] readme --- resources/healthsystem/consumables/README.md | 68 +------------------- 1 file changed, 3 insertions(+), 65 deletions(-) diff --git a/resources/healthsystem/consumables/README.md b/resources/healthsystem/consumables/README.md index fde597e51f..c6b25451de 100644 --- a/resources/healthsystem/consumables/README.md +++ b/resources/healthsystem/consumables/README.md @@ -1,65 +1,3 @@ -## Consumable Availability Scenarios - -This README describes the different **scenarios** used in consumable availability analysis. Each scenario corresponds to a specific level of availability of consumables across health facilities and months. The data for these scenarios are stored in columns such as `available_prop_scenario1`, `available_prop_scenario2`, etc., in the `ResourceFile_Consumables_availability_small.csv`. This is generated by the the following scripts - 1. `consumable_availability_estimation.py` generates the `available_prop` column representing the proportion of instances that a consumables is likely to be available given the levels of availability observed during 2018, 2. `generate_consumable_availability_scenarios_for_impact_analysis.py` generates additional scenarios of consumable availability ans appends them to the file generated by the first script. - -The scenario names below can be specified as parameters for `cons_availability` under `HealthSystem` when running simulations. - ---- - -### **Base Scenario** -- `default` - - **Description:** Actual 2018 availability estimates based on OpenLMIS data. - - **Purpose:** Serves as the baseline for comparisons. - ---- - -### **Scenarios 1–5: System-Level Improvements at Level 1a + 1b ** -These are based on regression analysis performed in [Mohan et al (2024)](https://pubmed.ncbi.nlm.nih.gov/38762283/). - -| Scenario | Column Name | Description | -|----------|---------------------------|-------------| -| 1 | `scenario1` | All items perform like *non-drug/diagnostic* consumables. | -| 2 | `scenario2` | Scenario 1 + all items match performance of *vital* medicines. | -| 3 | `scenario3` | Scenario 2 + all facilities match those managed by *pharmacists*. | -| 4 | `scenario4` | Scenario 3 + Level 1a facilities perform like Level 1b. | -| 5 | `scenario5` | Scenario 4 + All facilities perform like *CHAM* facilities. | - ---- - -### **Scenarios 6–9: Benchmarking Against Best Facilities** -| Scenario | Column Name | Description | -|----------|---------------------------|-------------| -| 6 | `scenario6` | All Level 1a/1b facilities match the *75th percentile* facility for each item. | -| 7 | `scenario7` | Same as above but using the *90th percentile*. | -| 8 | `scenario8` | Same as above but using the *99th percentile*. | -| 9 | `scenario9` | Level 1a, 1b, and 2 facilities match the *99th percentile*. | - ---- - -### **Scenarios 10–11: Horizontal Supply Chain Alignment** -| Scenario | Column Name | Description | -|----------|---------------------------|-------------| -| 10 | `scenario10` | All programs perform as well as *HIV* programs (only levels 1a and 1b updated). | -| 11 | `scenario11` | All programs perform as well as *EPI* programs (only levels 1a and 1b updated). | - -Scenarios 6-8 and 10-11 only include levels 1a and 1b where most of the service is delivered and consumable availability is particularly a challenge to match up with the regression-analysis-based scenarios 1-5 - ---- - -### **Scenarios 12–15: HIV Drug Supply Adjustments** -| Scenario | Column Name | Description | -|----------|---------------------------|-------------| -| 12 | `scenario12` | HIV performs as well (i.e. as badly) as general programs (excluding EPI and Cancer), benchmarked at *Facility_Level*. | -| 13 | `scenario13` | HIV performs as well as other programs, benchmarked at *Facility_ID*. | -| 14 | `scenario14` | Same as Scenario 13, but availability scaled *up* by 25%. | -| 15 | `scenario15` | Same as Scenario 13, but availability scaled *down* by 25%. | - ---- - -### **Upper Bound Scenario** -- **`all`** - - **Description:** All consumables are always available (i.e., 100% availability). - - **Purpose:** Represents the theoretical upper bound for health gains due to supply improvements. - ---- - +version https://git-lfs.github.com/spec/v1 +oid sha256:8caacbfcbf94df4a24a2bba66a71bf8f89514527dd32409a2e9d3bc69e177bfe +size 3913 From 02f4ad94a3cd16d2ba7ac7ab307ee798fdc1cdd3 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 21 Aug 2025 17:13:12 +0200 Subject: [PATCH 40/85] remove moderate stage and introduce mild/moderate stage --- src/tlo/methods/diabetic_retinopathy.py | 102 ++++++++++-------------- tests/test_diabetic_retinopathy.py | 19 +++-- 2 files changed, 50 insertions(+), 71 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 069d676bb8..fbe81df8f7 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -31,15 +31,12 @@ class DiabeticRetinopathy(Module): } PARAMETERS = { - "rate_onset_to_mild_dr": Parameter(Types.REAL, - "Probability of people who get diagnosed with mild " - "diabetic retinopathy"), - "rate_mild_to_moderate": Parameter(Types.REAL, - "Probability of people who get diagnosed with moderate " - "diabetic retinopathy"), - "rate_moderate_to_severe": Parameter(Types.REAL, - "Probability of people who get diagnosed with severe " - "diabetic retinopathy"), + "rate_onset_to_mild_or_moderate_dr": Parameter(Types.REAL, + "Probability of people who get diagnosed with non-proliferative " + "mild/moderate diabetic retinopathy"), + "rate_mild_or_moderate_to_severe": Parameter(Types.REAL, + "Probability of people who get diagnosed with severe " + "diabetic retinopathy"), "rate_severe_to_proliferative": Parameter(Types.REAL, "Probability of people who get diagnosed with " "proliferative diabetic retinopathy"), @@ -84,10 +81,9 @@ class DiabeticRetinopathy(Module): 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( Types.REAL, 'Probability of severe diabetic retinopathy regressing to moderate.'), - "probs_for_dmo_when_dr_status_mild": Parameter( - Types.LIST, "probability of having a DMO state when an individual has mild Diabetic Retinopathy "), - "probs_for_dmo_when_dr_status_moderate": Parameter( - Types.LIST, "probability of having a DMO state when an individual has mild Diabetic Retinopathy "), + "probs_for_dmo_when_dr_status_mild_or_moderate": Parameter( + Types.LIST, "probability of having a DMO state when an individual has non-proliferative mild/moderate " + "Diabetic Retinopathy "), "probs_for_dmo_when_dr_status_severe": Parameter( Types.LIST, "probability of having a DMO state when an individual has severe Diabetic Retinopathy "), "probs_for_dmo_when_dr_status_proliferative": Parameter( @@ -99,7 +95,7 @@ class DiabeticRetinopathy(Module): "dr_status": Property( Types.CATEGORICAL, "DR status", - categories=["none", "mild", "moderate", "severe", "proliferative"], + categories=["none", "mild_or_moderate", "severe", "proliferative"], ), "dmo_status": Property( Types.CATEGORICAL, @@ -116,10 +112,11 @@ class DiabeticRetinopathy(Module): "dr_stage_at_which_treatment_given": Property( Types.CATEGORICAL, "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", - categories=["none", "mild", "moderate", "severe", "proliferative"] + categories=["none", "mild_or_moderate", "severe", "proliferative"] ), "dr_mild_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with mild diabetic retinopathy" + Types.BOOL, "Whether this person has been diagnosed with mild/moderate non-proliferative diabetic " + "retinopathy" ), "dr_proliferative_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with proliferative diabetic retinopathy" @@ -149,19 +146,16 @@ def read_parameters(self, data_folder: str | Path) -> None: """ #TODO Read from resourcefile - self.parameters['rate_onset_to_mild_dr'] = 0.29 - - self.parameters['rate_mild_to_moderate'] = 0.4 - self.parameters['rate_moderate_to_severe'] = 0.5 + self.parameters['rate_onset_to_mild_or_moderate_dr'] = 0.29 + self.parameters['rate_mild_or_moderate_to_severe'] = 0.5 self.parameters['rate_severe_to_proliferative'] = 0.07 self.parameters['prob_fast_dr'] = 0.5 - self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.2] + self.parameters['init_prob_any_dr'] = [0.4, 0.3, 0.3] self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] - self.parameters['probs_for_dmo_when_dr_status_mild'] = [0.7, 0.1, 0.2] - self.parameters['probs_for_dmo_when_dr_status_moderate'] = [0.5, 0.3, 0.2] + self.parameters['probs_for_dmo_when_dr_status_mild_or_moderate'] = [0.7, 0.1, 0.2] self.parameters['probs_for_dmo_when_dr_status_severe'] = [0.3, 0.5, 0.2] self.parameters['probs_for_dmo_when_dr_status_proliferative'] = [0.1, 0.7, 0.2] @@ -329,21 +323,14 @@ def make_the_linear_models(self) -> None: """Make and save LinearModels that will be used when the module is running""" self.lm = dict() - self.lm['onset_mild_dr'] = LinearModel( + self.lm['onset_mild_or_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_onset_to_mild_dr'] + intercept=self.parameters['rate_onset_to_mild_or_moderate_dr'] ) - self.lm['mild_moderate_dr'] = LinearModel( + self.lm['mildmoderate_severe_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - self.parameters['rate_mild_to_moderate'], - Predictor('had_treatment_during_this_stage', external=True) - .when(True, 0.0).otherwise(1.0) - ) - - self.lm['moderate_severe_dr'] = LinearModel( - LinearModelType.MULTIPLICATIVE, - self.parameters['rate_moderate_to_severe'], + self.parameters['rate_mild_or_moderate_to_severe'], Predictor('had_treatment_during_this_stage', external=True) .when(True, 0.0).otherwise(1.0) ) @@ -360,8 +347,10 @@ def look_up_consumable_item_codes(self): get_item_codes = self.sim.modules['HealthSystem'].get_item_code_from_item_name self.cons_item_codes = dict() - self.cons_item_codes['laser_photocoagulation'] = { + self.cons_item_codes['laser_pan_retinal_photocoagulation'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, + get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, + get_item_codes("Ophthalmic gel, 15ml"): 1, get_item_codes('Gloves, exam, latex, disposable, pair'): 4, get_item_codes('Contact lens'): 7 } @@ -396,17 +385,15 @@ def update_dmo_status(self): df.loc[no_dr_mask, 'dmo_status'] = 'none' # Now only process people with valid DR status - valid_dr_statuses = ['mild', 'moderate', 'severe', 'proliferative'] + valid_dr_statuses = ['mild_or_moderate', 'severe', 'proliferative'] dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses)].index if not dr_idx.empty: for person in dr_idx: dr_stage = df.at[person, 'dr_status'] - if dr_stage == 'mild': - probs = self.parameters['probs_for_dmo_when_dr_status_mild'] - elif dr_stage == 'moderate': - probs = self.parameters['probs_for_dmo_when_dr_status_moderate'] + if dr_stage == 'mild_or_moderate': + probs = self.parameters['probs_for_dmo_when_dr_status_mild_or_moderate'] elif dr_stage == 'severe': probs = self.parameters['probs_for_dmo_when_dr_status_severe'] elif dr_stage == 'proliferative': @@ -442,30 +429,23 @@ def apply(self, population: Population) -> None: (df.dr_status == df.dr_stage_at_which_treatment_given) diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] - diabetes_and_alive_milddr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'mild')] + diabetes_and_alive_mild_moderate_dr = df.loc[ + df.is_alive & df.nc_diabetes & (df.dr_status == 'mild_or_moderate')] diabetes_and_alive_moderatedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'moderate')] diabetes_and_alive_severedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'severe')] - will_progress = self.module.lm['onset_mild_dr'].predict(diabetes_and_alive_nodr, self.module.rng) + will_progress = self.module.lm['onset_mild_or_moderate_dr'].predict(diabetes_and_alive_nodr, self.module.rng) # will_progress_idx = will_progress[will_progress].index will_progress_idx = df.index[np.where(will_progress)[0]] - df.loc[will_progress_idx, 'dr_status'] = 'mild' - - mild_to_moderate = self.module.lm['mild_moderate_dr'].predict( - diabetes_and_alive_milddr, - self.module.rng, - had_treatment_during_this_stage=had_treatment_during_this_stage) - # mild_to_moderate_idx = mild_to_moderate[mild_to_moderate].index - mild_to_moderate_idx = df.index[np.where(mild_to_moderate)[0]] - df.loc[mild_to_moderate_idx, 'dr_status'] = 'moderate' + df.loc[will_progress_idx, 'dr_status'] = 'mild_or_moderate' - moderate_to_severe = self.module.lm['moderate_severe_dr'].predict( - diabetes_and_alive_moderatedr, + mildmoderate_to_severe = self.module.lm['mildmoderate_severe_dr'].predict( + diabetes_and_alive_mild_moderate_dr, self.module.rng, had_treatment_during_this_stage=had_treatment_during_this_stage) # moderate_to_severe_idx = moderate_to_severe[moderate_to_severe].index - moderate_to_severe_idx = df.index[np.where(moderate_to_severe)[0]] - df.loc[moderate_to_severe_idx, 'dr_status'] = 'severe' + mildmoderate_to_severe_idx = df.index[np.where(mildmoderate_to_severe)[0]] + df.loc[mildmoderate_to_severe_idx, 'dr_status'] = 'severe' severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict( diabetes_and_alive_severedr, @@ -478,13 +458,13 @@ def apply(self, population: Population) -> None: # Update DMO status self.module.update_dmo_status() - mild_dr_individuals = diabetes_and_alive_milddr + mild_dr_individuals = diabetes_and_alive_mild_moderate_dr # Get those who are currently on diabetes weight loss medication from cardiometabolicdisorders mild_dr_individuals_eligible = mild_dr_individuals[mild_dr_individuals.nc_diabetes_on_medication] # Get those with controlled diabetes among those with mild dr_status selected_individuals_with_controlled_and_mild = ( - self.module.rng.random_sample(len(mild_dr_individuals_eligible)) - < self.module.parameters['prob_diabetes_controlled']) + self.module.rng.random_sample(len(mild_dr_individuals_eligible)) + < self.module.parameters['prob_diabetes_controlled']) controlled_and_mild_idx = mild_dr_individuals_eligible.index[selected_individuals_with_controlled_and_mild] # Get those who will regress to none dr_status among those with mild dr_status and controlled diabetes @@ -510,8 +490,8 @@ def do_at_generic_first_appt( if dr_stage == 'none': return - elif dr_stage == 'mild' or dr_stage == 'moderate': - # schedule HSI for mild and moderate + elif dr_stage == 'mild_or_moderate': + # schedule HSI for mild_or_moderate and moderate self.sim.modules["HealthSystem"].schedule_hsi_event( hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( person_id=person_id, @@ -531,7 +511,7 @@ def do_at_generic_first_appt( class HSI_Dr_LaserTreatment(HSI_Event, IndividualScopeEventMixin): """ - This is the Laser treatment of DR for dr_status mild and moderate stages. Given to individuals + This is the Laser treatment of DR for dr_status mild_or_moderate. Given to individuals who have gone through HSI_CardioMetabolicDisorders_StartWeightLossAndMedication but condition did not person. """ diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index b425e303ec..0839b9eccf 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -108,36 +108,35 @@ def check_dtypes(sim): def zero_out_init_prev(sim): # Set initial prevalence to zero: - sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.0] * 4 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.0] * 3 # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.0 return sim def make_high_init_prev(sim): # Set initial prevalence to a high value: - sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.1] * 4 + sim.modules['DiabeticRetinopathy'].parameters['init_prob_any_dr'] = [0.1] * 3 # sim.modules['DiabeticRetinopathy'].parameters['init_prob_late_dr'] = 0.1 return sim -def incr_rate_of_onset_mild(sim): +def incr_rate_of_onset_mild_or_moderate(sim): # Rate of cancer onset per # months: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.05 + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] = 0.05 return sim -def zero_rate_of_onset_mild(sim): +def zero_rate_of_onset_mild_or_moderate(sim): # Rate of cancer onset per # months: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] = 0.00 + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] = 0.00 return sim def incr_rates_of_progression(sim): # Rates of DR progression: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_dr'] *= 5 - sim.modules['DiabeticRetinopathy'].parameters['rate_mild_to_moderate'] *= 5 - sim.modules['DiabeticRetinopathy'].parameters['rate_moderate_to_severe'] *= 5 - sim.modules['DiabeticRetinopathy'].parameters['rate_severe_to_proliferative'] *= 5 + sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] *= 4 + sim.modules['DiabeticRetinopathy'].parameters['rate_mild_or_moderate_to_severe'] *= 4 + sim.modules['DiabeticRetinopathy'].parameters['rate_severe_to_proliferative'] *= 4 return sim From 1ad3fe45345a99b3c2ad8021a822cfa7cd00a86b Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 22 Aug 2025 07:36:32 +0200 Subject: [PATCH 41/85] HSI Laser Pan Retinal Coagulation. Not working yet --- ...rceFile_Consumables_Items_and_Packages.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 56 ++++++++++++++----- 2 files changed, 45 insertions(+), 15 deletions(-) diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index fc404c9149..ee72f95b7b 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:7c0c788b32e2c67fb791069ccee50f23e357a011c833bc10a5c1f4cd8c7cdbea -size 246722 +oid sha256:db947ae71c8c2914191654fcb1cbdaec24f3d0953a29ac8e5215e3cb8a3ad3d9 +size 246682 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index fbe81df8f7..7d21b0554b 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -128,10 +128,6 @@ class DiabeticRetinopathy(Module): Types.DATE, "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" ), - "dr_blindness_investigated": Property( - Types.BOOL, - "Whether blindness has been investigated, and diabetic retinopathy missed" - ), } def __init__(self): @@ -209,7 +205,6 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT - df.loc[list(alive_diabetes_idx), "dr_blindness_investigated"] = False # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -314,8 +309,6 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_stage_at_which_treatment_given'] = 'none' self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT - self.sim.population.props.at[child_id, 'dr_blindness_investigated'] = False - def on_simulation_end(self) -> None: pass @@ -351,8 +344,7 @@ def look_up_consumable_item_codes(self): get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, get_item_codes("Ophthalmic gel, 15ml"): 1, - get_item_codes('Gloves, exam, latex, disposable, pair'): 4, - get_item_codes('Contact lens'): 7 + get_item_codes('Gloves, exam, latex, disposable, pair'): 4 } self.cons_item_codes['anti_vegf_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, @@ -545,8 +537,6 @@ def apply(self, person_id, squeeze_factor): # randomly_sampled = self.module.rng.rand() # treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] - df.at[person_id, 'dr_blindness_investigated'] = True - is_cons_available = self.get_consumables( self.module.cons_item_codes['laser_photocoagulation'] ) @@ -621,8 +611,6 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() - df.at[person_id, 'dr_blindness_investigated'] = True - is_cons_available = self.get_consumables( self.module.cons_item_codes['anti_vegf_injection'] ) @@ -650,6 +638,48 @@ def apply(self, person_id, squeeze_factor): ) +class HSI_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): + """ + This is the HSI event given to individuals with proliferative diabetic retinopathy after undergoing an eye exam/screening + """ + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + assert isinstance(module, DiabeticRetinopathy) + + # Define the necessary information for an HSI + self.TREATMENT_ID = 'Dr_Laser_Pan_Retinal_Coagulation' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) + self.ACCEPTED_FACILITY_LEVEL = '3' + self.ALERT_OTHER_DISEASES = [] + + def apply(self, person_id, squeeze_factor): + logger.debug(key='debug', + data=f'This is HSI_Laser_Pan_Retinal_Coagulation for person {person_id}') + df = self.sim.population.props + person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + + is_cons_available = self.get_consumables( + self.module.cons_item_codes['laser_pan_retinal_photocoagulation'] + ) + + if is_cons_available: + self.add_equipment({'Laser generator', 'Delivery system', 'Contact lenses', 'Patient head support'}) + pass + # if person.dr_status == "proliferative": + # pass + + class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): """The only logging event for this module""" From 155f36359b550b8e20be480254fb2ba09cb9a7b8 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 27 Aug 2025 16:25:50 +0200 Subject: [PATCH 42/85] Add 4 HSIs --- src/tlo/methods/diabetic_retinopathy.py | 149 +++++++++++++++--------- 1 file changed, 91 insertions(+), 58 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 7d21b0554b..bb45e8fdc0 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -122,12 +122,16 @@ class DiabeticRetinopathy(Module): Types.BOOL, "Whether this person has been diagnosed with proliferative diabetic retinopathy" ), "dr_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy" + Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy or diabetic macular " + "oedema" ), "dr_date_diagnosis": Property( Types.DATE, "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" ), + "selected_for_eye_exam": Property( + Types.BOOL,"selected for via this period" + ), } def __init__(self): @@ -202,6 +206,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False + df.loc[list(alive_diabetes_idx), "selected_for_eye_exam"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT @@ -308,6 +313,7 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_stage_at_which_treatment_given'] = 'none' self.sim.population.props.at[child_id, 'dr_diagnosed'] = False + self.sim.population.props.at[child_id, 'selected_for_eye_exam'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT def on_simulation_end(self) -> None: pass @@ -348,7 +354,21 @@ def look_up_consumable_item_codes(self): } self.cons_item_codes['anti_vegf_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, - get_item_codes('Aflibercept, 2mg'): 3 + get_item_codes('Aflibercept, 2mg'): 3, + get_item_codes("Antiseptic solution, 15ml"): 1, + get_item_codes("Sterile syringe"): 1 + } + + self.cons_item_codes['focal_laser'] = { + get_item_codes("Anesthetic Eye drops, 15ml"): 1, + get_item_codes('Aflibercept, 2mg'): 3, + get_item_codes('Sterile drapes and supplies'): 3, + get_item_codes('Diagnostic dye'): 1 + } + + self.cons_item_codes['eye_examination'] = { + get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, + get_item_codes('Fluorescin dye'): 1 } def do_recovery(self, idx: Union[list, pd.Index]): @@ -497,29 +517,26 @@ def do_at_generic_first_appt( elif dr_stage == 'severe' or dr_stage == 'proliferative': # Intervention for severe and proliferative schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self, person_id=person_id), + hsi_event=HSI_Dr_AntiVEGF(module=self, person_id=person_id), priority=0, topen=self.sim.date) -class HSI_Dr_LaserTreatment(HSI_Event, IndividualScopeEventMixin): - """ - This is the Laser treatment of DR for dr_status mild_or_moderate. Given to individuals - who have gone through HSI_CardioMetabolicDisorders_StartWeightLossAndMedication but condition did not person. - """ +class HSI_Dr_Eye_Examination(HSI_Event, IndividualScopeEventMixin): + """This is the Eye examination done to individuals selected for screening for individuals with any complication""" def __init__(self, module, person_id): super().__init__(module, person_id=person_id) assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Treatment_Initiation' + self.TREATMENT_ID = 'Dr_Eye_Examination' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): logger.debug(key='debug', - data=f'This is HSI_Dr_StartTreatment: initiating treatment for person {person_id}') + data=f'This is HSI_Dr_Eye_Examination: investigating the condition of {person_id}') df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] @@ -534,11 +551,8 @@ def apply(self, person_id, squeeze_factor): assert pd.isnull(df.at[person_id, 'dr_date_treatment']) - # randomly_sampled = self.module.rng.rand() - # treatment_slows_progression_to_proliferative = randomly_sampled < self.module.parameters['p_medication'] - is_cons_available = self.get_consumables( - self.module.cons_item_codes['laser_photocoagulation'] + self.module.cons_item_codes['focal_laser'] ) dx_result = hs.dx_manager.run_dx_test( @@ -551,54 +565,30 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dr_date_diagnosis'] = self.sim.date df.at[person_id, 'dr_date_treatment'] = self.sim.date df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] - # If consumables are available, add equipment used and run dx_test - self.add_equipment({'Ophthalmoscope'}) + # If consumables are available, add equipment used + self.add_equipment({'Silt lamp', 'Optical coherence tomography device', + 'Ophthalmoscope/Fundus camera', 'Amsler grid'}) if person.dr_status == 'severe': - #determine_effectiveness pass - # self.module.do_treatment(person_id, prob_success=self.module.parameters[ - # 'effectiveness_of_laser_photocoagulation_in_severe_regression']) - - # if treatment_slows_progression_to_proliferative: - # df.at[person_id, 'dr_on_treatment'] = True - # df.at[person_id, 'dr_date_treatment'] = self.sim.date - # - # # Reduce probability of progression to "proliferative" DR - # progression_chance = self.module.parameters['rate_severe_to_proliferative'] * ( - # 1 - self.module.parameters['p_medication']) - # - # # Determine if person will still progress - # if self.module.rng.rand() < progression_chance: - # df.at[person_id, 'dr_status'] = 'proliferative' - # else: - # df.at[person_id, 'dr_status'] = 'mild' # Stays in mild stage due to medication - # - # else: - # # If medication is not effective, progression happens as usual - # df.at[person_id, 'dr_on_treatment'] = True - # df.at[person_id, 'dr_status'] = 'proliferative' - - -class HSI_Dr_Dmo_AdvancedTreatment(HSI_Event, IndividualScopeEventMixin): - """ - This is the event when a person undergoes the optical coherence topography before being given the anti-vegf - injection. Given to individuals with dr_status of severe and proliferative - """ + + +class HSI_Dr_Focal_Laser(HSI_Event, IndividualScopeEventMixin): + """This is the Laser treatment for individuals with CSMO.""" def __init__(self, module, person_id): super().__init__(module, person_id=person_id) assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Advanced_Treatment' + self.TREATMENT_ID = 'Dr_Focal_Laser_Treatment' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): logger.debug(key='debug', - data=f'This is HSI_Dr_Dmo_AdvancedTreatment for person {person_id}') + data=f'This is HSI_Dr_Focal_Laser: initiating laser treatment for person {person_id}') df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] @@ -611,19 +601,63 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + assert pd.isnull(df.at[person_id, 'dr_date_treatment']) + is_cons_available = self.get_consumables( - self.module.cons_item_codes['anti_vegf_injection'] + self.module.cons_item_codes['focal_laser'] ) - dx_result = hs.dx_manager.run_dx_test( - dx_tests_to_run='optical_coherence_topography_dr_dmo', - hsi_event=self + if is_cons_available: + # record date of diagnosis + df.at[person_id, 'dr_date_diagnosis'] = self.sim.date + df.at[person_id, 'dr_date_treatment'] = self.sim.date + df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] + # If consumables are available, add equipment used and run dx_test + self.add_equipment({'Ophthalmic Laser System', 'Laser Delivery System', 'Contact lenses'}) + + if person.dr_status == 'severe': + pass + + + +class HSI_Dr_AntiVEGF(HSI_Event, IndividualScopeEventMixin): + """This is the Anti-VEGF treatment for individuals with CSMO.""" + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + assert isinstance(module, DiabeticRetinopathy) + + # Define the necessary information for an HSI + self.TREATMENT_ID = 'Dr_AntiVEGF_Treatment' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) + self.ACCEPTED_FACILITY_LEVEL = '3' + self.ALERT_OTHER_DISEASES = [] + + def apply(self, person_id, squeeze_factor): + logger.debug(key='debug', + data=f'This is HSI_Dr_AntiVEGF for person {person_id}') + df = self.sim.population.props + person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + is_cons_available = self.get_consumables( + self.module.cons_item_codes['anti_vegf_injection'] ) - if dx_result and is_cons_available: + if is_cons_available: + self.add_equipment({'Silt lamp', 'Optical coherence tomography device', + 'Ophthalmoscope/Fundus camera', 'Goniometre'}) if person.dr_status == "severe": hs.schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self.module, person_id=person_id), + hsi_event=HSI_Dr_AntiVEGF(module=self.module, person_id=person_id), topen=self.sim.date + DateOffset(months=3), tclose=None, priority=0 @@ -631,16 +665,17 @@ def apply(self, person_id, squeeze_factor): elif person.dr_status == 'proliferative': hs.schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_AdvancedTreatment(module=self.module, person_id=person_id), + hsi_event=HSI_Dr_AntiVEGF(module=self.module, person_id=person_id), topen=self.sim.date + DateOffset(months=1), tclose=None, priority=0 ) -class HSI_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): +class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): """ - This is the HSI event given to individuals with proliferative diabetic retinopathy after undergoing an eye exam/screening + This is the HSI event given to individuals with proliferative diabetic retinopathy after undergoing an eye + exam/screening """ def __init__(self, module, person_id): @@ -676,8 +711,6 @@ def apply(self, person_id, squeeze_factor): if is_cons_available: self.add_equipment({'Laser generator', 'Delivery system', 'Contact lenses', 'Patient head support'}) pass - # if person.dr_status == "proliferative": - # pass class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): From 4d72e19a2ae1f6aae98e9e3bd3cb2008416377d2 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 27 Aug 2025 16:48:20 +0200 Subject: [PATCH 43/85] eligible population for screening --- src/tlo/methods/diabetic_retinopathy.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index bb45e8fdc0..33bd3273ee 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -121,7 +121,7 @@ class DiabeticRetinopathy(Module): "dr_proliferative_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with proliferative diabetic retinopathy" ), - "dr_diagnosed": Property( + "dr_dmo_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy or diabetic macular " "oedema" ), @@ -487,6 +487,18 @@ def apply(self, population: Population) -> None: df.loc[regress_to_none_idx, "dr_status"] = "none" # df.loc[regress_to_none_idx, "dmo_status"] = "none" + # ------------------------SELECTING INDIVIDUALS FOR FOR DR OR DMO EYE EXAM/SCREENING--------------------- + df.selected_for_eye_exam = False + + eligible_population_for_eye_exam = ( + (df.is_alive & df.nc_diabetes) & + (df.dr_status == 'none') & + (df.dmo_status == 'none') & + (df.age_years >= 20) & + (pd.isna(df.dr_date_diagnosis)) + ) + + def do_at_generic_first_appt( self, person_id: int, From b77cbd11a1b565d130a995e12fadfa093ee5eeed Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 28 Aug 2025 08:50:41 +0200 Subject: [PATCH 44/85] Selected for screening from polling event --- src/tlo/methods/diabetic_retinopathy.py | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 33bd3273ee..0e3a964a7e 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -89,6 +89,9 @@ class DiabeticRetinopathy(Module): "probs_for_dmo_when_dr_status_proliferative": Parameter( Types.LIST, "probability of having a DMO state when an individual has " "proliferative Diabetic Retinopathy "), + "prob_eye_exam": Parameter( + Types.REAL, "probability of going for an eye exam/screening" + ) } PROPERTIES = { @@ -164,6 +167,7 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['p_medication'] = 0.8 self.parameters['effectiveness_of_laser_photocoagulation_in_severe_regression'] = 0.21 self.parameters["prob_diabetes_controlled"] = 0.5 + self.parameters["prob_eye_exam"] = 0.07 self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 self.parameters['prob_reg_eye_exam'] = 0.05 @@ -491,13 +495,25 @@ def apply(self, population: Population) -> None: df.selected_for_eye_exam = False eligible_population_for_eye_exam = ( - (df.is_alive & df.nc_diabetes) & + (df.is_alive & df.nc_diabetes) & #todo add condition for people do not be selected again witin 1 year (df.dr_status == 'none') & (df.dmo_status == 'none') & (df.age_years >= 20) & (pd.isna(df.dr_date_diagnosis)) ) + df.loc[eligible_population_for_eye_exam, 'selected_for_eye_exam'] = ( + np.random.random_sample(size=len(df[eligible_population_for_eye_exam])) + < self.module.parameters['prob_eye_exam'] + ) + + for idx in df.index[df.selected_for_eye_exam]: + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Dr_Eye_Examination(module=self.module, person_id=idx), + priority=0, + topen=self.sim.date, + tclose=None) + def do_at_generic_first_appt( self, From 85097f5e898e2f650fe06ed0c04ed6fd03781f0d Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 18 Sep 2025 08:58:22 +0200 Subject: [PATCH 45/85] call eye exam cons in HSI --- src/tlo/methods/diabetic_retinopathy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 0e3a964a7e..af64adecbb 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -580,7 +580,7 @@ def apply(self, person_id, squeeze_factor): assert pd.isnull(df.at[person_id, 'dr_date_treatment']) is_cons_available = self.get_consumables( - self.module.cons_item_codes['focal_laser'] + self.module.cons_item_codes['eye_examination'] ) dx_result = hs.dx_manager.run_dx_test( From 70801f2614b24f769515295696aa2817bb2c28ff Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 1 Oct 2025 09:37:55 +0200 Subject: [PATCH 46/85] schedule mild moderate from eye exam --- src/tlo/methods/diabetic_retinopathy.py | 18 +++++++++++++++--- 1 file changed, 15 insertions(+), 3 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index af64adecbb..a0a41c2f38 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -495,7 +495,7 @@ def apply(self, population: Population) -> None: df.selected_for_eye_exam = False eligible_population_for_eye_exam = ( - (df.is_alive & df.nc_diabetes) & #todo add condition for people do not be selected again witin 1 year + (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year (df.dr_status == 'none') & (df.dmo_status == 'none') & (df.age_years >= 20) & @@ -531,7 +531,7 @@ def do_at_generic_first_appt( return elif dr_stage == 'mild_or_moderate': - # schedule HSI for mild_or_moderate and moderate + # schedule HSI for mild_or_moderate self.sim.modules["HealthSystem"].schedule_hsi_event( hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( person_id=person_id, @@ -597,7 +597,19 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Silt lamp', 'Optical coherence tomography device', 'Ophthalmoscope/Fundus camera', 'Amsler grid'}) - if person.dr_status == 'severe': + if person.dr_status == 'mild_or_moderate': + # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication and repeat HSI_DR_Eye_Examination in 1 year + self.sim.modules["HealthSystem"].schedule_hsi_event( + hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( + person_id=person_id, + module=self.sim.modules["CardioMetabolicDisorders"], + condition='diabetes', + ), + priority=0, + topen=self.sim.date + ) + elif person.dr_status == 'proliferative': + # schedule HSI_Dr_Laser_Pan_Retinal_Coagulation (treat in 2 sessions that are 1 week apart) and then review after 3 months pass From 70fa6845f914b0904c9384909b95e6b70b25066a Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 1 Oct 2025 17:04:50 +0200 Subject: [PATCH 47/85] progression logic for proliferative, severe and mild/moderate --- ...rceFile_Consumables_Items_and_Packages.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 87 ++++++++++++++++--- 2 files changed, 78 insertions(+), 13 deletions(-) diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index ee72f95b7b..e66c0e4ebd 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:db947ae71c8c2914191654fcb1cbdaec24f3d0953a29ac8e5215e3cb8a3ad3d9 -size 246682 +oid sha256:765dde474bad381f74598517e646fa7fa26b619211c442b142395c347cf1883a +size 247029 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index a0a41c2f38..48ed3ccbee 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -91,7 +91,12 @@ class DiabeticRetinopathy(Module): "proliferative Diabetic Retinopathy "), "prob_eye_exam": Parameter( Types.REAL, "probability of going for an eye exam/screening" - ) + ), + "prob_repeat_laser": Parameter( + Types.REAL, + "Probability that a patient who remains proliferative at follow-up/review will " + "require a repeat of HSI_Dr_Laser_Pan_Retinal_Coagulation" + ), } PROPERTIES = { @@ -117,6 +122,9 @@ class DiabeticRetinopathy(Module): "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", categories=["none", "mild_or_moderate", "severe", "proliferative"] ), + "dr_diagnosed": Property( + Types.BOOL, "Whether this person has been diagnosed with many form of diabetic retinopathy" + ), "dr_mild_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with mild/moderate non-proliferative diabetic " "retinopathy" @@ -133,7 +141,7 @@ class DiabeticRetinopathy(Module): "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" ), "selected_for_eye_exam": Property( - Types.BOOL,"selected for via this period" + Types.BOOL, "selected for via this period" ), } @@ -170,6 +178,7 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters["prob_eye_exam"] = 0.07 self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 self.parameters['prob_reg_eye_exam'] = 0.05 + self.parameters['prob_repeat_laser'] = 0.3 self.parameters['rp_dr_ex_alc'] = 1.1 self.parameters['rp_dr_tobacco'] = 1.3 @@ -319,6 +328,7 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'selected_for_eye_exam'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT + def on_simulation_end(self) -> None: pass @@ -495,7 +505,7 @@ def apply(self, population: Population) -> None: df.selected_for_eye_exam = False eligible_population_for_eye_exam = ( - (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year + (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year (df.dr_status == 'none') & (df.dmo_status == 'none') & (df.age_years >= 20) & @@ -514,7 +524,6 @@ def apply(self, population: Population) -> None: topen=self.sim.date, tclose=None) - def do_at_generic_first_appt( self, person_id: int, @@ -598,7 +607,8 @@ def apply(self, person_id, squeeze_factor): 'Ophthalmoscope/Fundus camera', 'Amsler grid'}) if person.dr_status == 'mild_or_moderate': - # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication and repeat HSI_DR_Eye_Examination in 1 year + # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication + # and repeat HSI_DR_Eye_Examination in 1 year self.sim.modules["HealthSystem"].schedule_hsi_event( hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( person_id=person_id, @@ -608,9 +618,40 @@ def apply(self, person_id, squeeze_factor): priority=0, topen=self.sim.date ) + + # repeat eye exam in 1 year + next_exam_if_mild_or_moderate = self.sim.date + pd.DateOffset(years=1) + self.sim.modules['HealthSystem'].schedule_hsi_event(self, + topen=next_exam_if_mild_or_moderate, + tclose=None, + priority=1) + + elif person.dr_status == 'severe': + next_exam_if_severe = self.sim.date + pd.DateOffset(months=3) + self.sim.modules['HealthSystem'].schedule_hsi_event(self, + topen=next_exam_if_severe, + tclose=None, + priority=1) + elif person.dr_status == 'proliferative': - # schedule HSI_Dr_Laser_Pan_Retinal_Coagulation (treat in 2 sessions that are 1 week apart) and then review after 3 months - pass + # If this is their FIRST diagnosis (no prior treatment yet), send them + # for HSI_Dr_Laser_Pan_Retinal_Coagulation + if pd.isna(person.dr_date_treatment): + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=1), + topen=self.sim.date, + priority=0 + ) + else: + # This is a scheduled follow-up or review (2 months / 3,6,9,12 months after + # HSI_Dr_Laser_Pan_Retinal_Coagulation). Since HSI_Dr_Laser_Pan_Retinal_Coagulation is + # scheduled for 2 weeks, this will only execute after at least 2 months and hence after session 2 + if self.module.rng.random_sample() < self.module.parameters['prob_repeat_laser']: + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=1), + topen=self.sim.date, + priority=0 + ) class HSI_Dr_Focal_Laser(HSI_Event, IndividualScopeEventMixin): @@ -659,7 +700,6 @@ def apply(self, person_id, squeeze_factor): pass - class HSI_Dr_AntiVEGF(HSI_Event, IndividualScopeEventMixin): """This is the Anti-VEGF treatment for individuals with CSMO.""" @@ -718,7 +758,7 @@ class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin) exam/screening """ - def __init__(self, module, person_id): + def __init__(self, module, person_id, session: int = 1): super().__init__(module, person_id=person_id) assert isinstance(module, DiabeticRetinopathy) @@ -743,14 +783,39 @@ def apply(self, person_id, squeeze_factor): if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() - is_cons_available = self.get_consumables( self.module.cons_item_codes['laser_pan_retinal_photocoagulation'] ) if is_cons_available: self.add_equipment({'Laser generator', 'Delivery system', 'Contact lenses', 'Patient head support'}) - pass + if self.session == 1: + # schedule the second session in 1 week + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=2), + topen=self.sim.date + pd.DateOffset(weeks=1), + priority=0 + ) + elif self.session == 2: + # completing treatment + df.at[person_id, 'dr_on_treatment'] = False + + # schedule follow-up at 2 months + follow_up = self.sim.date + pd.DateOffset(months=2) + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + topen=follow_up, + priority=1 + ) + + # schedule reviews at 3, 6, 9, 12 months + for m in [3, 6, 9, 12]: + review_date = self.sim.date + pd.DateOffset(months=m) + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + topen=review_date, + priority=1 + ) class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): From c99e5de37361ee673e1be4c3f97bb34bb0bced34 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 1 Oct 2025 17:33:06 +0200 Subject: [PATCH 48/85] update priority policies in healthsystem --- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 4 ++-- .../ClinicallyVulnerable.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 4 ++-- .../VerticalProgrammes.csv | 4 ++-- src/tlo/methods/diabetic_retinopathy.py | 2 +- 11 files changed, 21 insertions(+), 21 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 77e354f55d..15561e29da 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:1552fb022e91b02eb378a5deea67a726299e8407fe659bc2b146939f3f781932 -size 4020 +oid sha256:4ce883ae9769e1c2c331845d67170c1de3d32e323bceb5f9c2ff37179c0e6878 +size 4214 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index 24667e7103..f837e6c018 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:8395340b8fcc22bd891d3e0000ea8af3a1a2dc3ef3ead368b6d10a31ec125540 -size 3640 +oid sha256:2ddbc979dddb7cacec5f60532d5b5467a8b126ef4d4fbe03796632b64ed3f395 +size 3834 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 74e9ff1b41..232d946849 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:8f110ce1a0f9eaa31baf17223a0270b9254aa8c7d58ee00ccf158763f3078a74 -size 4022 +oid sha256:cacc6054bccf8a69edfbf5b91f5e472782f36040c1ba6c272fd4fc5afbc0a64a +size 4216 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 9424e6bdbd..d28aea053f 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:df8e079baa2dd1b181fb1eb5e02c069d6a7d33ad50c41f5683da4f286f0715e5 -size 4021 +oid sha256:ac0c14ecb2a7cf10cbff37b369e0d1a2e29262948087f24a0007ec347c147e4d +size 4215 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index b773f33f4b..21250e7566 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:249e6554084898c4fe563ba92c51c4d621854a90921d036fc1f91ca92a64dcbe -size 4020 +oid sha256:3752aabe855f3ab95eede3db26c0bbe1b009b82dc8bce156f42171300304462c +size 4214 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index ac918c1a9b..16eb2d8717 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:55964697b8b0269507cd03e4b0f774f3d1d5d42968b38c644508ff231c229444 -size 4020 +oid sha256:dcec4d189fa700d7b16fa99ce5cd1eacc50c377eb70d9ff5ffd1bd7ea066c7d5 +size 4214 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 04e0732859..a1362284e2 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:ec441dd94adbda5d0498b6debc03dc908c96323958343d1cd4333e09e0e6ab25 -size 4004 +oid sha256:0e60f0938bc5e7a824e9b2ec625a9640e47316c3ba6f009c1547b8843de0fdb6 +size 4198 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 8e4e600b07..1313bb0c4e 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:e8aa3cabdf151ded5db083bb4a52c8432f8fbee366693430da7b8e326c3421ec -size 4022 +oid sha256:6839f163116fc70f8778369836b352bb89a8a951ea831064829d24cb8953b3dd +size 4216 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 970a032a92..75e5b41560 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cbead6ede5b5ff2c802f0256dac420d9d1f32813f41a83490c992c16a24c1eee -size 4022 +oid sha256:c0ed73362be8dae350d8e44c8a5282e43c3a035ad5825d204267bad2055369f7 +size 4216 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index cce1d62a4f..d719de1585 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:0a7030ae0f4de868e86e2698a94dbe6337357aff3f10c42c695717b9ef26a6bd -size 4020 +oid sha256:b9c6045b0542ce7eeb8b350d67666116e1721c530d42451f163e56d894f325ec +size 4214 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 48ed3ccbee..878bd1a30b 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -763,7 +763,7 @@ def __init__(self, module, person_id, session: int = 1): assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Laser_Pan_Retinal_Coagulation' + self.TREATMENT_ID = 'Dr_Laser_Pan_Retinal_Coagulation_Treatment' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] From f2cc43123ef9acc60f6b0fd22d9a4724f2eea621 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 2 Oct 2025 09:06:36 +0200 Subject: [PATCH 49/85] remove unused variables --- src/tlo/methods/diabetic_retinopathy.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 878bd1a30b..2f20464986 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -457,7 +457,6 @@ def apply(self, population: Population) -> None: diabetes_and_alive_nodr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'none')] diabetes_and_alive_mild_moderate_dr = df.loc[ df.is_alive & df.nc_diabetes & (df.dr_status == 'mild_or_moderate')] - diabetes_and_alive_moderatedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'moderate')] diabetes_and_alive_severedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'severe')] will_progress = self.module.lm['onset_mild_or_moderate_dr'].predict(diabetes_and_alive_nodr, self.module.rng) @@ -672,7 +671,7 @@ def apply(self, person_id, squeeze_factor): data=f'This is HSI_Dr_Focal_Laser: initiating laser treatment for person {person_id}') df = self.sim.population.props person = df.loc[person_id] - hs = self.sim.modules["HealthSystem"] + # hs = self.sim.modules["HealthSystem"] if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint From b586bfc57f9cb7fa2c4bad290f16ad9f36a1f313 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 2 Oct 2025 09:18:11 +0200 Subject: [PATCH 50/85] add session --- src/tlo/methods/diabetic_retinopathy.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 2f20464986..71d50ff3dd 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -766,6 +766,7 @@ def __init__(self, module, person_id, session: int = 1): self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] + self.session = int(session) def apply(self, person_id, squeeze_factor): logger.debug(key='debug', From f8e9e26f6b63df5cdc0864d7a61ce4c4e3fb5456 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 6 Oct 2025 09:44:17 +0200 Subject: [PATCH 51/85] change comment in laser pan retinal coagulation --- src/tlo/methods/diabetic_retinopathy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 71d50ff3dd..988b958e4b 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -797,7 +797,7 @@ def apply(self, person_id, squeeze_factor): priority=0 ) elif self.session == 2: - # completing treatment + # should complete treatment?? df.at[person_id, 'dr_on_treatment'] = False # schedule follow-up at 2 months From 75cd2c7ae4d30b3560c40e8f870c06b7d3701c29 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 9 Oct 2025 09:24:14 +0200 Subject: [PATCH 52/85] remove generic first appointment --- src/tlo/methods/diabetic_retinopathy.py | 26 +------------------------ 1 file changed, 1 insertion(+), 25 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 988b958e4b..1fa0f004a0 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -530,31 +530,7 @@ def do_at_generic_first_appt( schedule_hsi_event: HSIEventScheduler, **kwargs, ) -> None: - - # get the clinical states - dr_stage = individual_properties['dr_status'] - - # No interventions if well - if dr_stage == 'none': - return - - elif dr_stage == 'mild_or_moderate': - # schedule HSI for mild_or_moderate - self.sim.modules["HealthSystem"].schedule_hsi_event( - hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( - person_id=person_id, - module=self.sim.modules["CardioMetabolicDisorders"], - condition='diabetes', - ), - priority=0, - topen=self.sim.date - ) - - elif dr_stage == 'severe' or dr_stage == 'proliferative': - # Intervention for severe and proliferative - schedule_hsi_event( - hsi_event=HSI_Dr_AntiVEGF(module=self, person_id=person_id), - priority=0, topen=self.sim.date) + pass class HSI_Dr_Eye_Examination(HSI_Event, IndividualScopeEventMixin): From 6a59ff7ec4c74703a67117ac5399e6e1acf7450a Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 30 Oct 2025 13:54:52 +0200 Subject: [PATCH 53/85] remove unused params and symbols. Partially populate resource file --- .../Parameter_values.csv | 4 +-- .../ResourceFile_Master_Facilities_List.csv | 4 +-- src/tlo/methods/diabetic_retinopathy.py | 25 +++---------------- 3 files changed, 8 insertions(+), 25 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index b693705694..05b2520bcb 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:75b53759d6d906a447a56effe9abcf74fe1453a521c10f824d9b42663d2dce12 -size 91 +oid sha256:0aef4e655b0bdf776b07b3dac1cb97d9325fe94c166f0c1533f9519cdfee96bb +size 487 diff --git a/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv b/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv index 5ebedf3aab..24fc0a6479 100644 --- a/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv +++ b/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:c6df4a42409b22d0b10d56ec077f6f4b5ccbed0f16f570fedbfd397e100063a9 -size 8471 +oid sha256:f1d83661fedc6c9b4baa299a43b220756f352489fe04b90cca23e43675c722af +size 590 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 1fa0f004a0..edc6a20cb9 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -40,9 +40,6 @@ class DiabeticRetinopathy(Module): "rate_severe_to_proliferative": Parameter(Types.REAL, "Probability of people who get diagnosed with " "proliferative diabetic retinopathy"), - 'prob_fast_dr': Parameter(Types.REAL, - "Probability of people who get diagnosed from none phase to " - "proliferative diabetic retinopathy stage"), "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having " @@ -52,9 +49,6 @@ class DiabeticRetinopathy(Module): Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " "with diabetic retinopathy" ), - "prob_reg_eye_exam": Parameter( - Types.REAL, "Probability of people with Diabetes Mellitus selected for regular eye exam" - ), "rp_dr_tobacco": Parameter( Types.REAL, "relative prevalence at baseline of diabetic retinopathy if tobacco" ), @@ -78,9 +72,6 @@ class DiabeticRetinopathy(Module): Types.REAL, "Probability that people with mild DR and controlled diabetes regress to 'none'" ), - 'effectiveness_of_laser_photocoagulation_in_severe_regression': Parameter( - Types.REAL, - 'Probability of severe diabetic retinopathy regressing to moderate.'), "probs_for_dmo_when_dr_status_mild_or_moderate": Parameter( Types.LIST, "probability of having a DMO state when an individual has non-proliferative mild/moderate " "Diabetic Retinopathy "), @@ -162,9 +153,8 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['rate_severe_to_proliferative'] = 0.07 - self.parameters['prob_fast_dr'] = 0.5 self.parameters['init_prob_any_dr'] = [0.4, 0.3, 0.3] - self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] + self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] # not in resourcefile self.parameters['probs_for_dmo_when_dr_status_mild_or_moderate'] = [0.7, 0.1, 0.2] self.parameters['probs_for_dmo_when_dr_status_severe'] = [0.3, 0.5, 0.2] @@ -172,12 +162,10 @@ def read_parameters(self, data_folder: str | Path) -> None: # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] # self.parameters['init_prob_proliferative_dr'] = 0.09 - self.parameters['p_medication'] = 0.8 - self.parameters['effectiveness_of_laser_photocoagulation_in_severe_regression'] = 0.21 - self.parameters["prob_diabetes_controlled"] = 0.5 + self.parameters['p_medication'] = 0.8 # not in resourcefile + self.parameters["prob_diabetes_controlled"] = 0.5 # not in resource file self.parameters["prob_eye_exam"] = 0.07 - self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 - self.parameters['prob_reg_eye_exam'] = 0.05 + self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 # not in resource file self.parameters['prob_repeat_laser'] = 0.3 self.parameters['rp_dr_ex_alc'] = 1.1 @@ -186,11 +174,6 @@ def read_parameters(self, data_folder: str | Path) -> None: self.parameters['rp_dr_low_ex'] = 1.3 self.parameters['rp_dr_urban'] = 1.4 - self.sim.modules['SymptomManager'].register_symptom( - Symptom(name='blindness_partial'), - Symptom(name='blindness_full') - ) - def initialise_population(self, population: Population) -> None: """ Set property values for the initial population From fd25bb3939604b428a4785c5836048a1346ae3cf Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 31 Oct 2025 15:38:10 +0200 Subject: [PATCH 54/85] call csmo HSIs --- .../ResourceFile_Master_Facilities_List.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 81 +++++++++++++------ tests/test_diabetic_retinopathy.py | 4 - 3 files changed, 59 insertions(+), 30 deletions(-) diff --git a/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv b/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv index 24fc0a6479..5ebedf3aab 100644 --- a/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv +++ b/resources/healthsystem/organisation/ResourceFile_Master_Facilities_List.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:f1d83661fedc6c9b4baa299a43b220756f352489fe04b90cca23e43675c722af -size 590 +oid sha256:c6df4a42409b22d0b10d56ec077f6f4b5ccbed0f16f570fedbfd397e100063a9 +size 8471 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index edc6a20cb9..fc47283df7 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -108,6 +108,13 @@ class DiabeticRetinopathy(Module): Types.DATE, "date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)" ), + "dmo_on_treatment": Property( + Types.BOOL, "Whether this person is on diabetic macular oedema treatment", + ), + "dmo_date_treatment": Property( + Types.DATE, + "date of first receiving diabetic macular oedema treatment (pd.NaT if never started treatment)" + ), "dr_stage_at_which_treatment_given": Property( Types.CATEGORICAL, "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", @@ -134,6 +141,10 @@ class DiabeticRetinopathy(Module): "selected_for_eye_exam": Property( Types.BOOL, "selected for via this period" ), + "dmo_antivegf_count": Property( + Types.INT, + "Number of anti-VEGF injections received in the current treatment cycle", + ), } def __init__(self): @@ -201,11 +212,14 @@ def initialise_population(self, population: Population) -> None: df.loc[df.is_alive & ~df.nc_diabetes, 'dmo_status'] = 'none' df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False + df.loc[list(alive_diabetes_idx), "dmo_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False df.loc[list(alive_diabetes_idx), "selected_for_eye_exam"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dmo_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dmo_antivegf_count"] = 0 # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -307,10 +321,13 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dmo_status'] = 'none' self.sim.population.props.at[child_id, 'dr_on_treatment'] = False self.sim.population.props.at[child_id, 'dr_date_treatment'] = pd.NaT + self.sim.population.props.at[child_id, 'dmo_on_treatment'] = False + self.sim.population.props.at[child_id, 'dmo_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_stage_at_which_treatment_given'] = 'none' self.sim.population.props.at[child_id, 'dr_diagnosed'] = False self.sim.population.props.at[child_id, 'selected_for_eye_exam'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT + self.sim.population.props.at[child_id, "dmo_antivegf_count"] = 0 def on_simulation_end(self) -> None: pass @@ -564,7 +581,7 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Silt lamp', 'Optical coherence tomography device', 'Ophthalmoscope/Fundus camera', 'Amsler grid'}) - if person.dr_status == 'mild_or_moderate': + if person.dr_status == 'mild_or_moderate' or person.dmo_status == 'non_clinically_significant': # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication # and repeat HSI_DR_Eye_Examination in 1 year self.sim.modules["HealthSystem"].schedule_hsi_event( @@ -577,7 +594,7 @@ def apply(self, person_id, squeeze_factor): topen=self.sim.date ) - # repeat eye exam in 1 year + # Repeat eye exam in 1 year if dr_status is mild_or_moderate or dmo_status is non_clinically_significant next_exam_if_mild_or_moderate = self.sim.date + pd.DateOffset(years=1) self.sim.modules['HealthSystem'].schedule_hsi_event(self, topen=next_exam_if_mild_or_moderate, @@ -611,6 +628,15 @@ def apply(self, person_id, squeeze_factor): priority=0 ) + if person.dmo_status == "clinically_significant" and person.dr_status != "none": + # Randomise between AntiVEGF or Focal Laser + treatment_for_cs_dmo = HSI_Dr_AntiVEGF if self.module.rng.random_sample() < 0.5 else HSI_Dr_Focal_Laser + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), + topen=self.sim.date, + priority=0 + ) + class HSI_Dr_Focal_Laser(HSI_Event, IndividualScopeEventMixin): """This is the Laser treatment for individuals with CSMO.""" @@ -620,7 +646,7 @@ def __init__(self, module, person_id): assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Focal_Laser_Treatment' + self.TREATMENT_ID = 'Dr_Focal_Laser_Treatment' #todo change to Dr_Dmo_Focal_Laser_Treatment self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] @@ -648,14 +674,19 @@ def apply(self, person_id, squeeze_factor): if is_cons_available: # record date of diagnosis - df.at[person_id, 'dr_date_diagnosis'] = self.sim.date - df.at[person_id, 'dr_date_treatment'] = self.sim.date - df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] + df.at[person_id, 'dmo_date_treatment'] = self.sim.date + df.at[person_id, 'dmo_on_treatment'] = True + # df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] # If consumables are available, add equipment used and run dx_test self.add_equipment({'Ophthalmic Laser System', 'Laser Delivery System', 'Contact lenses'}) - if person.dr_status == 'severe': - pass + # Schedule follow-up checkup after 3 months #todo add chance that person needs after 3 months + follow_up_date = self.sim.date + pd.DateOffset(months=3) + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + topen=follow_up_date, + priority=1 + ) class HSI_Dr_AntiVEGF(HSI_Event, IndividualScopeEventMixin): @@ -666,7 +697,7 @@ def __init__(self, module, person_id): assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_AntiVEGF_Treatment' + self.TREATMENT_ID = 'Dr_AntiVEGF_Treatment' #todo change to Dr_Dmo_AntiVEGF_Treatment self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] @@ -682,7 +713,7 @@ def apply(self, person_id, squeeze_factor): # The person is not alive, the event did not happen: so return a blank footprint return self.sim.modules['HealthSystem'].get_blank_appt_footprint() - # if person already on treatment or not yet diagnosed, do nothing + # If person already on treatment or not yet diagnosed, do nothing if person["dr_on_treatment"] or not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() @@ -693,21 +724,23 @@ def apply(self, person_id, squeeze_factor): if is_cons_available: self.add_equipment({'Silt lamp', 'Optical coherence tomography device', 'Ophthalmoscope/Fundus camera', 'Goniometre'}) - if person.dr_status == "severe": - hs.schedule_hsi_event( - hsi_event=HSI_Dr_AntiVEGF(module=self.module, person_id=person_id), - topen=self.sim.date + DateOffset(months=3), - tclose=None, - priority=0 - ) - elif person.dr_status == 'proliferative': - hs.schedule_hsi_event( - hsi_event=HSI_Dr_AntiVEGF(module=self.module, person_id=person_id), - topen=self.sim.date + DateOffset(months=1), - tclose=None, - priority=0 - ) + df.at[person_id, 'dmo_date_treatment'] = self.sim.date + df.at[person_id, 'dmo_on_treatment'] = True + # Increment the injection count + df.at[person_id, 'dmo_antivegf_count'] = df.at[person_id, 'dmo_antivegf_count'] + 1 + + # Check if more injections are needed. Must not exceed 8 + if df.at[person_id, 'dmo_antivegf_count'] < 8: + next_session = self.sim.date + pd.DateOffset(months=1) + self.sim.modules['HealthSystem'].schedule_hsi_event(self, + topen=next_session, + priority=0 + ) + else: + # Reset individual injections after getting 8 of them + df.at[person_id, 'dmo_antivegf_count'] = 0 + df.at[person_id, 'dmo_on_treatment'] = False class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index 0839b9eccf..ac2d2a31e1 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -153,10 +153,6 @@ def check_configuration_of_population(sim): assert pd.isnull(df.loc[df.dr_status == 'none', 'dr_date_diagnosis']).all() assert pd.isnull(df.loc[df.dr_status == 'none', 'dr_date_treatment']).all() - # check that those with symptoms are a subset of those with diabetic retinopathy: - assert set(sim.modules['SymptomManager'].who_has('blindness_full')).issubset(df.index[df.dr_status != 'none']) - assert set(sim.modules['SymptomManager'].who_has('blindness_partial')).issubset(df.index[df.dr_status != 'none']) - # check that those diagnosed are a subset of those with any dr (and that the date makes sense): assert set(df.index[~pd.isnull(df.dr_date_diagnosis)]).issubset(df.index[df.dr_status_any_stage]) From c846cfd1bfba05e47b82b59785ec9f4b7bde4300 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 19 Nov 2025 14:24:27 +0200 Subject: [PATCH 55/85] Equipment and consumables --- ...rceFile_Consumables_Items_and_Packages.csv | 4 +-- .../ResourceFile_EquipmentCatalogue.csv | 4 +-- ...eFile_Equipment_Availability_Estimates.csv | 4 +-- src/tlo/methods/diabetic_retinopathy.py | 36 ++++++++++--------- 4 files changed, 26 insertions(+), 22 deletions(-) diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index e66c0e4ebd..bb997ed79f 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:765dde474bad381f74598517e646fa7fa26b619211c442b142395c347cf1883a -size 247029 +oid sha256:4a22b8c621740bba4464a9668d9f56f8916f6f350ac4494d652e162893413f43 +size 247136 diff --git a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_EquipmentCatalogue.csv b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_EquipmentCatalogue.csv index 0442cc00a6..2bd6aa6739 100644 --- a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_EquipmentCatalogue.csv +++ b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_EquipmentCatalogue.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:eba56688a2bd31802340feffdacf337522c494fa0e7e5b6fbc7f3ee171a79a2c -size 38006 +oid sha256:1a336247ac385a6a505a06d63615348a30a2429ea57cd68cb008721da7909bb2 +size 38942 diff --git a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv index 706297da67..fac68c47e2 100644 --- a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv +++ b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:2785365d20a4da4c147ba6a5df9e0259c9076df0fec556086aea0f2a068c9c53 -size 1313098 +oid sha256:7b63fa186d7be667e3e5d31d90846629cb259ada822175767cef230bcd3b08c6 +size 1316917 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index fc47283df7..5c20a1190c 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -10,7 +10,7 @@ from tlo.methods import Metadata, cardio_metabolic_disorders from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler -from tlo.methods.symptommanager import Symptom +# from tlo.methods.symptommanager import Symptom from tlo.population import IndividualProperties logger = logging.getLogger(__name__) @@ -363,26 +363,28 @@ def look_up_consumable_item_codes(self): self.cons_item_codes['laser_pan_retinal_photocoagulation'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, - get_item_codes("Ophthalmic gel, 15ml"): 1, - get_item_codes('Gloves, exam, latex, disposable, pair'): 4 + get_item_codes("Methylcellulose"): 1, + get_item_codes('Alcohol wipes for lens'): 4 } self.cons_item_codes['anti_vegf_injection'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes('Aflibercept, 2mg'): 3, get_item_codes("Antiseptic solution, 15ml"): 1, - get_item_codes("Sterile syringe"): 1 + get_item_codes("Syringe"): 1, + get_item_codes("30G needle"): 1, + get_item_codes("Speculum"): 1, + get_item_codes("Sterile gloves and drapes"): 1 } self.cons_item_codes['focal_laser'] = { get_item_codes("Anesthetic Eye drops, 15ml"): 1, - get_item_codes('Aflibercept, 2mg'): 3, - get_item_codes('Sterile drapes and supplies'): 3, - get_item_codes('Diagnostic dye'): 1 + get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, + get_item_codes("Methylcellulose"): 1, + get_item_codes('Alcohol wipes for lens'): 4 } self.cons_item_codes['eye_examination'] = { - get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1, - get_item_codes('Fluorescin dye'): 1 + get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1 } def do_recovery(self, idx: Union[list, pd.Index]): @@ -578,8 +580,8 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dr_date_treatment'] = self.sim.date df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] # If consumables are available, add equipment used - self.add_equipment({'Silt lamp', 'Optical coherence tomography device', - 'Ophthalmoscope/Fundus camera', 'Amsler grid'}) + self.add_equipment({'Visual acuity chart', 'Direct ophthalmoscope', + 'Fundus camera'}) if person.dr_status == 'mild_or_moderate' or person.dmo_status == 'non_clinically_significant': # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication @@ -678,7 +680,8 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dmo_on_treatment'] = True # df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] # If consumables are available, add equipment used and run dx_test - self.add_equipment({'Ophthalmic Laser System', 'Laser Delivery System', 'Contact lenses'}) + self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', + 'Silt lamp laser delivery system', 'Laser macular contact lens'}) # Schedule follow-up checkup after 3 months #todo add chance that person needs after 3 months follow_up_date = self.sim.date + pd.DateOffset(months=3) @@ -707,7 +710,6 @@ def apply(self, person_id, squeeze_factor): data=f'This is HSI_Dr_AntiVEGF for person {person_id}') df = self.sim.population.props person = df.loc[person_id] - hs = self.sim.modules["HealthSystem"] if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint @@ -722,8 +724,8 @@ def apply(self, person_id, squeeze_factor): ) if is_cons_available: - self.add_equipment({'Silt lamp', 'Optical coherence tomography device', - 'Ophthalmoscope/Fundus camera', 'Goniometre'}) + self.add_equipment({'Visual acuity chart', 'Silt lamp', 'Optical coherence tomography device', + 'Fundus camera', 'Tonometre'}) df.at[person_id, 'dmo_date_treatment'] = self.sim.date df.at[person_id, 'dmo_on_treatment'] = True @@ -780,7 +782,9 @@ def apply(self, person_id, squeeze_factor): ) if is_cons_available: - self.add_equipment({'Laser generator', 'Delivery system', 'Contact lenses', 'Patient head support'}) + self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', + 'Silt lamp laser delivery system', + 'Indirect laser delivery system', 'Laser wide-field contact lens'}) if self.session == 1: # schedule the second session in 1 week hs.schedule_hsi_event( From aa9b9e1733e6072246453965d9f32499db841a27 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 19 Nov 2025 18:07:26 +0200 Subject: [PATCH 56/85] Fix errors from merge --- .../ResourceFile_Oesophageal_Cancer/parameter_values.csv | 2 -- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 6 ++---- .../ClinicallyVulnerable.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 6 ++---- .../Test Mode 1.csv | 6 ++---- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 6 ++---- .../VerticalProgrammes.csv | 6 ++---- src/tlo/methods/diabetic_retinopathy.py | 1 - 12 files changed, 20 insertions(+), 43 deletions(-) diff --git a/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv b/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv index 5323f3e5c6..5d4826c6d8 100644 --- a/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv +++ b/resources/ResourceFile_Oesophageal_Cancer/parameter_values.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:332e44d101a5263a41eadcceee8bc0eeafc38d23aa45fe9fd6abed7a06aeed0b -size 1337 oid sha256:301410240d73130ed7cdcb2da8d51aed0a95a0c935a8c87eec193e9ea34f795e size 2961 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 92316f6a26..df31b95ee6 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:4ce883ae9769e1c2c331845d67170c1de3d32e323bceb5f9c2ff37179c0e6878 -size 4214 -oid sha256:be19c64d84ed49ae79be28f6a8e7abb8e279f7cb441ee90d934753731c708e12 -size 4138 +oid sha256:31aa68261f3dc79c327cb7f708563357df874105ae6730aed0646e4426ca9a1d +size 4394 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index d7de63e3c4..d0a0826e9b 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:2ddbc979dddb7cacec5f60532d5b5467a8b126ef4d4fbe03796632b64ed3f395 -size 3834 -oid sha256:824c5882bf4f320e58e7cff622fd5abf5c2b581fd3ed4f2df2d8a2f919509cfd -size 3742 +oid sha256:6f346dbc8373f9a8c26f80d73ab33a1337d14205d0a8137cdbac04c51c630900 +size 3998 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 4858314274..6db23372ac 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cacc6054bccf8a69edfbf5b91f5e472782f36040c1ba6c272fd4fc5afbc0a64a -size 4216 -oid sha256:6b87874bafc8f792822ef1962070c62aead74992e7856a7ca749a05b340eb20a -size 4140 +oid sha256:690f3b6408653e673ebb408f822a9c0659159d09847cadbbf705c69e557d47aa +size 4396 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 4466c40a46..0b4f2ee2d0 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:ac0c14ecb2a7cf10cbff37b369e0d1a2e29262948087f24a0007ec347c147e4d -size 4215 -oid sha256:f97a75bf186809ed5edc41f4542e61bf5ebefb131d7617bbccd74ef5b5a4f33b -size 4139 +oid sha256:db7529d58f1d938783079b035eeaa9086e86d5d2ac00c3a7a03ec67da8e57672 +size 4395 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index b43ab99d02..7d894413b2 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:3752aabe855f3ab95eede3db26c0bbe1b009b82dc8bce156f42171300304462c -size 4214 -oid sha256:50502e603cb50e6ea00f6df494b4f0cd39f216ce1dffff93ad9d136cd4592c50 -size 4138 +oid sha256:e249f587f2d62f9f06c487eb02c3b829aeb06fb65de9ea4c93a51771ece914ff +size 4394 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index 2fb39c1a7c..d8f395d4ea 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:dcec4d189fa700d7b16fa99ce5cd1eacc50c377eb70d9ff5ffd1bd7ea066c7d5 -size 4214 -oid sha256:c914b33a927d488ff650e7a39a1ba8e7b965c8cda73348595e74c2bb2a5fcf89 -size 4138 +oid sha256:8be9ec7e5ab72be9da085a53059231e90404b113721db3aeac06fd2df3e50be7 +size 4394 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 2d457a7a57..c77ff033b5 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:0e60f0938bc5e7a824e9b2ec625a9640e47316c3ba6f009c1547b8843de0fdb6 -size 4198 -oid sha256:838b3ccc7b5882631ae455634aa8d034065a928a63f5ecd412176556738e20b9 -size 4118 +oid sha256:016d78db3a4f34f02b6e9c29bf53f4ea4e5b8ae3332cec0e6f285fd3a3cbdc3b +size 4374 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 5619c0e5bb..0804d62946 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:6839f163116fc70f8778369836b352bb89a8a951ea831064829d24cb8953b3dd -size 4216 -oid sha256:38a678d31cacc4cff04f54d9a916cd5ff2f5f76641ac7bad316087056b8df16c -size 4140 +oid sha256:503573b8ff49a2fc3661926e9957db8683a4a9e9bef9080ba8f66eabb2f1ce79 +size 4396 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 2e7a95eb10..98b28ab04e 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:c0ed73362be8dae350d8e44c8a5282e43c3a035ad5825d204267bad2055369f7 -size 4216 -oid sha256:4645d100a2b19ca1b50888d2233f7752d360763eb53ec9e61e4355c411b5f18d -size 4140 +oid sha256:856106bed7be6dfbf8b753d355f5ec78cf2b002de5748223cd051b3615e3e713 +size 4396 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 8b3a61c7d7..5a18b99f41 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,5 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:b9c6045b0542ce7eeb8b350d67666116e1721c530d42451f163e56d894f325ec -size 4214 -oid sha256:191d303273c80fa7a1fe59488b5c63e718b9f92911ab45f70ada1c98db06e086 -size 4138 +oid sha256:c461f5e8b20aee5ebd578a97069751b292922ee2d5905b30a17356c08bd9c849 +size 4394 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 5c20a1190c..633de4d996 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -10,7 +10,6 @@ from tlo.methods import Metadata, cardio_metabolic_disorders from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler -# from tlo.methods.symptommanager import Symptom from tlo.population import IndividualProperties logger = logging.getLogger(__name__) From 474566b2054d087c52740e1d597dea988ac88f1c Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 4 Dec 2025 17:01:42 +0200 Subject: [PATCH 57/85] parameters use csv --- .../Parameter_values.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 100 +++++++----------- 2 files changed, 38 insertions(+), 66 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index 05b2520bcb..1389df6c44 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:0aef4e655b0bdf776b07b3dac1cb97d9325fe94c166f0c1533f9519cdfee96bb -size 487 +oid sha256:744bbd57eb13b311f6f833326761bbaeb6f723f73cda7d96d86b6682a0af395b +size 985 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 633de4d996..89f4a23362 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,5 +1,5 @@ from pathlib import Path -from typing import Union +from typing import Union, Optional import numpy as np import pandas as pd @@ -11,6 +11,7 @@ from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.population import IndividualProperties +from tlo.util import read_csv_files logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -43,11 +44,7 @@ class DiabeticRetinopathy(Module): "init_prob_any_dr": Parameter(Types.LIST, "Initial probability of anyone with diabetic retinopathy"), "prob_any_dmo": Parameter(Types.LIST, "Probability of anyone with diabetic retinopathy having " "Diabetic Macular Oedema (DMO)"), - "p_medication": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), - "init_prob_ever_diet_mgmt_if_diagnosed": Parameter( - Types.REAL, "Initial probability of ever having had a diet management session if ever diagnosed " - "with diabetic retinopathy" - ), + "p_laser_success": Parameter(Types.REAL, "Diabetic retinopathy treatment/medication effectiveness"), "rp_dr_tobacco": Parameter( Types.REAL, "relative prevalence at baseline of diabetic retinopathy if tobacco" ), @@ -150,39 +147,12 @@ def __init__(self): super().__init__() self.cons_item_codes = None # (Will store consumable item codes) - def read_parameters(self, data_folder: str | Path) -> None: - """ initialise module parameters. Here we are assigning values to all parameters defined at the beginning of - this module. - - :param data_folder: Path to the folder containing parameter values - - """ - #TODO Read from resourcefile - self.parameters['rate_onset_to_mild_or_moderate_dr'] = 0.29 - self.parameters['rate_mild_or_moderate_to_severe'] = 0.5 - - self.parameters['rate_severe_to_proliferative'] = 0.07 - - self.parameters['init_prob_any_dr'] = [0.4, 0.3, 0.3] - self.parameters['prob_any_dmo'] = [0.1, 0.2, 0.3, 0.4] # not in resourcefile - - self.parameters['probs_for_dmo_when_dr_status_mild_or_moderate'] = [0.7, 0.1, 0.2] - self.parameters['probs_for_dmo_when_dr_status_severe'] = [0.3, 0.5, 0.2] - self.parameters['probs_for_dmo_when_dr_status_proliferative'] = [0.1, 0.7, 0.2] - - # self.parameters['init_prob_any_dr'] = [0.2, 0.3, 0.3, 0.15, 0.05] - # self.parameters['init_prob_proliferative_dr'] = 0.09 - self.parameters['p_medication'] = 0.8 # not in resourcefile - self.parameters["prob_diabetes_controlled"] = 0.5 # not in resource file - self.parameters["prob_eye_exam"] = 0.07 - self.parameters["prob_mild_to_none_if_controlled_diabetes"] = 0.21 # not in resource file - self.parameters['prob_repeat_laser'] = 0.3 - - self.parameters['rp_dr_ex_alc'] = 1.1 - self.parameters['rp_dr_tobacco'] = 1.3 - self.parameters['rp_dr_high_sugar'] = 1.2 - self.parameters['rp_dr_low_ex'] = 1.3 - self.parameters['rp_dr_urban'] = 1.4 + def read_parameters(self, resourcefilepath: Optional[Path]=None): + """ Read all parameters and define symptoms (if any)""" + self.load_parameters_from_dataframe( + read_csv_files(resourcefilepath / "ResourceFile_Diabetic_Retinopathy", + files="parameter_values") + ) def initialise_population(self, population: Population) -> None: """ Set property values for the initial population @@ -191,17 +161,17 @@ def initialise_population(self, population: Population) -> None: """ df = population.props - # p = self.parameters + p = self.parameters alive_diabetes_idx = df.loc[df.is_alive & df.nc_diabetes].index # any_dr_idx = alive_diabetes_idx[ - # self.rng.random_sample(size=len(alive_diabetes_idx)) < self.parameters['init_prob_any_dr'] + # self.rng.random_sample(size=len(alive_diabetes_idx)) < p['init_prob_any_dr'] # ] # no_dr_idx = set(alive_diabetes_idx) - set(any_dr_idx) # # proliferative_dr_idx = any_dr_idx[ - # self.rng.random_sample(size=len(any_dr_idx)) < self.parameters['init_prob_proliferative_dr'] + # self.rng.random_sample(size=len(any_dr_idx)) < p['init_prob_proliferative_dr'] # ] # # mild_dr_idx = set(any_dr_idx) - set(proliferative_dr_idx) @@ -223,16 +193,16 @@ def initialise_population(self, population: Population) -> None: # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: # check parameters are sensible: probability of having any cancer stage cannot exceed 1.0 - assert sum(self.parameters['init_prob_any_dr']) <= 1.0 + assert sum(p['init_prob_any_dr']) <= 1.0 lm_init_dr_status_any_dr = LinearModel( LinearModelType.MULTIPLICATIVE, - sum(self.parameters['init_prob_any_dr']), - Predictor('li_ex_alc').when(True, self.parameters['rp_dr_ex_alc']), - Predictor('li_tob').when(True, self.parameters['rp_dr_tobacco']), - Predictor('li_high_sugar').when(True, self.parameters['rp_dr_high_sugar']), - Predictor('li_low_ex').when(True, self.parameters['rp_dr_low_ex']), - Predictor('li_urban').when(True, self.parameters['rp_dr_urban']), + sum(p['init_prob_any_dr']), + Predictor('li_ex_alc').when(True, p['rp_dr_ex_alc']), + Predictor('li_tob').when(True, p['rp_dr_tobacco']), + Predictor('li_high_sugar').when(True, p['rp_dr_high_sugar']), + Predictor('li_low_ex').when(True, p['rp_dr_low_ex']), + Predictor('li_urban').when(True, p['rp_dr_urban']), ) # any_dr = \ @@ -249,11 +219,11 @@ def initialise_population(self, population: Population) -> None: categories = [cat for cat in df.dr_status.cat.categories if cat != 'none'] # Verify probabilities match categories - assert len(categories) == len(self.parameters['init_prob_any_dr']) + assert len(categories) == len(p['init_prob_any_dr']) # Normalize probabilities - total_prob = sum(self.parameters['init_prob_any_dr']) - probs = [p / total_prob for p in self.parameters['init_prob_any_dr']] + total_prob = sum(p['init_prob_any_dr']) + probs = [p / total_prob for p in p['init_prob_any_dr']] # Assign DR stages df.loc[dr_idx, 'dr_status'] = self.rng.choice( @@ -262,17 +232,17 @@ def initialise_population(self, population: Population) -> None: p=probs ) - # dr_stage_probs = self.parameters["init_prob_any_dr"] + # dr_stage_probs = p["init_prob_any_dr"] # Determine the stage of DR for those who have DM: # if any_dr.sum(): # categories = [cat for cat in df.dr_status.cat.categories if cat != 'none'] # # # Make sure we have the right number of probabilities - # assert len(categories) == len(self.parameters['init_prob_any_dr']) + # assert len(categories) == len(p['init_prob_any_dr']) # # # Normalize probabilities - # sum_probs = sum(self.parameters['init_prob_any_dr']) - # prob_by_stage_of_dr_if_dr = [p / sum_probs for p in self.parameters['init_prob_any_dr']] + # sum_probs = sum(p['init_prob_any_dr']) + # prob_by_stage_of_dr_if_dr = [p / sum_probs for p in p['init_prob_any_dr']] # # # Assign statuses # df.loc[any_dr, "dr_status"] = self.rng.choice( @@ -281,9 +251,9 @@ def initialise_population(self, population: Population) -> None: # p=prob_by_stage_of_dr_if_dr # ) - # sum_probs = sum(self.parameters['init_prob_any_dr']) + # sum_probs = sum(p['init_prob_any_dr']) # if sum_probs > 0: - # prob_by_stage_of_dr_if_dr = [i / sum_probs for i in self.parameters['init_prob_any_dr']] + # prob_by_stage_of_dr_if_dr = [i / sum_probs for i in p['init_prob_any_dr']] # assert (sum(prob_by_stage_of_dr_if_dr) - 1.0) < 1e-10 # # df.loc[any_dr, "dr_status"] = self.rng.choice( # # dr_stage_probs[1:], # exclude "none" @@ -334,22 +304,23 @@ def on_simulation_end(self) -> None: def make_the_linear_models(self) -> None: """Make and save LinearModels that will be used when the module is running""" self.lm = dict() + p =self.parameters self.lm['onset_mild_or_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=self.parameters['rate_onset_to_mild_or_moderate_dr'] + intercept=p['rate_onset_to_mild_or_moderate_dr'] ) self.lm['mildmoderate_severe_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - self.parameters['rate_mild_or_moderate_to_severe'], + p['rate_mild_or_moderate_to_severe'], Predictor('had_treatment_during_this_stage', external=True) .when(True, 0.0).otherwise(1.0) ) self.lm['severe_proliferative_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - self.parameters['rate_severe_to_proliferative'], + p['rate_severe_to_proliferative'], Predictor('had_treatment_during_this_stage', external=True) .when(True, 0.0).otherwise(1.0) ) @@ -406,6 +377,7 @@ def update_dmo_status(self): """Update DMO status for people with diabetic retinopathy. Ensures dmo_status is none when dr_status is none/nan.""" df = self.sim.population.props + p = self.parameters # First reset dmo_status to 'none' for anyone without DR no_dr_mask = (df.dr_status == 'none') | df.dr_status.isna() @@ -420,11 +392,11 @@ def update_dmo_status(self): dr_stage = df.at[person, 'dr_status'] if dr_stage == 'mild_or_moderate': - probs = self.parameters['probs_for_dmo_when_dr_status_mild_or_moderate'] + probs = p['probs_for_dmo_when_dr_status_mild_or_moderate'] elif dr_stage == 'severe': - probs = self.parameters['probs_for_dmo_when_dr_status_severe'] + probs = p['probs_for_dmo_when_dr_status_severe'] elif dr_stage == 'proliferative': - probs = self.parameters['probs_for_dmo_when_dr_status_proliferative'] + probs = p['probs_for_dmo_when_dr_status_proliferative'] df.at[person, 'dmo_status'] = self.rng.choice( ['none', 'clinically_significant', 'non_clinically_significant'], From 0bb709b731570c33e0daa5f4c9e75e4ccba00289 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 4 Dec 2025 17:24:07 +0200 Subject: [PATCH 58/85] changes years in eye exam to params --- .../Parameter_values.csv | 4 ++-- src/tlo/methods/diabetic_retinopathy.py | 13 +++++++++++-- 2 files changed, 13 insertions(+), 4 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index 1389df6c44..4e067b0746 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:744bbd57eb13b311f6f833326761bbaeb6f723f73cda7d96d86b6682a0af395b -size 985 +oid sha256:ffc0f8087b657e304427d33160f8d6196c5294683037eaa7f1e2785c4a504476 +size 1072 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 89f4a23362..9edb0924eb 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -84,6 +84,14 @@ class DiabeticRetinopathy(Module): "Probability that a patient who remains proliferative at follow-up/review will " "require a repeat of HSI_Dr_Laser_Pan_Retinal_Coagulation" ), + "next_exam_if_mild_or_moderate": Parameter( + Types.INT, + "Number of months until next eye exam if DR status is mild or moderate" + ), + "next_exam_if_severe": Parameter( + Types.INT, + "Number of months until next eye exam if DR status is severe" + ), } PROPERTIES = { @@ -525,6 +533,7 @@ def apply(self, person_id, squeeze_factor): df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] + p = self.parameters if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint @@ -568,14 +577,14 @@ def apply(self, person_id, squeeze_factor): ) # Repeat eye exam in 1 year if dr_status is mild_or_moderate or dmo_status is non_clinically_significant - next_exam_if_mild_or_moderate = self.sim.date + pd.DateOffset(years=1) + next_exam_if_mild_or_moderate = self.sim.date + pd.DateOffset(months=p['next_exam_if_mild_or_moderate']) self.sim.modules['HealthSystem'].schedule_hsi_event(self, topen=next_exam_if_mild_or_moderate, tclose=None, priority=1) elif person.dr_status == 'severe': - next_exam_if_severe = self.sim.date + pd.DateOffset(months=3) + next_exam_if_severe = self.sim.date + pd.DateOffset(months=p['next_exam_if_severe']) self.sim.modules['HealthSystem'].schedule_hsi_event(self, topen=next_exam_if_severe, tclose=None, From 6657544d2b99316652dfd306d7d7f1edfa7fb0cb Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 9 Dec 2025 15:59:56 +0200 Subject: [PATCH 59/85] . --- .../clinics/ResourceFile_ClinicConfigurations/Default.csv | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/resources/healthsystem/human_resources/clinics/ResourceFile_ClinicConfigurations/Default.csv b/resources/healthsystem/human_resources/clinics/ResourceFile_ClinicConfigurations/Default.csv index 88c9a3cb73..871f162935 100644 --- a/resources/healthsystem/human_resources/clinics/ResourceFile_ClinicConfigurations/Default.csv +++ b/resources/healthsystem/human_resources/clinics/ResourceFile_ClinicConfigurations/Default.csv @@ -1 +1,3 @@ -Facility_ID,Officer_Type_Code,GenericClinic +version https://git-lfs.github.com/spec/v1 +oid sha256:cd312903ff50d5233d81075b1f38e7879b8933e3ad7067d52c696e4f37e51eac +size 44 From c81e3a5cc59bca8e9102158d49cf224785b5b8cf Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 11 Dec 2025 13:58:35 +0200 Subject: [PATCH 60/85] reformat --- .../Parameter_values.csv | 4 +- ...rceFile_Consumables_Items_and_Packages.csv | 4 +- .../CVD.csv | 4 +- .../ClinicallyVulnerable.csv | 4 +- .../Default.csv | 4 +- .../EHP_III.csv | 4 +- .../LCOA_EHP.csv | 4 +- .../Naive.csv | 4 +- .../RMNCH.csv | 4 +- .../Test Mode 1.csv | 4 +- .../Test.csv | 4 +- .../VerticalProgrammes.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 116 ++++++++++++------ 13 files changed, 102 insertions(+), 62 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index 4e067b0746..3b56e5e151 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:ffc0f8087b657e304427d33160f8d6196c5294683037eaa7f1e2785c4a504476 -size 1072 +oid sha256:1991729723d679b48d1a4b66dfcbc20742684f672a1400d490dfb6bbdf3fcf16 +size 1087 diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index bb997ed79f..10ec4b7757 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:4a22b8c621740bba4464a9668d9f56f8916f6f350ac4494d652e162893413f43 -size 247136 +oid sha256:515862a8b179bad84002c6206a71d1dc6fee9b42969a50dd32754cabfcbbf535 +size 247101 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index df31b95ee6..216b509334 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:31aa68261f3dc79c327cb7f708563357df874105ae6730aed0646e4426ca9a1d -size 4394 +oid sha256:80b0226548541259fc613b6ddb7c6624d9538904bccdfb51b73d7201ea6d06d9 +size 4406 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index d0a0826e9b..44184eb5e0 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:6f346dbc8373f9a8c26f80d73ab33a1337d14205d0a8137cdbac04c51c630900 -size 3998 +oid sha256:255687d8220598c85dd9294df90037be304fdb0b762fa6126fd16e0b60d32cf1 +size 4010 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index 6db23372ac..897bda57e1 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:690f3b6408653e673ebb408f822a9c0659159d09847cadbbf705c69e557d47aa -size 4396 +oid sha256:e2270ceb566e5899c977795c9c0cc166991458cc1597740f597bc99604cacde3 +size 4408 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index 0b4f2ee2d0..796ac156c9 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:db7529d58f1d938783079b035eeaa9086e86d5d2ac00c3a7a03ec67da8e57672 -size 4395 +oid sha256:281d4c8ff65f6e0d12cf4570f1aac4599fcca3046b87fb72fa9c484b459675a4 +size 4407 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 7d894413b2..fbb6e855cc 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:e249f587f2d62f9f06c487eb02c3b829aeb06fb65de9ea4c93a51771ece914ff -size 4394 +oid sha256:ee98cf5e77f6bd27351a47511e9b3c6d53689149fe4b800cde75043782714cdd +size 4406 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index d8f395d4ea..b0e4c822ae 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:8be9ec7e5ab72be9da085a53059231e90404b113721db3aeac06fd2df3e50be7 -size 4394 +oid sha256:b01d966a3b97042b4de99447a5ce26c067ba65bd560c5f0565c4d257a9653275 +size 4406 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index c77ff033b5..f33a40cfc7 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:016d78db3a4f34f02b6e9c29bf53f4ea4e5b8ae3332cec0e6f285fd3a3cbdc3b -size 4374 +oid sha256:24d668fc9abcdca35a879022dae46e69743a77e79dcd9c20ff0708e36a4ea2ef +size 4386 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 0804d62946..09346a482e 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:503573b8ff49a2fc3661926e9957db8683a4a9e9bef9080ba8f66eabb2f1ce79 -size 4396 +oid sha256:2cea1a96c0d05e34fb93300b1d82ab11a09f5f53c933809e9ab3b2da5fc74bb7 +size 4408 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index 98b28ab04e..6f5c3c3f13 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:856106bed7be6dfbf8b753d355f5ec78cf2b002de5748223cd051b3615e3e713 -size 4396 +oid sha256:6ae5cc8231efc2f8067fbe43f38c327f1ce91f1ad9aeee827d2e7c4c459defef +size 4408 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 5a18b99f41..eae67af418 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:c461f5e8b20aee5ebd578a97069751b292922ee2d5905b30a17356c08bd9c849 -size 4394 +oid sha256:dac2200773fadf5cb355f1c2d73cbafcf1fd8efefb7425692576e6c6f4c92655 +size 4406 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 9edb0924eb..49a6e10858 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -76,7 +76,7 @@ class DiabeticRetinopathy(Module): "probs_for_dmo_when_dr_status_proliferative": Parameter( Types.LIST, "probability of having a DMO state when an individual has " "proliferative Diabetic Retinopathy "), - "prob_eye_exam": Parameter( + "prob_eye_screening": Parameter( Types.REAL, "probability of going for an eye exam/screening" ), "prob_repeat_laser": Parameter( @@ -84,13 +84,13 @@ class DiabeticRetinopathy(Module): "Probability that a patient who remains proliferative at follow-up/review will " "require a repeat of HSI_Dr_Laser_Pan_Retinal_Coagulation" ), - "next_exam_if_mild_or_moderate": Parameter( + "next_screening_if_mild_or_moderate": Parameter( Types.INT, - "Number of months until next eye exam if DR status is mild or moderate" + "Number of months until next eye screening if DR status is mild or moderate" ), - "next_exam_if_severe": Parameter( + "next_screening_if_severe": Parameter( Types.INT, - "Number of months until next eye exam if DR status is severe" + "Number of months until next eye screening if DR status is severe" ), } @@ -142,8 +142,8 @@ class DiabeticRetinopathy(Module): Types.DATE, "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" ), - "selected_for_eye_exam": Property( - Types.BOOL, "selected for via this period" + "selected_for_eye_screening": Property( + Types.BOOL, "selected for screening this period" ), "dmo_antivegf_count": Property( Types.INT, @@ -191,7 +191,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dmo_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False - df.loc[list(alive_diabetes_idx), "selected_for_eye_exam"] = False + df.loc[list(alive_diabetes_idx), "selected_for_eye_screening"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dmo_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" @@ -302,7 +302,7 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'dmo_date_treatment'] = pd.NaT self.sim.population.props.at[child_id, 'dr_stage_at_which_treatment_given'] = 'none' self.sim.population.props.at[child_id, 'dr_diagnosed'] = False - self.sim.population.props.at[child_id, 'selected_for_eye_exam'] = False + self.sim.population.props.at[child_id, 'selected_for_eye_screening'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, "dmo_antivegf_count"] = 0 @@ -348,7 +348,7 @@ def look_up_consumable_item_codes(self): get_item_codes("Anesthetic Eye drops, 15ml"): 1, get_item_codes('Aflibercept, 2mg'): 3, get_item_codes("Antiseptic solution, 15ml"): 1, - get_item_codes("Syringe"): 1, + get_item_codes("Syringe, 5ml, disposable, hypoluer with 21g needle_each_CMST"): 1, get_item_codes("30G needle"): 1, get_item_codes("Speculum"): 1, get_item_codes("Sterile gloves and drapes"): 1 @@ -361,7 +361,7 @@ def look_up_consumable_item_codes(self): get_item_codes('Alcohol wipes for lens'): 4 } - self.cons_item_codes['eye_examination'] = { + self.cons_item_codes['eye_screening'] = { get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1 } @@ -482,9 +482,9 @@ def apply(self, population: Population) -> None: # df.loc[regress_to_none_idx, "dmo_status"] = "none" # ------------------------SELECTING INDIVIDUALS FOR FOR DR OR DMO EYE EXAM/SCREENING--------------------- - df.selected_for_eye_exam = False + df.selected_for_eye_screening = False - eligible_population_for_eye_exam = ( + eligible_population_for_eye_screening = ( (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year (df.dr_status == 'none') & (df.dmo_status == 'none') & @@ -492,14 +492,14 @@ def apply(self, population: Population) -> None: (pd.isna(df.dr_date_diagnosis)) ) - df.loc[eligible_population_for_eye_exam, 'selected_for_eye_exam'] = ( - np.random.random_sample(size=len(df[eligible_population_for_eye_exam])) - < self.module.parameters['prob_eye_exam'] + df.loc[eligible_population_for_eye_screening, 'selected_for_eye_screening'] = ( + np.random.random_sample(size=len(df[eligible_population_for_eye_screening])) + < self.module.parameters['prob_eye_screening'] ) - for idx in df.index[df.selected_for_eye_exam]: + for idx in df.index[df.selected_for_eye_screening]: self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Dr_Eye_Examination(module=self.module, person_id=idx), + hsi_event=HSI_Dr_Dmo_Screening(module=self.module, person_id=idx), priority=0, topen=self.sim.date, tclose=None) @@ -514,22 +514,23 @@ def do_at_generic_first_appt( pass -class HSI_Dr_Eye_Examination(HSI_Event, IndividualScopeEventMixin): - """This is the Eye examination done to individuals selected for screening for individuals with any complication""" +class HSI_Dr_Dmo_Screening(HSI_Event, IndividualScopeEventMixin): + """This is the eye examination/screening done to individuals selected for screening + for individuals with any complication""" def __init__(self, module, person_id): super().__init__(module, person_id=person_id) assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Eye_Examination' + self.TREATMENT_ID = 'Dr_Dmo_Eye_Examination' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): logger.debug(key='debug', - data=f'This is HSI_Dr_Eye_Examination: investigating the condition of {person_id}') + data=f'This is HSI_Dr_Dmo_Screening: investigating the condition of {person_id}') df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] @@ -546,11 +547,11 @@ def apply(self, person_id, squeeze_factor): assert pd.isnull(df.at[person_id, 'dr_date_treatment']) is_cons_available = self.get_consumables( - self.module.cons_item_codes['eye_examination'] + self.module.cons_item_codes['eye_screening'] ) dx_result = hs.dx_manager.run_dx_test( - dx_tests_to_run='dilated_eye_exam_dr', + dx_tests_to_run='dilated_eye_exam_dr_dmo', hsi_event=self ) @@ -565,7 +566,7 @@ def apply(self, person_id, squeeze_factor): if person.dr_status == 'mild_or_moderate' or person.dmo_status == 'non_clinically_significant': # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication - # and repeat HSI_DR_Eye_Examination in 1 year + # and repeat HSI_DR_Dmo_Screening in 1 year self.sim.modules["HealthSystem"].schedule_hsi_event( hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( person_id=person_id, @@ -576,17 +577,19 @@ def apply(self, person_id, squeeze_factor): topen=self.sim.date ) - # Repeat eye exam in 1 year if dr_status is mild_or_moderate or dmo_status is non_clinically_significant - next_exam_if_mild_or_moderate = self.sim.date + pd.DateOffset(months=p['next_exam_if_mild_or_moderate']) + # Repeat eye screening in 1 year if dr_status is mild_or_moderate or dmo_status is + # non_clinically_significant + next_screening_if_mild_or_moderate =\ + self.sim.date + pd.DateOffset(months=p['next_screening_if_mild_or_moderate']) self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_exam_if_mild_or_moderate, + topen=next_screening_if_mild_or_moderate, tclose=None, priority=1) elif person.dr_status == 'severe': - next_exam_if_severe = self.sim.date + pd.DateOffset(months=p['next_exam_if_severe']) + next_screening_if_severe = self.sim.date + pd.DateOffset(months=p['next_screening_if_severe']) self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_exam_if_severe, + topen=next_screening_if_severe, tclose=None, priority=1) @@ -612,7 +615,8 @@ def apply(self, person_id, squeeze_factor): if person.dmo_status == "clinically_significant" and person.dr_status != "none": # Randomise between AntiVEGF or Focal Laser - treatment_for_cs_dmo = HSI_Dr_AntiVEGF if self.module.rng.random_sample() < 0.5 else HSI_Dr_Focal_Laser + treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ + if self.module.rng.random_sample() < 0.5 else HSI_Dr_Dmo_Focal_Laser self.sim.modules['HealthSystem'].schedule_hsi_event( hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), topen=self.sim.date, @@ -620,7 +624,7 @@ def apply(self, person_id, squeeze_factor): ) -class HSI_Dr_Focal_Laser(HSI_Event, IndividualScopeEventMixin): +class HSI_Dr_Dmo_Focal_Laser(HSI_Event, IndividualScopeEventMixin): """This is the Laser treatment for individuals with CSMO.""" def __init__(self, module, person_id): @@ -628,7 +632,7 @@ def __init__(self, module, person_id): assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_Focal_Laser_Treatment' #todo change to Dr_Dmo_Focal_Laser_Treatment + self.TREATMENT_ID = 'Dr_Dmo_Focal_Laser_Treatment' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] @@ -666,13 +670,13 @@ def apply(self, person_id, squeeze_factor): # Schedule follow-up checkup after 3 months #todo add chance that person needs after 3 months follow_up_date = self.sim.date + pd.DateOffset(months=3) self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), topen=follow_up_date, priority=1 ) -class HSI_Dr_AntiVEGF(HSI_Event, IndividualScopeEventMixin): +class HSI_Dr_Dmo_AntiVEGF(HSI_Event, IndividualScopeEventMixin): """This is the Anti-VEGF treatment for individuals with CSMO.""" def __init__(self, module, person_id): @@ -680,7 +684,7 @@ def __init__(self, module, person_id): assert isinstance(module, DiabeticRetinopathy) # Define the necessary information for an HSI - self.TREATMENT_ID = 'Dr_AntiVEGF_Treatment' #todo change to Dr_Dmo_AntiVEGF_Treatment + self.TREATMENT_ID = 'Dr_Dmo_AntiVEGF_Treatment' self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] @@ -725,6 +729,42 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dmo_on_treatment'] = False +class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): + """This is a Health System Interaction Event in which a person receives a dialysis session 2 times a week + adding up to 8 times a month.""" + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + + self.TREATMENT_ID = 'Dr_Laser_Pan_Retinal_Coagulation_Treatment' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) + self.ACCEPTED_FACILITY_LEVEL = '3' + + def apply(self, person_id, squeeze_factor): + + df = self.sim.population.props + person = df.loc[person_id] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + + # if person already on treatment or not yet diagnosed, do nothing + if person["dr_on_treatment"] or not person["dr_diagnosed"]: + return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + + self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', + 'Silt lamp laser delivery system', + 'Indirect laser delivery system', 'Laser wide-field contact lens'}) + + next_session_date = self.sim.date + pd.DateOffset(weeks=1) + self.sim.modules['HealthSystem'].schedule_hsi_event(self, + topen=next_session_date, + tclose=next_session_date + pd.DateOffset(days=3), + priority=1 + ) + + class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): """ This is the HSI event given to individuals with proliferative diabetic retinopathy after undergoing an eye @@ -779,7 +819,7 @@ def apply(self, person_id, squeeze_factor): # schedule follow-up at 2 months follow_up = self.sim.date + pd.DateOffset(months=2) hs.schedule_hsi_event( - hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), topen=follow_up, priority=1 ) @@ -788,7 +828,7 @@ def apply(self, person_id, squeeze_factor): for m in [3, 6, 9, 12]: review_date = self.sim.date + pd.DateOffset(months=m) hs.schedule_hsi_event( - hsi_event=HSI_Dr_Eye_Examination(self.module, person_id), + hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), topen=review_date, priority=1 ) From d7e45262bb8b535fc76c0ebac3558bd21a8c2647 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 12 Dec 2025 09:29:13 +0200 Subject: [PATCH 61/85] Change logic of HSI Laser PRC --- src/tlo/methods/diabetic_retinopathy.py | 123 ++++++++++-------------- 1 file changed, 50 insertions(+), 73 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 49a6e10858..b568b47db5 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,5 +1,5 @@ from pathlib import Path -from typing import Union, Optional +from typing import Optional, Union import numpy as np import pandas as pd @@ -149,13 +149,23 @@ class DiabeticRetinopathy(Module): Types.INT, "Number of anti-VEGF injections received in the current treatment cycle", ), + "total_laser_pan_retinal_coagulation_sessions": Property( + Types.INT, "Number of Laser Pan Retinal Coagulation sessions received", + ), + "on_laser_pan_retinal_coagulation_treatment": Property( + Types.BOOL, "Whether this person is on Laser Pan Retinal Coagulation treatment", + ), + "dr_date_prc_treatment": Property( + Types.DATE, + "date of first receiving Laser Pan Retinal Coagulation treatment (pd.NaT if never started treatment)" + ), } def __init__(self): super().__init__() self.cons_item_codes = None # (Will store consumable item codes) - def read_parameters(self, resourcefilepath: Optional[Path]=None): + def read_parameters(self, resourcefilepath: Optional[Path] = None): """ Read all parameters and define symptoms (if any)""" self.load_parameters_from_dataframe( read_csv_files(resourcefilepath / "ResourceFile_Diabetic_Retinopathy", @@ -197,6 +207,9 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dmo_antivegf_count"] = 0 + df.loc[list(alive_diabetes_idx), "total_laser_pan_retinal_coagulation_sessions"] = 0 + df.loc[list(alive_diabetes_idx), "on_laser_pan_retinal_coagulation_treatment"] = False + df.loc[list(alive_diabetes_idx), "dr_date_prc_treatment"] = pd.NaT # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -305,6 +318,9 @@ def on_birth(self, mother_id: int, child_id: int) -> None: self.sim.population.props.at[child_id, 'selected_for_eye_screening'] = False self.sim.population.props.at[child_id, 'dr_date_diagnosis'] = pd.NaT self.sim.population.props.at[child_id, "dmo_antivegf_count"] = 0 + self.sim.population.props.at[child_id, "total_laser_pan_retinal_coagulation_sessions"] = 0 + self.sim.population.props.at[child_id, 'on_laser_pan_retinal_coagulation_treatment'] = False + self.sim.population.props.at[child_id, 'dr_date_prc_treatment'] = pd.NaT def on_simulation_end(self) -> None: pass @@ -312,7 +328,7 @@ def on_simulation_end(self) -> None: def make_the_linear_models(self) -> None: """Make and save LinearModels that will be used when the module is running""" self.lm = dict() - p =self.parameters + p = self.parameters self.lm['onset_mild_or_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, @@ -579,7 +595,7 @@ def apply(self, person_id, squeeze_factor): # Repeat eye screening in 1 year if dr_status is mild_or_moderate or dmo_status is # non_clinically_significant - next_screening_if_mild_or_moderate =\ + next_screening_if_mild_or_moderate = \ self.sim.date + pd.DateOffset(months=p['next_screening_if_mild_or_moderate']) self.sim.modules['HealthSystem'].schedule_hsi_event(self, topen=next_screening_if_mild_or_moderate, @@ -594,24 +610,11 @@ def apply(self, person_id, squeeze_factor): priority=1) elif person.dr_status == 'proliferative': - # If this is their FIRST diagnosis (no prior treatment yet), send them - # for HSI_Dr_Laser_Pan_Retinal_Coagulation - if pd.isna(person.dr_date_treatment): - self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=1), - topen=self.sim.date, - priority=0 - ) - else: - # This is a scheduled follow-up or review (2 months / 3,6,9,12 months after - # HSI_Dr_Laser_Pan_Retinal_Coagulation). Since HSI_Dr_Laser_Pan_Retinal_Coagulation is - # scheduled for 2 weeks, this will only execute after at least 2 months and hence after session 2 - if self.module.rng.random_sample() < self.module.parameters['prob_repeat_laser']: - self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=1), - topen=self.sim.date, - priority=0 - ) + self.sim.modules['HealthSystem'].schedule_hsi_event( + hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id), + topen=self.sim.date, + priority=0 + ) if person.dmo_status == "clinically_significant" and person.dr_status != "none": # Randomise between AntiVEGF or Focal Laser @@ -729,42 +732,6 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dmo_on_treatment'] = False -class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): - """This is a Health System Interaction Event in which a person receives a dialysis session 2 times a week - adding up to 8 times a month.""" - - def __init__(self, module, person_id): - super().__init__(module, person_id=person_id) - - self.TREATMENT_ID = 'Dr_Laser_Pan_Retinal_Coagulation_Treatment' - self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) - self.ACCEPTED_FACILITY_LEVEL = '3' - - def apply(self, person_id, squeeze_factor): - - df = self.sim.population.props - person = df.loc[person_id] - - if not df.at[person_id, 'is_alive']: - # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() - - # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() - - self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', - 'Silt lamp laser delivery system', - 'Indirect laser delivery system', 'Laser wide-field contact lens'}) - - next_session_date = self.sim.date + pd.DateOffset(weeks=1) - self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_session_date, - tclose=next_session_date + pd.DateOffset(days=3), - priority=1 - ) - - class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin): """ This is the HSI event given to individuals with proliferative diabetic retinopathy after undergoing an eye @@ -794,7 +761,7 @@ def apply(self, person_id, squeeze_factor): return self.sim.modules['HealthSystem'].get_blank_appt_footprint() # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: + if not person["dr_diagnosed"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() is_cons_available = self.get_consumables( @@ -805,31 +772,41 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', 'Silt lamp laser delivery system', 'Indirect laser delivery system', 'Laser wide-field contact lens'}) - if self.session == 1: - # schedule the second session in 1 week + # Increment the per-person session count + df.at[person_id, 'total_laser_pan_retinal_coagulation_sessions'] += 1 + sessions = df.at[person_id, 'total_laser_pan_retinal_coagulation_sessions'] + + # Marks treatment started on first session of each cycle + # Odd-numbered session means session 1 of cycle + if sessions % 2 == 1: + df.at[person_id, 'on_laser_pan_retinal_coagulation_treatment'] = True + df.at[person_id, 'dr_date_prc_treatment'] = self.sim.date + df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] + + # Schedule session 2 in 1 week + next_session_date = self.sim.date + pd.DateOffset(weeks=1) hs.schedule_hsi_event( - hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id, session=2), - topen=self.sim.date + pd.DateOffset(weeks=1), - priority=0 + self, + topen=next_session_date, + tclose=next_session_date + pd.DateOffset(days=3), + priority=1 ) - elif self.session == 2: - # should complete treatment?? - df.at[person_id, 'dr_on_treatment'] = False + else: + df.at[person_id, 'on_laser_pan_retinal_coagulation_treatment'] = False - # schedule follow-up at 2 months + # Schedule follow-up at 2 months follow_up = self.sim.date + pd.DateOffset(months=2) hs.schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), + HSI_Dr_Dmo_Screening(self.module, person_id), topen=follow_up, priority=1 ) - # schedule reviews at 3, 6, 9, 12 months + # Schedule reviews at 3, 6, 9, 12 months for m in [3, 6, 9, 12]: - review_date = self.sim.date + pd.DateOffset(months=m) hs.schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), - topen=review_date, + HSI_Dr_Dmo_Screening(self.module, person_id), + topen=self.sim.date + pd.DateOffset(months=m), priority=1 ) From 2d266c741e8ead2878e93f2f88e85bbd62034763 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 12 Dec 2025 13:33:35 +0200 Subject: [PATCH 62/85] add diabetes_duration_greater_than_15_years as risk factor --- .../Parameter_values.csv | 4 +-- src/tlo/methods/diabetic_retinopathy.py | 34 ++++++++++++++++--- 2 files changed, 32 insertions(+), 6 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index 3b56e5e151..508643867e 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:1991729723d679b48d1a4b66dfcbc20742684f672a1400d490dfb6bbdf3fcf16 -size 1087 +oid sha256:b1ca6f067269fd58185531a60a4afbbc41343ca5eb034a71ea002d2f9b9156bc +size 1144 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b568b47db5..8a80cf7214 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -92,6 +92,10 @@ class DiabeticRetinopathy(Module): Types.INT, "Number of months until next eye screening if DR status is severe" ), + "rr_diabetes_duration_greater_than_15": Parameter( + Types.REAL, + "Relative risk multiplier for diabetic retinopathy when diabetes duration > 15 years" + ), } PROPERTIES = { @@ -224,6 +228,7 @@ def initialise_population(self, population: Population) -> None: Predictor('li_high_sugar').when(True, p['rp_dr_high_sugar']), Predictor('li_low_ex').when(True, p['rp_dr_low_ex']), Predictor('li_urban').when(True, p['rp_dr_urban']), + # Predictor().when('nc_hypertension', p['rp_ckd_nc_hypertension']), ) # any_dr = \ @@ -339,14 +344,18 @@ def make_the_linear_models(self) -> None: LinearModelType.MULTIPLICATIVE, p['rate_mild_or_moderate_to_severe'], Predictor('had_treatment_during_this_stage', external=True) - .when(True, 0.0).otherwise(1.0) + .when(True, 0.0).otherwise(1.0), + Predictor('diabetes_duration_greater_than_15_years', external=True) + .when(True, p['rr_diabetes_duration_greater_than_15']) ) self.lm['severe_proliferative_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, p['rate_severe_to_proliferative'], Predictor('had_treatment_during_this_stage', external=True) - .when(True, 0.0).otherwise(1.0) + .when(True, 0.0).otherwise(1.0), + Predictor('diabetes_duration_greater_than_15_years', external=True) + .when(True, p['rr_diabetes_duration_greater_than_15']) ) def look_up_consumable_item_codes(self): @@ -447,6 +456,21 @@ def __init__(self, module): def apply(self, population: Population) -> None: df = population.props + # Getting all those with diagnosed diabetes from the cardio_metabolic_disorders module + alive_diabetes_diagnosed_in_cmd = df.is_alive & df.nc_diabetes & df.nc_diabetes_date_diagnosis.notna() + + # Compute diabetes duration (years) + diabetes_duration_years = pd.Series(0.0, index=df.index) + + diabetes_duration_years.loc[alive_diabetes_diagnosed_in_cmd] = ( + (self.sim.date - df.loc[alive_diabetes_diagnosed_in_cmd, 'nc_diabetes_date_diagnosis']).dt.days / 365.25 + ) + + # Compute the boolean threshold as a variable you can inspect + # Boolean for >15 years + diabetes_duration_greater_than_15_years = diabetes_duration_years >= 15 + print(f'long diabetes {diabetes_duration_greater_than_15_years}') + had_treatment_during_this_stage = \ df.is_alive & ~pd.isnull(df.dr_date_treatment) & \ (df.dr_status == df.dr_stage_at_which_treatment_given) @@ -464,7 +488,8 @@ def apply(self, population: Population) -> None: mildmoderate_to_severe = self.module.lm['mildmoderate_severe_dr'].predict( diabetes_and_alive_mild_moderate_dr, self.module.rng, - had_treatment_during_this_stage=had_treatment_during_this_stage) + had_treatment_during_this_stage=had_treatment_during_this_stage, + diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) # moderate_to_severe_idx = moderate_to_severe[moderate_to_severe].index mildmoderate_to_severe_idx = df.index[np.where(mildmoderate_to_severe)[0]] df.loc[mildmoderate_to_severe_idx, 'dr_status'] = 'severe' @@ -472,7 +497,8 @@ def apply(self, population: Population) -> None: severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict( diabetes_and_alive_severedr, self.module.rng, - had_treatment_during_this_stage=had_treatment_during_this_stage) + had_treatment_during_this_stage=had_treatment_during_this_stage, + diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) # severe_to_proliferative_idx = mild_to_moderate[severe_to_proliferative].index severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' From 3fd8de293ae2aa411702278d5877184dddb97614 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 12 Dec 2025 14:06:03 +0200 Subject: [PATCH 63/85] re-work dr and dmo combination scheduling --- src/tlo/methods/diabetic_retinopathy.py | 27 ++++++++++++------------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 8a80cf7214..b61eb321ea 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -469,7 +469,6 @@ def apply(self, population: Population) -> None: # Compute the boolean threshold as a variable you can inspect # Boolean for >15 years diabetes_duration_greater_than_15_years = diabetes_duration_years >= 15 - print(f'long diabetes {diabetes_duration_greater_than_15_years}') had_treatment_during_this_stage = \ df.is_alive & ~pd.isnull(df.dr_date_treatment) & \ @@ -609,7 +608,7 @@ def apply(self, person_id, squeeze_factor): if person.dr_status == 'mild_or_moderate' or person.dmo_status == 'non_clinically_significant': # schedule HSI_CardioMetabolicDisorders_StartWeightLossAndMedication # and repeat HSI_DR_Dmo_Screening in 1 year - self.sim.modules["HealthSystem"].schedule_hsi_event( + hs.schedule_hsi_event( hsi_event=cardio_metabolic_disorders.HSI_CardioMetabolicDisorders_StartWeightLossAndMedication( person_id=person_id, module=self.sim.modules["CardioMetabolicDisorders"], @@ -623,30 +622,30 @@ def apply(self, person_id, squeeze_factor): # non_clinically_significant next_screening_if_mild_or_moderate = \ self.sim.date + pd.DateOffset(months=p['next_screening_if_mild_or_moderate']) - self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_screening_if_mild_or_moderate, - tclose=None, - priority=1) + hs.schedule_hsi_event(self, + topen=next_screening_if_mild_or_moderate, + tclose=None, + priority=1) elif person.dr_status == 'severe': next_screening_if_severe = self.sim.date + pd.DateOffset(months=p['next_screening_if_severe']) - self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_screening_if_severe, - tclose=None, - priority=1) + hs.schedule_hsi_event(self, + topen=next_screening_if_severe, + tclose=None, + priority=1) - elif person.dr_status == 'proliferative': - self.sim.modules['HealthSystem'].schedule_hsi_event( + if person.dr_status == 'proliferative': + hs.schedule_hsi_event( hsi_event=HSI_Dr_Laser_Pan_Retinal_Coagulation(self.module, person_id), topen=self.sim.date, priority=0 ) - if person.dmo_status == "clinically_significant" and person.dr_status != "none": + if person.dmo_status == 'clinically_significant': # Randomise between AntiVEGF or Focal Laser treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ if self.module.rng.random_sample() < 0.5 else HSI_Dr_Dmo_Focal_Laser - self.sim.modules['HealthSystem'].schedule_hsi_event( + hs.schedule_hsi_event( hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), topen=self.sim.date, priority=0 From 492c004dc636c5fe6ae74a296080c0c2f07a4af6 Mon Sep 17 00:00:00 2001 From: thewati Date: Sat, 3 Jan 2026 02:07:24 +0200 Subject: [PATCH 64/85] treatment success --- .../Parameter_values.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 69 ++++++++++++++++++- 2 files changed, 69 insertions(+), 4 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index 508643867e..ac44920abd 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:b1ca6f067269fd58185531a60a4afbbc41343ca5eb034a71ea002d2f9b9156bc -size 1144 +oid sha256:b32a60beb2d15ebfb13a61c3be8370384900828a3bd29ba774a59d86e3ce60d4 +size 1385 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b61eb321ea..a36548d5e8 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -96,6 +96,24 @@ class DiabeticRetinopathy(Module): Types.REAL, "Relative risk multiplier for diabetic retinopathy when diabetes duration > 15 years" ), + "prob_antivegf_success_clinically_significant": Parameter( + Types.REAL, + "Probability that anti-VEGF treatment improves vision (transition from clinically_significant to " + "non_clinically_significant)" + ), + "prob_focal_laser_success_clinically_significant": Parameter( + Types.REAL, + "Probability that focal laser treatment improves vision (transition from clinically_significant to " + "non_clinically_significant)" + ), + "prob_laser_prc_success_proliferative": Parameter( + Types.REAL, + "Probability that pan-retinal laser coagulation successfully treats proliferative DR" + ), + "rr_progression_after_treatment": Parameter( + Types.REAL, + "Relative risk of progression to more severe stages after receiving treatment (applied multiplicatively)" + ), } PROPERTIES = { @@ -344,7 +362,7 @@ def make_the_linear_models(self) -> None: LinearModelType.MULTIPLICATIVE, p['rate_mild_or_moderate_to_severe'], Predictor('had_treatment_during_this_stage', external=True) - .when(True, 0.0).otherwise(1.0), + .when(True, p['rr_progression_after_treatment']), Predictor('diabetes_duration_greater_than_15_years', external=True) .when(True, p['rr_diabetes_duration_greater_than_15']) ) @@ -353,7 +371,7 @@ def make_the_linear_models(self) -> None: LinearModelType.MULTIPLICATIVE, p['rate_severe_to_proliferative'], Predictor('had_treatment_during_this_stage', external=True) - .when(True, 0.0).otherwise(1.0), + .when(True, p['rr_progression_after_treatment']), Predictor('diabetes_duration_greater_than_15_years', external=True) .when(True, p['rr_diabetes_duration_greater_than_15']) ) @@ -406,6 +424,46 @@ def do_treatment(self, person_id, prob_success): if prob_success > self.rng.random_sample(): self.do_recovery([person_id]) + def do_treatment_success_dmo(self, person_id: int, treatment_type: str) -> None: + """Apply treatment success for DMO (clinically_significant)""" + df = self.sim.population.props + p = self.parameters + + if df.at[person_id, 'dmo_status'] != 'clinically_significant': + return + + if treatment_type == 'antivegf': + success_prob = p['prob_antivegf_success_clinically_significant'] + elif treatment_type == 'focal_laser': + success_prob = p['prob_focal_laser_success_clinically_significant'] + else: + return + + if self.rng.random_sample() < success_prob: + # Treatment successful, then improve DMO status + df.at[person_id, 'dmo_status'] = 'non_clinically_significant' + logger.debug(key='debug', + data=f'Treatment successful for person {person_id}: DMO improved to non_clinically_significant') + + def do_treatment_success_proliferative(self, person_id: int) -> None: + """Apply treatment success for proliferative DR""" + df = self.sim.population.props + p = self.parameters + + if df.at[person_id, 'dr_status'] != 'proliferative': + return + + success_prob = p['prob_laser_prc_success_proliferative'] + + if self.rng.random_sample() < success_prob: + # Treatment successful, then regress DR status + # Move from proliferative to severe + df.at[person_id, 'dr_status'] = 'severe' + df.at[person_id, 'dr_stage_at_which_treatment_given'] = 'proliferative' + df.at[person_id, 'dr_date_treatment'] = self.sim.date + df.at[person_id, 'dr_on_treatment'] = True + logger.debug(key='debug', data=f'PRC treatment successful for person {person_id}: DR regressed to severe') + def update_dmo_status(self): """Update DMO status for people with diabetic retinopathy. Ensures dmo_status is none when dr_status is none/nan.""" @@ -695,6 +753,9 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', 'Silt lamp laser delivery system', 'Laser macular contact lens'}) + # Apply treatment success + self.module.do_treatment_success_dmo(person_id, 'focal_laser') + # Schedule follow-up checkup after 3 months #todo add chance that person needs after 3 months follow_up_date = self.sim.date + pd.DateOffset(months=3) self.sim.modules['HealthSystem'].schedule_hsi_event( @@ -739,6 +800,8 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Visual acuity chart', 'Silt lamp', 'Optical coherence tomography device', 'Fundus camera', 'Tonometre'}) + self.module.do_treatment_success_dmo(person_id, 'antivegf') + df.at[person_id, 'dmo_date_treatment'] = self.sim.date df.at[person_id, 'dmo_on_treatment'] = True # Increment the injection count @@ -808,6 +871,8 @@ def apply(self, person_id, squeeze_factor): df.at[person_id, 'dr_date_prc_treatment'] = self.sim.date df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] + self.module.do_treatment_success_proliferative(person_id) + # Schedule session 2 in 1 week next_session_date = self.sim.date + pd.DateOffset(weeks=1) hs.schedule_hsi_event( From 8ce181d75acdbbe7752f856f452014a197725fd4 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 14 Jan 2026 13:49:10 +0200 Subject: [PATCH 65/85] treatment improving vision path --- .../Parameter_values.csv | 4 +- src/tlo/methods/diabetic_retinopathy.py | 138 ++++++++++++++---- 2 files changed, 112 insertions(+), 30 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index ac44920abd..b9bb61f75d 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:b32a60beb2d15ebfb13a61c3be8370384900828a3bd29ba774a59d86e3ce60d4 -size 1385 +oid sha256:df36969ef4987f202ae26e7b3934eee7f33008db14a402d7ecc19827adaeac8f +size 1832 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index a36548d5e8..d09c712fbf 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -11,7 +11,7 @@ from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.population import IndividualProperties -from tlo.util import read_csv_files +from tlo.util import read_csv_files, transition_states logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -114,6 +114,14 @@ class DiabeticRetinopathy(Module): Types.REAL, "Relative risk of progression to more severe stages after receiving treatment (applied multiplicatively)" ), + "vision_transition_matrix_no_dr": Parameter( + Types.LIST, + "Probability matrix for vision status transitions for people without sight-threatening DR" + ), + "vision_transition_matrix_sight_threatening": Parameter( + Types.LIST, + "Probability matrix for vision status transitions for people with sight-threatening DR" + ), } PROPERTIES = { @@ -181,6 +189,16 @@ class DiabeticRetinopathy(Module): Types.DATE, "date of first receiving Laser Pan Retinal Coagulation treatment (pd.NaT if never started treatment)" ), + "vision_status": Property( + Types.CATEGORICAL, + "Visual acuity status of an individual", + categories=["normal", "moderate_vision_impairment", "severe_vision_impairment", "blindness"], + ordered=True + ), + "vision_loss_due_to_dr": Property( + Types.BOOL, + "Whether current vision impairment is due to diabetic retinopathy" + ), } def __init__(self): @@ -232,6 +250,8 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "total_laser_pan_retinal_coagulation_sessions"] = 0 df.loc[list(alive_diabetes_idx), "on_laser_pan_retinal_coagulation_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_date_prc_treatment"] = pd.NaT + df.loc[list(alive_diabetes_idx), "vision_status"] = "normal" + df.loc[list(alive_diabetes_idx), "vision_loss_due_to_dr"] = False # -------------------- dr_status ----------- # Determine who has diabetic retinopathy at all stages: @@ -323,6 +343,23 @@ def initialise_simulation(self, sim: Simulation) -> None: self.make_the_linear_models() self.look_up_consumable_item_codes() + # Convert vision transition matrices + vision_states = sim.population.props.vision_status.cat.categories + + for key in [ + 'vision_transition_matrix_no_dr', + 'vision_transition_matrix_sight_threatening' + ]: + self.parameters[key] = pd.DataFrame( + self.parameters[key], + index=vision_states, + columns=vision_states + ) + + # Check that rows sum to 1 + assert np.allclose(self.parameters[key].sum(axis=1), 1.0), \ + f"{key} rows do not sum to 1" + def report_daly_values(self) -> pd.Series: return pd.Series(index=self.sim.population.props.index, data=0.0) @@ -408,22 +445,6 @@ def look_up_consumable_item_codes(self): get_item_codes("Mydriatic/Dilation Drops, 15ml"): 1 } - def do_recovery(self, idx: Union[list, pd.Index]): - """Represent the recovery from diabetic retinopathy for the person_id given in `idx`. - Recovery causes the person to move from severe to moderate""" - df = self.sim.population.props - - # Getting those with severe and updating to moderate - mask = df.loc[idx, 'dr_status'] == 'severe' - df.loc[idx[mask], 'dr_status'] = 'moderate' - df.loc[idx[mask], 'dr_date_treatment'] = self.sim.date - df.loc[idx[mask], 'dr_on_treatment'] = True - - def do_treatment(self, person_id, prob_success): - """For treatment of individuals with Severe DR status. If treatment is successful, regress to moderate.""" - if prob_success > self.rng.random_sample(): - self.do_recovery([person_id]) - def do_treatment_success_dmo(self, person_id: int, treatment_type: str) -> None: """Apply treatment success for DMO (clinically_significant)""" df = self.sim.population.props @@ -440,10 +461,25 @@ def do_treatment_success_dmo(self, person_id: int, treatment_type: str) -> None: return if self.rng.random_sample() < success_prob: - # Treatment successful, then improve DMO status - df.at[person_id, 'dmo_status'] = 'non_clinically_significant' - logger.debug(key='debug', - data=f'Treatment successful for person {person_id}: DMO improved to non_clinically_significant') + self.improve_vision(person_id) + + def improve_vision(self, person_id: int) -> None: + """Improve vision status by one category after receiving DMO treatment""" + df = self.sim.population.props + + if not df.at[person_id, 'vision_loss_due_to_dr']: + return + + vision_categories = df.vision_status.cat.categories + current_vision = df.at[person_id, 'vision_status'] + current_idx = list(vision_categories).index(current_vision) + + if current_idx > 0: # Not already at best + df.at[person_id, 'vision_status'] = vision_categories[current_idx - 1] + + # If vision becomes normal, vision loss is no longer due to DR + if df.at[person_id, 'vision_status'] == 'normal': + df.at[person_id, 'vision_loss_due_to_dr'] = False def do_treatment_success_proliferative(self, person_id: int) -> None: """Apply treatment success for proliferative DR""" @@ -457,12 +493,10 @@ def do_treatment_success_proliferative(self, person_id: int) -> None: if self.rng.random_sample() < success_prob: # Treatment successful, then regress DR status - # Move from proliferative to severe - df.at[person_id, 'dr_status'] = 'severe' - df.at[person_id, 'dr_stage_at_which_treatment_given'] = 'proliferative' - df.at[person_id, 'dr_date_treatment'] = self.sim.date - df.at[person_id, 'dr_on_treatment'] = True - logger.debug(key='debug', data=f'PRC treatment successful for person {person_id}: DR regressed to severe') + vs = df.at[person_id, 'vision_status'] + + if vs not in ['normal', 'blindness']: + self.improve_vision(person_id) def update_dmo_status(self): """Update DMO status for people with diabetic retinopathy. @@ -503,6 +537,41 @@ def update_dmo_status(self): f"have DMO status: {invalid_cases[['dr_status', 'dmo_status']].to_dict()}" ) + def update_vision_status(self): + """Update vision status for people living with diabtes""" + df = self.sim.population.props + p = self.parameters + rng = self.rng + + alive_diabetes = df.is_alive & df.nc_diabetes + if not alive_diabetes.any(): + return + + sight_threatening = ( + df.dr_status.isin(['severe', 'proliferative']) | + (df.dmo_status == 'clinically_significant') + ) + + for idx, matrix in [ + (alive_diabetes & ~sight_threatening, p['vision_transition_matrix_no_dr']), + (alive_diabetes & sight_threatening, p['vision_transition_matrix_sight_threatening']), + ]: + if not idx.any(): + continue + + current = df.loc[idx, 'vision_status'] + proposed = transition_states(current, matrix, rng) + + # Allow only same or worse vision (categorical ordering) + allowed = proposed >= current + + # Update vision status + df.loc[idx & allowed, 'vision_status'] = proposed[allowed] + + # Update cause only when vision impaired and DR present + impaired = df.vision_status != 'normal' + df.loc[impaired & (df.dr_status != 'none'), 'vision_loss_due_to_dr'] = True + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis @@ -580,6 +649,8 @@ def apply(self, population: Population) -> None: df.loc[regress_to_none_idx, "dr_status"] = "none" # df.loc[regress_to_none_idx, "dmo_status"] = "none" + self.module.update_vision_status() + # ------------------------SELECTING INDIVIDUALS FOR FOR DR OR DMO EYE EXAM/SCREENING--------------------- df.selected_for_eye_screening = False @@ -633,7 +704,7 @@ def apply(self, person_id, squeeze_factor): df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] - p = self.parameters + p = self.module.parameters if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint @@ -919,6 +990,17 @@ def apply(self, population): # Create dictionary for each subset, adding prefix to key name, and adding to make a flat dict for logging. out = {} + # Vision-related stats + vision_out = { + 'total_normal_vision': (df.vision_status == 'normal').sum(), + 'total_moderate_vision_impairment': (df.vision_status == 'moderate_vision_impairment').sum(), + 'total_severe_vision_impairment': (df.vision_status == 'severe_vision_impairment').sum(), + 'total_blindness': (df.vision_status == 'blindness').sum(), + 'vision_loss_due_to_dr': df.vision_loss_due_to_dr.sum(), + } + + out.update(vision_out) + # Current counts, total out.update({ f'total_{k}': v for k, v in df.loc[df.is_alive].dr_status.value_counts().items()}) From 341da6a069d025d1383a35253797b30ad9207cb9 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 16 Jan 2026 09:50:57 +0200 Subject: [PATCH 66/85] create diagnostic for dilated eye exam --- .../Parameter_values.csv | 4 ++-- src/tlo/methods/diabetic_retinopathy.py | 16 +++++++++++++++- 2 files changed, 17 insertions(+), 3 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv index b9bb61f75d..12816a6279 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:df36969ef4987f202ae26e7b3934eee7f33008db14a402d7ecc19827adaeac8f -size 1832 +oid sha256:4041074105b3685beba2b20f078dbb23ac51734516b4b7969feab79142afd4c6 +size 1891 diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index d09c712fbf..da76d1b661 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -8,6 +8,7 @@ from tlo.events import IndividualScopeEventMixin, PopulationScopeEventMixin, RegularEvent from tlo.lm import LinearModel, LinearModelType, Predictor from tlo.methods import Metadata, cardio_metabolic_disorders +from tlo.methods.dxmanager import DxTest from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler from tlo.population import IndividualProperties @@ -122,6 +123,9 @@ class DiabeticRetinopathy(Module): Types.LIST, "Probability matrix for vision status transitions for people with sight-threatening DR" ), + "sensitivity_of_dilated_eye_exam_dr_dmo": Parameter( + Types.REAL, "sensitivity of dilated eye exam/test for DR and DMO" + ), } PROPERTIES = { @@ -343,6 +347,16 @@ def initialise_simulation(self, sim: Simulation) -> None: self.make_the_linear_models() self.look_up_consumable_item_codes() + # ----- DX TESTS ----- + # Create the diagnostic test representing dilated eye exam for DR and DMO + self.sim.modules['HealthSystem'].dx_manager.register_dx_test( + dilated_eye_exam_dr_dmo=DxTest( + property='dr_status', + sensitivity=self.parameters['sensitivity_of_dilated_eye_exam_dr_dmo'], + target_categories=["none", "mild_or_moderate", "severe", "proliferative"] + ) + ) + # Convert vision transition matrices vision_states = sim.population.props.vision_status.cat.categories @@ -719,7 +733,7 @@ def apply(self, person_id, squeeze_factor): is_cons_available = self.get_consumables( self.module.cons_item_codes['eye_screening'] ) - + #todo should I create another test so that the second one is for dmo? dx_result = hs.dx_manager.run_dx_test( dx_tests_to_run='dilated_eye_exam_dr_dmo', hsi_event=self From d2cf2a56ce28223d74b674e361068cdd490e2f61 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 16 Jan 2026 13:17:12 +0200 Subject: [PATCH 67/85] report dalys --- src/tlo/methods/diabetic_retinopathy.py | 40 ++++++++++++++++++++++++- 1 file changed, 39 insertions(+), 1 deletion(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index da76d1b661..10c05965a1 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -208,6 +208,7 @@ class DiabeticRetinopathy(Module): def __init__(self): super().__init__() self.cons_item_codes = None # (Will store consumable item codes) + self.daly_wts = dict() def read_parameters(self, resourcefilepath: Optional[Path] = None): """ Read all parameters and define symptoms (if any)""" @@ -357,6 +358,21 @@ def initialise_simulation(self, sim: Simulation) -> None: ) ) + # ----- DISABILITY-WEIGHTS ----- + if "HealthBurden" in self.sim.modules: + # For those with moderate vision impairment due to Diabetes Mellitus + self.daly_wts["moderate_vision_impairment_due_to_dm"] = self.sim.modules["HealthBurden"].get_daly_weight( + sequlae_code=967 + ) + # For those with severe vision impairment due to Diabetes Mellitus + self.daly_wts["severe_vision_impairment_due_to_dm"] = self.sim.modules["HealthBurden"].get_daly_weight( + sequlae_code=969 + ) + # For those who are blind due to Diabetes Mellitus + self.daly_wts["blindness_due_to_dm"] = self.sim.modules["HealthBurden"].get_daly_weight( + sequlae_code=974 + ) + # Convert vision transition matrices vision_states = sim.population.props.vision_status.cat.categories @@ -375,7 +391,29 @@ def initialise_simulation(self, sim: Simulation) -> None: f"{key} rows do not sum to 1" def report_daly_values(self) -> pd.Series: - return pd.Series(index=self.sim.population.props.index, data=0.0) + df = self.sim.population.props # shortcut to population properties dataframe for alive persons + + disability_series_for_alive_persons = pd.Series(index=df.index[df.is_alive], data=0.0) + + # Assign daly_wt to those with moderate vision impairment due to DM + disability_series_for_alive_persons.loc[ + (df.vision_status == "moderate_vision_impairment") & + ((df.dr_status != "none") | (df.dmo_status != "none")) + ] = self.daly_wts['moderate_vision_impairment_due_to_dm'] + + # Assign daly_wt to those with severe vision impairment due to DM + disability_series_for_alive_persons.loc[ + (df.vision_status == "severe_vision_impairment") & + ((df.dr_status != "none") | (df.dmo_status != "none")) + ] = self.daly_wts['severe_vision_impairment_due_to_dm'] + + # Assign daly_wt to those who are blind due to DM + disability_series_for_alive_persons.loc[ + (df.vision_status == "blindness") & + ((df.dr_status != "none") | (df.dmo_status != "none")) + ] = self.daly_wts['blindness_due_to_dm'] + + return disability_series_for_alive_persons def on_birth(self, mother_id: int, child_id: int) -> None: """ Set properties of a child when they are born. From d6519f1c4603fe3b02166be4074af81f418080c9 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 19 Jan 2026 10:45:36 +0200 Subject: [PATCH 68/85] normalise cols to sum to 1 --- .../diabetic_retinopathy_calibration_check.py | 154 ++++++++++++++++++ src/tlo/methods/diabetic_retinopathy.py | 38 ++++- 2 files changed, 188 insertions(+), 4 deletions(-) create mode 100644 src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py new file mode 100644 index 0000000000..1c8ccb7bf9 --- /dev/null +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py @@ -0,0 +1,154 @@ +""" +Runs the diabetic retinopathy module and produces the standard compare_number_of_deaths analysis to check +the number of deaths modelled against the GBD data. It also produces plots for diabetes DALYs with and +without the healthsytem +""" + +import matplotlib.pyplot as plt +import pandas as pd + +from tlo import Date, Simulation, logging +from tlo.analysis.utils import compare_number_of_deaths, get_root_path, parse_log_file, make_age_grp_types +from tlo.methods import ( + cardio_metabolic_disorders, + demography, + depression, + diabetic_retinopathy, + enhanced_lifestyle, + healthburden, + healthseekingbehaviour, + healthsystem, + simplified_births, + symptommanager, +) + +# The resource files +root = get_root_path() +resourcefilepath = root / "resources" + +log_config = { + "filename": "diabetic_retinopathy_calibration_check", + "directory": root / "outputs", + "custom_levels": { + "*": logging.WARNING, + "tlo.methods.demography": logging.INFO, + "tlo.methods.healthburden": logging.INFO, + } +} + +# Set parameters for the simulation +start_date = Date(2010, 1, 1) +end_date = Date(2015, 1, 1) +popsize = 5_000 + + +def get_diabetes_dalys(logfile): + output = parse_log_file(logfile) + dalys = output['tlo.methods.healthburden']['dalys_stacked'] + # Keep only numeric DALY columns + age_range + numeric_cols = dalys.select_dtypes(include='number').columns + dalys = dalys[['age_range', *numeric_cols]] + + # Sum over time + dalys = ( + dalys + .groupby('age_range') + .sum() + .reindex(make_age_grp_types().categories) + .fillna(0.0) + ) + + return dalys + + +def run_sim(allow_hsi: bool): + sim = Simulation(start_date=start_date, log_config=log_config, resourcefilepath=resourcefilepath) + + sim.register( + demography.Demography(), + simplified_births.SimplifiedBirths(), + enhanced_lifestyle.Lifestyle(), + healthsystem.HealthSystem( + disable=(allow_hsi is True), + disable_and_reject_all=(allow_hsi is False) + ), + symptommanager.SymptomManager(), + healthseekingbehaviour.HealthSeekingBehaviour(), + healthburden.HealthBurden(), + cardio_metabolic_disorders.CardioMetabolicDisorders(), + depression.Depression(), + diabetic_retinopathy.DiabeticRetinopathy(), + ) + + sim.make_initial_population(n=popsize) + sim.simulate(end_date=end_date) + + return sim.log_filepath + + +# With interventions +logfile_with_healthsystem = run_sim(allow_hsi=True) +dalys_with_hs = get_diabetes_dalys(logfile_with_healthsystem) + +# Without interventions +logfile_no_healthsystem = run_sim(allow_hsi=False) +dalys_no_hs = get_diabetes_dalys(logfile_no_healthsystem) + +CAUSE_NAME = 'Diabetes' + +# Extract Diabetes only +diabetes_dalys_with_hs = dalys_with_hs[CAUSE_NAME].fillna(0.0) +diabetes_dalys_no_hs = dalys_no_hs[CAUSE_NAME].fillna(0.0) + +# With healthsystem +comparison = compare_number_of_deaths( + logfile=logfile_with_healthsystem, + resourcefilepath=resourcefilepath +).rename(columns={'model': 'model_with_healthsystem'}) + +# Without healthsystem +x = compare_number_of_deaths( + logfile=logfile_no_healthsystem, + resourcefilepath=resourcefilepath +)['model'] +x.name = 'model_no_healthsystem' + +comparison = pd.concat([comparison, x], axis=1) + +comparison = comparison.loc[ + ("2010-2014", slice(None), slice(None), CAUSE_NAME) +].fillna(0.0) + +comparison.index = comparison.index.droplevel( + [name for name in comparison.index.names if name in ('period', 'cause')] +) + +print("####################################### Result ###################") +print((comparison["model_with_healthsystem"] - comparison["model_no_healthsystem"]).abs().sum()) + +fig, axs = plt.subplots(nrows=2, sharex=True, figsize=(8, 6)) + +for ax, sex in zip(axs, ("M", "F")): + comparison.loc[sex].plot(ax=ax) + ax.set_ylabel("Deaths per year") + ax.set_title(f"Sex: {sex}") + +axs[-1].set_xlabel("Age group") + +plt.tight_layout() +plt.show() + +# Plot for DALYs +fig, axs = plt.subplots(1, 2, figsize=(10, 4), sharey=True) + +diabetes_dalys_with_hs.plot.bar(ax=axs[0]) +axs[0].set_title("Diabetes DALYs – With Health System") +axs[0].set_xlabel("Age group") +axs[0].set_ylabel("Total DALYs") + +diabetes_dalys_no_hs.plot.bar(ax=axs[1]) +axs[1].set_title("Diabetes DALYs – No Health System") +axs[1].set_xlabel("Age group") + +plt.tight_layout() +plt.show() diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 10c05965a1..951123e071 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,5 +1,5 @@ from pathlib import Path -from typing import Optional, Union +from typing import Optional import numpy as np import pandas as pd @@ -8,6 +8,7 @@ from tlo.events import IndividualScopeEventMixin, PopulationScopeEventMixin, RegularEvent from tlo.lm import LinearModel, LinearModelType, Predictor from tlo.methods import Metadata, cardio_metabolic_disorders +from tlo.methods.causes import Cause from tlo.methods.dxmanager import DxTest from tlo.methods.hsi_event import HSI_Event from tlo.methods.hsi_generic_first_appts import HSIEventScheduler @@ -31,6 +32,13 @@ class DiabeticRetinopathy(Module): Metadata.USES_HEALTHBURDEN, } + CAUSES_OF_DEATH = { + 'diabetes': Cause( + gbd_causes='Diabetes mellitus', label='Diabetes'), } + CAUSES_OF_DISABILITY = { + 'diabetes': Cause( + gbd_causes='Diabetes mellitus', label='Diabetes'), } + PARAMETERS = { "rate_onset_to_mild_or_moderate_dr": Parameter(Types.REAL, "Probability of people who get diagnosed with non-proliferative " @@ -380,15 +388,28 @@ def initialise_simulation(self, sim: Simulation) -> None: 'vision_transition_matrix_no_dr', 'vision_transition_matrix_sight_threatening' ]: - self.parameters[key] = pd.DataFrame( + mat = pd.DataFrame( self.parameters[key], index=vision_states, columns=vision_states ) + # Force numeric + mat = mat.astype(float) + + # Normalize each column to sum exactly to 1 + col_sums = mat.sum(axis=0) + mat = mat.divide(col_sums, axis=1) + + # Safety check + assert np.allclose(mat.sum(axis=0), 1.0), \ + f"{key} columns do not sum to 1 after normalization" + + self.parameters[key] = mat + # Check that rows sum to 1 - assert np.allclose(self.parameters[key].sum(axis=1), 1.0), \ - f"{key} rows do not sum to 1" + # assert np.allclose(self.parameters[key].sum(axis=1), 1.0), \ + # f"{key} rows do not sum to 1" def report_daly_values(self) -> pd.Series: df = self.sim.population.props # shortcut to population properties dataframe for alive persons @@ -612,6 +633,15 @@ def update_vision_status(self): continue current = df.loc[idx, 'vision_status'] + + col_sums = matrix.sum(axis=0) + + bad = col_sums[~np.isclose(col_sums, 1.0)] + if not bad.empty: + raise ValueError( + f"Invalid transition probabilities:\n{bad}" + ) + proposed = transition_states(current, matrix, rng) # Allow only same or worse vision (categorical ordering) From 6475b0604c962fa75734ac07b75f022f53a810d6 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 19 Jan 2026 16:42:23 +0200 Subject: [PATCH 69/85] fix progression logic and dr_diagnosed --- src/tlo/methods/diabetic_retinopathy.py | 71 ++++++++++++++++--------- 1 file changed, 46 insertions(+), 25 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 951123e071..8482cb483e 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -397,20 +397,17 @@ def initialise_simulation(self, sim: Simulation) -> None: # Force numeric mat = mat.astype(float) - # Normalize each column to sum exactly to 1 - col_sums = mat.sum(axis=0) - mat = mat.divide(col_sums, axis=1) + # Normalize each row to sum exactly to 1 + # col_sums = mat.sum(axis=0) + # mat = mat.divide(col_sums, axis=1) + row_sums = mat.sum(axis=1) + mat = mat.divide(row_sums, axis=0) # Safety check - assert np.allclose(mat.sum(axis=0), 1.0), \ - f"{key} columns do not sum to 1 after normalization" + assert np.allclose(mat.sum(axis=1), 1.0) self.parameters[key] = mat - # Check that rows sum to 1 - # assert np.allclose(self.parameters[key].sum(axis=1), 1.0), \ - # f"{key} rows do not sum to 1" - def report_daly_values(self) -> pd.Series: df = self.sim.population.props # shortcut to population properties dataframe for alive persons @@ -418,20 +415,17 @@ def report_daly_values(self) -> pd.Series: # Assign daly_wt to those with moderate vision impairment due to DM disability_series_for_alive_persons.loc[ - (df.vision_status == "moderate_vision_impairment") & - ((df.dr_status != "none") | (df.dmo_status != "none")) + (df.vision_status == "moderate_vision_impairment") & df.vision_loss_due_to_dr ] = self.daly_wts['moderate_vision_impairment_due_to_dm'] # Assign daly_wt to those with severe vision impairment due to DM disability_series_for_alive_persons.loc[ - (df.vision_status == "severe_vision_impairment") & - ((df.dr_status != "none") | (df.dmo_status != "none")) + (df.vision_status == "severe_vision_impairment") & df.vision_loss_due_to_dr ] = self.daly_wts['severe_vision_impairment_due_to_dm'] # Assign daly_wt to those who are blind due to DM disability_series_for_alive_persons.loc[ - (df.vision_status == "blindness") & - ((df.dr_status != "none") | (df.dmo_status != "none")) + (df.vision_status == "blindness") & df.vision_loss_due_to_dr ] = self.daly_wts['blindness_due_to_dm'] return disability_series_for_alive_persons @@ -625,7 +619,7 @@ def update_vision_status(self): (df.dmo_status == 'clinically_significant') ) - for idx, matrix in [ + for idx, base_matrix in [ (alive_diabetes & ~sight_threatening, p['vision_transition_matrix_no_dr']), (alive_diabetes & sight_threatening, p['vision_transition_matrix_sight_threatening']), ]: @@ -634,25 +628,51 @@ def update_vision_status(self): current = df.loc[idx, 'vision_status'] + # Ensure matrix is row-stochastic at runtime + matrix = base_matrix.astype(float).copy() + col_sums = matrix.sum(axis=0) - bad = col_sums[~np.isclose(col_sums, 1.0)] - if not bad.empty: + # Hard failure if any column has zero probability mass + if (col_sums == 0).any(): + bad = col_sums[col_sums == 0] raise ValueError( - f"Invalid transition probabilities:\n{bad}" + f"Transition matrix has zero-probability columns:\n{bad}" ) + # Renormalise rows + matrix = matrix.divide(col_sums, axis=1) + + # Final safety check + if not np.allclose(matrix.sum(axis=0), 1.0): + raise ValueError( + "Transition matrix columns do not sum to 1 after renormalisation" + ) + + # Propose new vision states proposed = transition_states(current, matrix, rng) - # Allow only same or worse vision (categorical ordering) + # on_treatment = df.loc[idx, 'dr_on_treatment'] + # + # # For treated individuals, they shouldn't worsen + # proposed.loc[on_treatment] = np.minimum( + # proposed.loc[on_treatment], + # current.loc[on_treatment] + # ) + + # Allow only same or worse vision (ordinal categories) allowed = proposed >= current - # Update vision status + # Apply updates df.loc[idx & allowed, 'vision_status'] = proposed[allowed] - # Update cause only when vision impaired and DR present - impaired = df.vision_status != 'normal' - df.loc[impaired & (df.dr_status != 'none'), 'vision_loss_due_to_dr'] = True + # Update cause only when vision impaired and diabetes-related eye disease + impaired = df.vision_status.isin([ + 'moderate_vision_impairment', + 'severe_vision_impairment', + 'blindness']) + + df.loc[impaired & df.nc_diabetes, 'vision_loss_due_to_dr'] = True class DrPollEvent(RegularEvent, PopulationScopeEventMixin): @@ -793,7 +813,7 @@ def apply(self, person_id, squeeze_factor): return self.sim.modules['HealthSystem'].get_blank_appt_footprint() # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: + if person["dr_on_treatment"]: return self.sim.modules["HealthSystem"].get_blank_appt_footprint() assert pd.isnull(df.at[person_id, 'dr_date_treatment']) @@ -811,6 +831,7 @@ def apply(self, person_id, squeeze_factor): # record date of diagnosis df.at[person_id, 'dr_date_diagnosis'] = self.sim.date df.at[person_id, 'dr_date_treatment'] = self.sim.date + df.at[person_id, 'dr_diagnosed'] = True df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] # If consumables are available, add equipment used self.add_equipment({'Visual acuity chart', 'Direct ophthalmoscope', From 8590b2fe6955d51eab76b79cde25473eed9f03c3 Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 19 Jan 2026 16:59:03 +0200 Subject: [PATCH 70/85] Add logging. Fix resourcefile issue --- .../{Parameter_values.csv => parameter_values.csv} | 0 src/tlo/methods/diabetic_retinopathy.py | 4 ++++ 2 files changed, 4 insertions(+) rename resources/ResourceFile_Diabetic_Retinopathy/{Parameter_values.csv => parameter_values.csv} (100%) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv similarity index 100% rename from resources/ResourceFile_Diabetic_Retinopathy/Parameter_values.csv rename to resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 8482cb483e..b5b4a25981 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1100,6 +1100,10 @@ def apply(self, population): 'total_severe_vision_impairment': (df.vision_status == 'severe_vision_impairment').sum(), 'total_blindness': (df.vision_status == 'blindness').sum(), 'vision_loss_due_to_dr': df.vision_loss_due_to_dr.sum(), + 'total_diagnosed': df.dr_diagnosed.sum(), + 'total_on_treatment': df.dr_on_treatment.sum(), + 'treatment_success_rate': df[df.dr_on_treatment & (df.vision_status == 'normal')].shape[0] / + max(1, df.dr_on_treatment.sum()) } out.update(vision_out) From 7536de8f6c53ef60f450384aecc87e111bb2bde9 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 20 Jan 2026 09:45:29 +0200 Subject: [PATCH 71/85] isort --- .../diabetic_retinopathy_calibration_check.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py index 1c8ccb7bf9..d3749be1a2 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py @@ -8,7 +8,12 @@ import pandas as pd from tlo import Date, Simulation, logging -from tlo.analysis.utils import compare_number_of_deaths, get_root_path, parse_log_file, make_age_grp_types +from tlo.analysis.utils import ( + compare_number_of_deaths, + get_root_path, + make_age_grp_types, + parse_log_file, +) from tlo.methods import ( cardio_metabolic_disorders, demography, From 8b2a6b2f917d8f2aa6fdf43fcebbc06b7ce033db Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 27 Jan 2026 16:19:14 +0200 Subject: [PATCH 72/85] review HSI, update update_vision_status, date_last_screening --- .../parameter_values.csv | 4 +- .../diabetic_retinopathy_calibration_check.py | 1 - src/tlo/methods/diabetic_retinopathy.py | 158 ++++++++++++------ 3 files changed, 113 insertions(+), 50 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index 12816a6279..0381cbe8de 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:4041074105b3685beba2b20f078dbb23ac51734516b4b7969feab79142afd4c6 -size 1891 +oid sha256:7b009e16093682680e11a6214562ccdb115dc815a56f6a3aaa2e3efb2bb7e3e9 +size 2166 diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py index d3749be1a2..dc17aea8d7 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py @@ -46,7 +46,6 @@ end_date = Date(2015, 1, 1) popsize = 5_000 - def get_diabetes_dalys(logfile): output = parse_log_file(logfile) dalys = output['tlo.methods.healthburden']['dalys_stacked'] diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b5b4a25981..8ddffa67cf 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -93,6 +93,10 @@ class DiabeticRetinopathy(Module): "Probability that a patient who remains proliferative at follow-up/review will " "require a repeat of HSI_Dr_Laser_Pan_Retinal_Coagulation" ), + "prob_repeat_dmo_treatment": Parameter( + Types.REAL, + "Probability that clinically significant DMO requires repeat treatment at review" + ), "next_screening_if_mild_or_moderate": Parameter( Types.INT, "Number of months until next eye screening if DR status is mild or moderate" @@ -131,6 +135,10 @@ class DiabeticRetinopathy(Module): Types.LIST, "Probability matrix for vision status transitions for people with sight-threatening DR" ), + "vision_transition_matrix_treated_sight_threatening": Parameter( + Types.LIST, + "Probability matrix for vision status transitions for people with sight-threatening DR" + ), "sensitivity_of_dilated_eye_exam_dr_dmo": Parameter( Types.REAL, "sensitivity of dilated eye exam/test for DR and DMO" ), @@ -161,6 +169,10 @@ class DiabeticRetinopathy(Module): Types.DATE, "date of first receiving diabetic macular oedema treatment (pd.NaT if never started treatment)" ), + "dr_date_last_screening": Property( + Types.DATE, + "Date of last eye screening (pd.NaT if never screened)" + ), "dr_stage_at_which_treatment_given": Property( Types.CATEGORICAL, "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", @@ -257,6 +269,7 @@ def initialise_population(self, population: Population) -> None: df.loc[list(alive_diabetes_idx), "selected_for_eye_screening"] = False df.loc[list(alive_diabetes_idx), "dr_date_treatment"] = pd.NaT df.loc[list(alive_diabetes_idx), "dmo_date_treatment"] = pd.NaT + df.loc[list(alive_diabetes_idx), "dr_date_last_screening"] = pd.NaT df.loc[list(alive_diabetes_idx), "dr_stage_at_which_treatment_given"] = "none" df.loc[list(alive_diabetes_idx), "dr_date_diagnosis"] = pd.NaT df.loc[list(alive_diabetes_idx), "dmo_antivegf_count"] = 0 @@ -386,7 +399,8 @@ def initialise_simulation(self, sim: Simulation) -> None: for key in [ 'vision_transition_matrix_no_dr', - 'vision_transition_matrix_sight_threatening' + 'vision_transition_matrix_sight_threatening', + 'vision_transition_matrix_treated_sight_threatening' ]: mat = pd.DataFrame( self.parameters[key], @@ -619,9 +633,15 @@ def update_vision_status(self): (df.dmo_status == 'clinically_significant') ) + # People on treatment should have better outcomes so should be isolated + on_treatment = df.dr_on_treatment | df.dmo_on_treatment + for idx, base_matrix in [ (alive_diabetes & ~sight_threatening, p['vision_transition_matrix_no_dr']), - (alive_diabetes & sight_threatening, p['vision_transition_matrix_sight_threatening']), + (alive_diabetes & sight_threatening & ~on_treatment, + p['vision_transition_matrix_sight_threatening']), + (alive_diabetes & sight_threatening & on_treatment, + p['vision_transition_matrix_treated_sight_threatening']) ]: if not idx.any(): continue @@ -661,11 +681,14 @@ def update_vision_status(self): # ) # Allow only same or worse vision (ordinal categories) - allowed = proposed >= current + # allowed = proposed >= current - # Apply updates - df.loc[idx & allowed, 'vision_status'] = proposed[allowed] + # Series of True values with the same index + # allowed = pd.Series(True, index=current.index) + # Apply updates + # df.loc[idx & allowed, 'vision_status'] = proposed[allowed] + df.loc[idx, 'vision_status'] = proposed # Update cause only when vision impaired and diabetes-related eye disease impaired = df.vision_status.isin([ 'moderate_vision_impairment', @@ -758,10 +781,13 @@ def apply(self, population: Population) -> None: eligible_population_for_eye_screening = ( (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year - (df.dr_status == 'none') & - (df.dmo_status == 'none') & + # (df.dr_status == 'none') & + # (df.dmo_status == 'none') & (df.age_years >= 20) & - (pd.isna(df.dr_date_diagnosis)) + (pd.isna(df.dr_date_diagnosis)) & + # Add time since last screening condition + ((df.dr_date_last_screening.isna()) | + (df.dr_date_last_screening < self.sim.date - pd.DateOffset(years=1))) ) df.loc[eligible_population_for_eye_screening, 'selected_for_eye_screening'] = ( @@ -801,8 +827,6 @@ def __init__(self, module, person_id): self.ALERT_OTHER_DISEASES = [] def apply(self, person_id, squeeze_factor): - logger.debug(key='debug', - data=f'This is HSI_Dr_Dmo_Screening: investigating the condition of {person_id}') df = self.sim.population.props person = df.loc[person_id] hs = self.sim.modules["HealthSystem"] @@ -810,13 +834,10 @@ def apply(self, person_id, squeeze_factor): if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() - - # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + return hs.get_blank_appt_footprint() - assert pd.isnull(df.at[person_id, 'dr_date_treatment']) + if person["dr_on_treatment"] and not pd.isna(person["dr_date_last_screening"]): + return hs.get_blank_appt_footprint() is_cons_available = self.get_consumables( self.module.cons_item_codes['eye_screening'] @@ -831,8 +852,14 @@ def apply(self, person_id, squeeze_factor): # record date of diagnosis df.at[person_id, 'dr_date_diagnosis'] = self.sim.date df.at[person_id, 'dr_date_treatment'] = self.sim.date + df.at[person_id, 'dr_date_last_screening'] = self.sim.date df.at[person_id, 'dr_diagnosed'] = True df.at[person_id, 'dr_stage_at_which_treatment_given'] = df.at[person_id, 'dr_status'] + + # Set diabetes ever diagnosed to true if not already set + if not df.at[person_id, 'nc_diabetes_ever_diagnosed']: + df.at[person_id, 'nc_diabetes_ever_diagnosed'] = True + # If consumables are available, add equipment used self.add_equipment({'Visual acuity chart', 'Direct ophthalmoscope', 'Fundus camera'}) @@ -902,17 +929,17 @@ def apply(self, person_id, squeeze_factor): data=f'This is HSI_Dr_Focal_Laser: initiating laser treatment for person {person_id}') df = self.sim.population.props person = df.loc[person_id] - # hs = self.sim.modules["HealthSystem"] + hs = self.sim.modules["HealthSystem"] if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + return hs.get_blank_appt_footprint() - # if person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + # if not already diagnosed, do nothing + if not person["dr_diagnosed"]: + return hs.get_blank_appt_footprint() - assert pd.isnull(df.at[person_id, 'dr_date_treatment']) + # assert pd.isnull(df.at[person_id, 'dr_date_treatment']) is_cons_available = self.get_consumables( self.module.cons_item_codes['focal_laser'] @@ -932,8 +959,8 @@ def apply(self, person_id, squeeze_factor): # Schedule follow-up checkup after 3 months #todo add chance that person needs after 3 months follow_up_date = self.sim.date + pd.DateOffset(months=3) - self.sim.modules['HealthSystem'].schedule_hsi_event( - hsi_event=HSI_Dr_Dmo_Screening(self.module, person_id), + hs.schedule_hsi_event( + hsi_event=HSI_Dr_Dmo_Review(self.module, person_id), topen=follow_up_date, priority=1 ) @@ -957,14 +984,15 @@ def apply(self, person_id, squeeze_factor): data=f'This is HSI_Dr_AntiVEGF for person {person_id}') df = self.sim.population.props person = df.loc[person_id] + hs = self.sim.modules["HealthSystem"] if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + return hs.get_blank_appt_footprint() - # If person already on treatment or not yet diagnosed, do nothing - if person["dr_on_treatment"] or not person["dr_diagnosed"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + # If not already diagnosed, do nothing + if not person["dr_diagnosed"]: + return hs.get_blank_appt_footprint() is_cons_available = self.get_consumables( self.module.cons_item_codes['anti_vegf_injection'] @@ -974,8 +1002,6 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Visual acuity chart', 'Silt lamp', 'Optical coherence tomography device', 'Fundus camera', 'Tonometre'}) - self.module.do_treatment_success_dmo(person_id, 'antivegf') - df.at[person_id, 'dmo_date_treatment'] = self.sim.date df.at[person_id, 'dmo_on_treatment'] = True # Increment the injection count @@ -983,11 +1009,13 @@ def apply(self, person_id, squeeze_factor): # Check if more injections are needed. Must not exceed 8 if df.at[person_id, 'dmo_antivegf_count'] < 8: + self.module.do_treatment_success_dmo(person_id, 'antivegf') + next_session = self.sim.date + pd.DateOffset(months=1) - self.sim.modules['HealthSystem'].schedule_hsi_event(self, - topen=next_session, - priority=0 - ) + hs.schedule_hsi_event(self, + topen=next_session, + priority=0 + ) else: # Reset individual injections after getting 8 of them df.at[person_id, 'dmo_antivegf_count'] = 0 @@ -1000,7 +1028,7 @@ class HSI_Dr_Laser_Pan_Retinal_Coagulation(HSI_Event, IndividualScopeEventMixin) exam/screening """ - def __init__(self, module, person_id, session: int = 1): + def __init__(self, module, person_id): super().__init__(module, person_id=person_id) assert isinstance(module, DiabeticRetinopathy) @@ -1009,7 +1037,6 @@ def __init__(self, module, person_id, session: int = 1): self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1, 'NewAdult': 1}) self.ACCEPTED_FACILITY_LEVEL = '3' self.ALERT_OTHER_DISEASES = [] - self.session = int(session) def apply(self, person_id, squeeze_factor): logger.debug(key='debug', @@ -1020,11 +1047,11 @@ def apply(self, person_id, squeeze_factor): if not df.at[person_id, 'is_alive']: # The person is not alive, the event did not happen: so return a blank footprint - return self.sim.modules['HealthSystem'].get_blank_appt_footprint() + return hs.get_blank_appt_footprint() - # if person already on treatment or not yet diagnosed, do nothing + # if person not yet diagnosed, do nothing if not person["dr_diagnosed"]: - return self.sim.modules["HealthSystem"].get_blank_appt_footprint() + return hs.get_blank_appt_footprint() is_cons_available = self.get_consumables( self.module.cons_item_codes['laser_pan_retinal_photocoagulation'] @@ -1058,21 +1085,58 @@ def apply(self, person_id, squeeze_factor): else: df.at[person_id, 'on_laser_pan_retinal_coagulation_treatment'] = False - # Schedule follow-up at 2 months + # Schedule follow-up and/or review at 2 months follow_up = self.sim.date + pd.DateOffset(months=2) hs.schedule_hsi_event( - HSI_Dr_Dmo_Screening(self.module, person_id), + HSI_Dr_Dmo_Review(self.module, person_id), topen=follow_up, priority=1 ) # Schedule reviews at 3, 6, 9, 12 months - for m in [3, 6, 9, 12]: - hs.schedule_hsi_event( - HSI_Dr_Dmo_Screening(self.module, person_id), - topen=self.sim.date + pd.DateOffset(months=m), - priority=1 - ) + # for m in [3, 6, 9, 12]: + # hs.schedule_hsi_event( + # self, + # topen=self.sim.date + pd.DateOffset(months=m), + # priority=1 + # ) + + +class HSI_Dr_Dmo_Review(HSI_Event, IndividualScopeEventMixin): + """Review appointment after pan-retinal laser""" + + def __init__(self, module, person_id): + super().__init__(module, person_id=person_id) + self.TREATMENT_ID = 'Dr_Dmo_Review' + self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({'Over5OPD': 1}) + self.ACCEPTED_FACILITY_LEVEL = '3' + + def apply(self, person_id, squeeze_factor): + df = self.sim.population.props + p = self.module.parameters + hs = self.sim.modules["HealthSystem"] + + if not df.at[person_id, 'is_alive']: + # The person is not alive, the event did not happen: so return a blank footprint + return hs.get_blank_appt_footprint() + + if df.at[person_id, 'dr_status'] == 'proliferative': + if self.module.rng.random_sample() < p['prob_repeat_laser']: + # Schedule new treatment cycle + self.sim.modules['HealthSystem'].schedule_hsi_event( + HSI_Dr_Laser_Pan_Retinal_Coagulation(module=self.module, person_id=person_id), + topen=self.sim.date, + priority=0 + ) + if df.at[person_id, 'dmo_status'] == 'clinically_significant': + if self.module.rng.random_sample() < p['prob_repeat_dmo_treatment']: + treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ + if self.module.rng.random_sample() < 0.5 else HSI_Dr_Dmo_Focal_Laser + hs.schedule_hsi_event( + hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), + topen=self.sim.date, + priority=0 + ) class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): From 11128c3bf2911e9d9f794c6d771289909ff2d395 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 27 Jan 2026 19:00:30 +0200 Subject: [PATCH 73/85] cleann up and re-work transition matrices --- .../parameter_values.csv | 4 +- .../diabetic_retinopathy_calibration_check.py | 13 +- src/tlo/methods/diabetic_retinopathy.py | 123 +++++++----------- 3 files changed, 58 insertions(+), 82 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index 0381cbe8de..7d90b12bfd 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:7b009e16093682680e11a6214562ccdb115dc815a56f6a3aaa2e3efb2bb7e3e9 -size 2166 +oid sha256:bc3397717246a7cca40e2394fdd5709f130615521b79beee2f1bad9e0e730797 +size 2067 diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py index dc17aea8d7..8cf754e8e2 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_calibration_check.py @@ -1,7 +1,6 @@ """ -Runs the diabetic retinopathy module and produces the standard compare_number_of_deaths analysis to check -the number of deaths modelled against the GBD data. It also produces plots for diabetes DALYs with and -without the healthsytem +Runs the diabetic retinopathy module and produces plots for diabetes DALYs with and +without the healthsystem """ import matplotlib.pyplot as plt @@ -43,8 +42,9 @@ # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2015, 1, 1) -popsize = 5_000 +end_date = Date(2020, 1, 1) +popsize = 10_000 + def get_diabetes_dalys(logfile): output = parse_log_file(logfile) @@ -140,7 +140,8 @@ def run_sim(allow_hsi: bool): axs[-1].set_xlabel("Age group") plt.tight_layout() -plt.show() +# This plot not be needed since deaths occur due to diabetes and not DR or DMO +#plt.show() # Plot for DALYs fig, axs = plt.subplots(1, 2, figsize=(10, 4), sharey=True) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 8ddffa67cf..efc872bccc 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -69,14 +69,14 @@ class DiabeticRetinopathy(Module): "rp_dr_urban": Parameter( Types.REAL, "relative prevalence at baseline of diabetic retinopathy if urban" ), - "prob_diabetes_controlled": Parameter( - Types.REAL, - "Probability that a person with mild DR has controlled diabetes" - ), - "prob_mild_to_none_if_controlled_diabetes": Parameter( - Types.REAL, - "Probability that people with mild DR and controlled diabetes regress to 'none'" - ), + # "prob_diabetes_controlled": Parameter( + # Types.REAL, + # "Probability that a person with mild DR has controlled diabetes" + # ), + # "prob_mild_to_none_if_controlled_diabetes": Parameter( + # Types.REAL, + # "Probability that people with mild DR and controlled diabetes regress to 'none'" + # ), "probs_for_dmo_when_dr_status_mild_or_moderate": Parameter( Types.LIST, "probability of having a DMO state when an individual has non-proliferative mild/moderate " "Diabetic Retinopathy "), @@ -158,13 +158,13 @@ class DiabeticRetinopathy(Module): "dr_on_treatment": Property( Types.BOOL, "Whether this person is on diabetic retinopathy treatment", ), + "dmo_on_treatment": Property( + Types.BOOL, "Whether this person is on diabetic macular oedema treatment", + ), "dr_date_treatment": Property( Types.DATE, "date of first receiving diabetic retinopathy treatment (pd.NaT if never started treatment)" ), - "dmo_on_treatment": Property( - Types.BOOL, "Whether this person is on diabetic macular oedema treatment", - ), "dmo_date_treatment": Property( Types.DATE, "date of first receiving diabetic macular oedema treatment (pd.NaT if never started treatment)" @@ -173,6 +173,14 @@ class DiabeticRetinopathy(Module): Types.DATE, "Date of last eye screening (pd.NaT if never screened)" ), + "dr_date_prc_treatment": Property( + Types.DATE, + "date of first receiving Laser Pan Retinal Coagulation treatment (pd.NaT if never started treatment)" + ), + "dr_date_diagnosis": Property( + Types.DATE, + "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" + ), "dr_stage_at_which_treatment_given": Property( Types.CATEGORICAL, "The DR stage at which treatment was given (used to apply stage-specific treatment effect)", @@ -181,21 +189,6 @@ class DiabeticRetinopathy(Module): "dr_diagnosed": Property( Types.BOOL, "Whether this person has been diagnosed with many form of diabetic retinopathy" ), - "dr_mild_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with mild/moderate non-proliferative diabetic " - "retinopathy" - ), - "dr_proliferative_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with proliferative diabetic retinopathy" - ), - "dr_dmo_diagnosed": Property( - Types.BOOL, "Whether this person has been diagnosed with any diabetic retinopathy or diabetic macular " - "oedema" - ), - "dr_date_diagnosis": Property( - Types.DATE, - "The date of diagnosis of diabetic retinopathy (pd.NaT if never diagnosed)" - ), "selected_for_eye_screening": Property( Types.BOOL, "selected for screening this period" ), @@ -209,10 +202,6 @@ class DiabeticRetinopathy(Module): "on_laser_pan_retinal_coagulation_treatment": Property( Types.BOOL, "Whether this person is on Laser Pan Retinal Coagulation treatment", ), - "dr_date_prc_treatment": Property( - Types.DATE, - "date of first receiving Laser Pan Retinal Coagulation treatment (pd.NaT if never started treatment)" - ), "vision_status": Property( Types.CATEGORICAL, "Visual acuity status of an individual", @@ -408,17 +397,18 @@ def initialise_simulation(self, sim: Simulation) -> None: columns=vision_states ) - # Force numeric - mat = mat.astype(float) + # CSV is row-stochastic → model expects column-stochastic + mat = mat.T - # Normalize each row to sum exactly to 1 - # col_sums = mat.sum(axis=0) - # mat = mat.divide(col_sums, axis=1) - row_sums = mat.sum(axis=1) - mat = mat.divide(row_sums, axis=0) + # Validate (columns must sum to 1) + col_sums = mat.sum(axis=0) + if not np.allclose(col_sums, 1.0): + raise ValueError( + f"{key} has columns that do not sum to 1:\n{col_sums}" + ) - # Safety check - assert np.allclose(mat.sum(axis=1), 1.0) + if (mat < 0).any().any(): + raise ValueError(f"{key} contains negative probabilities") self.parameters[key] = mat @@ -573,7 +563,7 @@ def do_treatment_success_proliferative(self, person_id: int) -> None: success_prob = p['prob_laser_prc_success_proliferative'] if self.rng.random_sample() < success_prob: - # Treatment successful, then regress DR status + # If treatment successful, then regress vision status vs = df.at[person_id, 'vision_status'] if vs not in ['normal', 'blindness']: @@ -648,29 +638,14 @@ def update_vision_status(self): current = df.loc[idx, 'vision_status'] - # Ensure matrix is row-stochastic at runtime - matrix = base_matrix.astype(float).copy() - - col_sums = matrix.sum(axis=0) - - # Hard failure if any column has zero probability mass - if (col_sums == 0).any(): - bad = col_sums[col_sums == 0] + # Safety check only — no renormalisation + if not np.allclose(base_matrix.sum(axis=0), 1.0): raise ValueError( - f"Transition matrix has zero-probability columns:\n{bad}" - ) - - # Renormalise rows - matrix = matrix.divide(col_sums, axis=1) - - # Final safety check - if not np.allclose(matrix.sum(axis=0), 1.0): - raise ValueError( - "Transition matrix columns do not sum to 1 after renormalisation" + "Vision transition matrix columns do not sum to 1" ) # Propose new vision states - proposed = transition_states(current, matrix, rng) + proposed = transition_states(current, base_matrix, rng) # on_treatment = df.loc[idx, 'dr_on_treatment'] # @@ -757,21 +732,21 @@ def apply(self, population: Population) -> None: # Update DMO status self.module.update_dmo_status() - mild_dr_individuals = diabetes_and_alive_mild_moderate_dr - # Get those who are currently on diabetes weight loss medication from cardiometabolicdisorders - mild_dr_individuals_eligible = mild_dr_individuals[mild_dr_individuals.nc_diabetes_on_medication] - # Get those with controlled diabetes among those with mild dr_status - selected_individuals_with_controlled_and_mild = ( - self.module.rng.random_sample(len(mild_dr_individuals_eligible)) - < self.module.parameters['prob_diabetes_controlled']) - controlled_and_mild_idx = mild_dr_individuals_eligible.index[selected_individuals_with_controlled_and_mild] - - # Get those who will regress to none dr_status among those with mild dr_status and controlled diabetes - selected_to_regress_to_none = (self.module.rng.random_sample(len(controlled_and_mild_idx)) - < self.module.parameters['prob_mild_to_none_if_controlled_diabetes']) - regress_to_none_idx = controlled_and_mild_idx[selected_to_regress_to_none] - - df.loc[regress_to_none_idx, "dr_status"] = "none" + # mild_dr_individuals = diabetes_and_alive_mild_moderate_dr + # # Get those who are currently on diabetes weight loss medication from cardiometabolicdisorders + # mild_dr_individuals_eligible = mild_dr_individuals[mild_dr_individuals.nc_diabetes_on_medication] + # # Get those with controlled diabetes among those with mild dr_status + # selected_individuals_with_controlled_and_mild = ( + # self.module.rng.random_sample(len(mild_dr_individuals_eligible)) + # < self.module.parameters['prob_diabetes_controlled']) + # controlled_and_mild_idx = mild_dr_individuals_eligible.index[selected_individuals_with_controlled_and_mild] + # + # # Get those who will regress to none dr_status among those with mild dr_status and controlled diabetes + # selected_to_regress_to_none = (self.module.rng.random_sample(len(controlled_and_mild_idx)) + # < self.module.parameters['prob_mild_to_none_if_controlled_diabetes']) + # regress_to_none_idx = controlled_and_mild_idx[selected_to_regress_to_none] + # + # df.loc[regress_to_none_idx, "dr_status"] = "none" # df.loc[regress_to_none_idx, "dmo_status"] = "none" self.module.update_vision_status() From 3cd79bc32344cc869fb0887b8c1b2f3ed30fd0e7 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 28 Jan 2026 08:44:39 +0200 Subject: [PATCH 74/85] policy files update --- .../ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv | 4 ++-- .../ClinicallyVulnerable.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv | 4 ++-- .../ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv | 4 ++-- .../VerticalProgrammes.csv | 4 ++-- 10 files changed, 20 insertions(+), 20 deletions(-) diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv index 1a5f9f9806..d9fc67f595 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/CVD.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:aecf7aa946c8b19f526dae00f93dfdbc5197bf099d8872c30425ed4546be97fe -size 4362 +oid sha256:73393a3ce5dbd4fe5e013e9378f1cf48d8e9f8ac37767180ac1021eedd23ed8b +size 4495 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv index d821db2222..c1e7180263 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/ClinicallyVulnerable.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:9b34fdcd973ff1614e920d75615c8f1ca2b907753062dacf24058a62ebd3557d -size 3962 +oid sha256:3f0dd865369c57afc1f7f16841597f6ce53de109c9ceeba5991b06f0098dd1f2 +size 4095 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv index de0822300e..76f827e7d8 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Default.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:5d532fd0740de3e705f8fe442ad33b9f0b5f4b06009c5558baf43c95c4e541a9 -size 4364 +oid sha256:665c870559e254ca7193d6bb222a39c940b28788cd454d28dd4c2f43a6b8404c +size 4497 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv index bbb7f87ac0..a1cb40566a 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/EHP_III.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:2c663cda5aabaab8714eab4d5de58de4793c209c782741c29bd1ad2aa096f774 -size 4363 +oid sha256:ae288a6cdc5d7bc307f9ec7b5e87fff3d71848a1c8da9e34849eac5acf130503 +size 4496 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv index 0e23a8aaa9..fe5774a0d7 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/LCOA_EHP.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:12882b15543673470cb44fb4cb80e66fa308bd3f23ebd4abb86ae3b970b8ad31 -size 4362 +oid sha256:bb12ec58e6b0fe48f00420095cb4c5581cfd522218e1fb6d6e487297bf3983e2 +size 4495 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv index e6c7ae111d..cc73d19fba 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Naive.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:e5052793a94827cbfa9595047a0d0a0531a79d36d686dfc3dfdd28393447bc30 -size 4362 +oid sha256:dcc450d6e4372cd164e8ad98b374ce86e7b39ccd1d0b08dc5a89714d8051e1f9 +size 4495 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv index 445c53c48b..06ed0bc6b9 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/RMNCH.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:427ef05a883149bf42d6a503f727e35000dc90c0ecb9d705c02c0fee71b105f7 -size 4342 +oid sha256:9d8980dbcf116b2dfc91ac8fa114443a295cec103039690d19461b74248f8b95 +size 4475 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv index 4599ff1eb5..821bf786d8 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test Mode 1.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:11f1f4b2f9fc2b7ddf9ef3e3edd8b212353d2620d8cc2bddbdd23bddbca974ae -size 4364 +oid sha256:9e706205c2b93c46b2bad8ec953f368668eee527806b7918b730472b102abb94 +size 4497 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv index fe172ae619..25b3e83ea1 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/Test.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:cbf0fc709896b6bf1b5e8fde8b9d335c2bf5da9527e289244f05a18f08bc1284 -size 4364 +oid sha256:3f45563e8ed7724aa6451377be5e57de2d900ffe36e047d7a0d6f3f026374d6e +size 4497 diff --git a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv index 7158a38be7..749f850e33 100644 --- a/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv +++ b/resources/healthsystem/priority_policies/ResourceFile_PriorityRanking_ALLPOLICIES/VerticalProgrammes.csv @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:2f925e476f9d6230c19782009fe2f4b6ba6eb9d4b39cdefd8160b752d58f5919 -size 4362 +oid sha256:d15b06da45ae1be8477787a1a38de5ccfcacaddeb82aee6aff467f876b96c202 +size 4495 From d064b81b7ea20d9fe72e0a4b18354f34b7346217 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 19 Feb 2026 15:47:19 +0200 Subject: [PATCH 75/85] From LFS to Git --- .../parameter_values.csv | 32 +++++++++++++++++-- 1 file changed, 29 insertions(+), 3 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index 7d90b12bfd..cd262b9518 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,3 +1,29 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:bc3397717246a7cca40e2394fdd5709f130615521b79beee2f1bad9e0e730797 -size 2067 +parameter_name,value,param_label,prior_min,prior_max,prior_note +init_prob_any_dr,"[0.4, 0.3, 0.3]",undetermined,"[0,0,0]","[1,1,1]", +rate_onset_to_mild_or_moderate_dr,0.29,local,0,1, +rate_mild_or_moderate_to_severe,0.5,local,0,1, +rate_severe_to_proliferative,0.07,local,0,1, +probs_for_dmo_when_dr_status_mild_or_moderate,"[0.7, 0.1, 0.2]",local,"[0,0,0]","[1,1,1]", +probs_for_dmo_when_dr_status_severe,"[0.3, 0.5, 0.2]",local,"[0,0,0]","[1,1,1]", +probs_for_dmo_when_dr_status_proliferative,"[0.1, 0.7, 0.2]",local,"[0,0,0]","[1,1,1]", +prob_eye_screening,0.07,local,0,1, +prob_repeat_laser,0.3,local,0,1, +prob_repeat_dmo_treatment,0.3,local,0,1, +rp_dr_ex_alc,1.1,local,0.01,100, +rp_dr_tobacco,1.3,local,0.01,100, +rp_dr_high_sugar,1.2,local,0.01,100, +rp_dr_low_ex,1.3,local,0.01,100, +rp_dr_urban,1.4,local,0.01,100, +prob_any_dmo,"[0.1, 0.2, 0.3, 0.4]",local,"[0,0,0,0]","[1,1,1,1]", +p_laser_success,0.8,universal,0,1, +next_screening_if_mild_or_moderate,12,scenario,6,24, +next_screening_if_severe,3,scenario,3,24, +rr_diabetes_duration_greater_than_15,0.8,universal,0,1, +prob_antivegf_success_clinically_significant,0.7,universal,0,1, +prob_focal_laser_success_clinically_significant,0.5,universal,0,1, +prob_laser_prc_success_proliferative,0.6,universal,0,1, +rr_progression_after_treatment,0.5,universal,0,1, +vision_transition_matrix_no_dr,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_sight_threatening,"[[0.970,0.025,0.005,0], [0.030,0.920,0.045,0.005], [0,0.050,0.890,0.060], [0,0,0.060,0.940]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_treated_sight_threatening,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +sensitivity_of_dilated_eye_exam_dr_dmo,0.8,universal,0,1, From 9a577b07349e10235ab294121c429388bd36c429 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 19 Feb 2026 15:57:46 +0200 Subject: [PATCH 76/85] Update equip availability estimates --- ...eFile_Equipment_Availability_Estimates.csv | 107601 ++++++++------- 1 file changed, 54532 insertions(+), 53069 deletions(-) diff --git a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv index e88aedcc01..ffc44c6677 100644 --- a/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv +++ b/resources/healthsystem/infrastructure_and_equipment/ResourceFile_Equipment_Availability_Estimates.csv @@ -1,53733 +1,55196 @@ Facility_ID,Item_Code,Pr_Available -0,0,0.22628122843340237 +0,0,0.226281228 0,1,0.75 -0,2,1.0 -0,3,1.0 -0,4,0.22628122843340237 -0,5,0.22628122843340237 +0,2,1 +0,3,1 +0,4,0.226281228 +0,5,0.226281228 0,6,0.25 0,7,0.75 -0,8,0.22628122843340237 -0,9,0.22628122843340237 -0,10,0.22628122843340237 -0,11,0.22628122843340237 -0,12,0.22628122843340237 +0,8,0.226281228 +0,9,0.226281228 +0,10,0.226281228 +0,11,0.226281228 +0,12,0.226281228 0,13,0.5 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+132,374,0 +132,375,0 +132,376,0 +132,377,0 +132,378,0 +132,379,0 +132,380,0 +132,381,0 +132,382,0 +132,383,0 +132,384,0 +132,385,0 +132,386,0 +132,387,0 +132,388,0 +132,389,0 +132,390,0 +132,391,0 +132,392,0 +132,393,0 +132,394,0 +132,395,0 +132,396,0 +132,397,0 +132,398,0 +132,399,0 +132,400,0 +132,401,0 +132,402,0 +132,403,0 +132,404,0.5 +132,405,0.5 +132,406,0.5 +132,407,0.5 +132,408,0.5 +132,409,0.5 +132,410,0.5 +132,411,0.5 +132,412,0.5 +132,413,0.5 +132,414,0.5 From 88d401289fe4d668386dadbc174afd1c5a367c43 Mon Sep 17 00:00:00 2001 From: thewati Date: Wed, 11 Mar 2026 14:48:41 +0200 Subject: [PATCH 77/85] Addressing comments --- .../parameter_values.csv | 7 +- ...rceFile_Consumables_Items_and_Packages.csv | 4456 ++++++++--------- src/tlo/methods/diabetic_retinopathy.py | 42 +- tests/test_diabetic_retinopathy.py | 18 +- 4 files changed, 2266 insertions(+), 2257 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index cd262b9518..acf5724d95 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,8 +1,8 @@ parameter_name,value,param_label,prior_min,prior_max,prior_note init_prob_any_dr,"[0.4, 0.3, 0.3]",undetermined,"[0,0,0]","[1,1,1]", -rate_onset_to_mild_or_moderate_dr,0.29,local,0,1, -rate_mild_or_moderate_to_severe,0.5,local,0,1, -rate_severe_to_proliferative,0.07,local,0,1, +prob_onset_to_mild_or_moderate_dr,0.29,local,0,1, +prob_mild_or_moderate_to_severe,0.5,local,0,1, +prob_severe_to_proliferative,0.07,local,0,1, probs_for_dmo_when_dr_status_mild_or_moderate,"[0.7, 0.1, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_severe,"[0.3, 0.5, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_proliferative,"[0.1, 0.7, 0.2]",local,"[0,0,0]","[1,1,1]", @@ -22,6 +22,7 @@ rr_diabetes_duration_greater_than_15,0.8,universal,0,1, prob_antivegf_success_clinically_significant,0.7,universal,0,1, prob_focal_laser_success_clinically_significant,0.5,universal,0,1, prob_laser_prc_success_proliferative,0.6,universal,0,1, +prob_antivegf_for_clinically_significant_dmo,0.5,local,0,1, rr_progression_after_treatment,0.5,universal,0,1, vision_transition_matrix_no_dr,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", vision_transition_matrix_sight_threatening,"[[0.970,0.025,0.005,0], [0.030,0.920,0.045,0.005], [0,0.050,0.890,0.060], [0,0,0.060,0.940]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", diff --git a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv index df45d4912d..7f61ba8c4b 100644 --- a/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv +++ b/resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv @@ -1,101 +1,101 @@ Intervention_Cat,Intervention_Pkg,Intervention_Pkg_Code,Items,Item_Code,Expected_Units_Per_Case,Unit_Cost Maternal/Newborn and Reproductive Health,Pill,0,"Levonorgestrel 0.0375 mg, cycle",0,7.5,48.25212 Maternal/Newborn and Reproductive Health,Pill,0,"Levonorgestrel 0.15 mg + Ethinyl estradiol 30 mcg (Microgynon), cycle",1,7.5,53.35008 -Maternal/Newborn and Reproductive Health,Male condom,1,"Condom, male",2,120.0,20.97018 -Maternal/Newborn and Reproductive Health,Injectable,2,Depot-Medroxyprogesterone Acetate 150 mg - 3 monthly,3,4.0,50.9439 -Maternal/Newborn and Reproductive Health,Injectable,2,"Gloves, exam, latex, disposable, pair",4,4.0,31.90866 -Maternal/Newborn and Reproductive Health,Injectable,2,"Povidone iodine, solution, 10 %, 5 ml per injection",5,4.0,2.00634 -Maternal/Newborn and Reproductive Health,Injectable,2,"Syringe, Autodisable SoloShot IX ",6,4.0,5.4264 -Maternal/Newborn and Reproductive Health,IUD,3,"Gloves, exam, latex, disposable, pair",4,3.0,31.90866 -Maternal/Newborn and Reproductive Health,IUD,3,"IUD, Copper T-380A",7,1.0,19.39224 -Maternal/Newborn and Reproductive Health,Implant,4,"Gloves, exam, latex, disposable, pair",4,2.0,31.90866 -Maternal/Newborn and Reproductive Health,Implant,4,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,2.0,52.00062 -Maternal/Newborn and Reproductive Health,Implant,4,"Povidone iodine, solution, 10 %, 5 ml per injection",5,2.0,2.00634 -Maternal/Newborn and Reproductive Health,Implant,4,"Syringe, needle + swab",9,2.0,7.7469 +Maternal/Newborn and Reproductive Health,Male condom,1,"Condom, male",2,120,20.97018 +Maternal/Newborn and Reproductive Health,Injectable,2,Depot-Medroxyprogesterone Acetate 150 mg - 3 monthly,3,4,50.9439 +Maternal/Newborn and Reproductive Health,Injectable,2,"Gloves, exam, latex, disposable, pair",4,4,31.90866 +Maternal/Newborn and Reproductive Health,Injectable,2,"Povidone iodine, solution, 10 %, 5 ml per injection",5,4,2.00634 +Maternal/Newborn and Reproductive Health,Injectable,2,"Syringe, Autodisable SoloShot IX ",6,4,5.4264 +Maternal/Newborn and Reproductive Health,IUD,3,"Gloves, exam, latex, disposable, pair",4,3,31.90866 +Maternal/Newborn and Reproductive Health,IUD,3,"IUD, Copper T-380A",7,1,19.39224 +Maternal/Newborn and Reproductive Health,Implant,4,"Gloves, exam, latex, disposable, pair",4,2,31.90866 +Maternal/Newborn and Reproductive Health,Implant,4,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,2,52.00062 +Maternal/Newborn and Reproductive Health,Implant,4,"Povidone iodine, solution, 10 %, 5 ml per injection",5,2,2.00634 +Maternal/Newborn and Reproductive Health,Implant,4,"Syringe, needle + swab",9,2,7.7469 Maternal/Newborn and Reproductive Health,Implant,4,Trocar,10,0.1,1203.99678 Maternal/Newborn and Reproductive Health,Implant,4,Needle suture intestinal round bodied ½ circle trocar_6_CMST,11,0.2,115.99644 Maternal/Newborn and Reproductive Health,Implant,4,"Jadelle (implant), box of 2_CMST",12,0.5,447.22104 Maternal/Newborn and Reproductive Health,Implant,4,Implanon (Etonogestrel 68 mg),13,0.5,484.97022 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Atropine sulphate, injection, 1 mg in 1 ml ampoule",14,1.0,17.99994 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Diazepam, injection, 5 mg/ml, in 2 ml ampoule",15,1.0,130.47636 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Lidocaine, injection, 1 % in 20 ml vial",16,1.0,149.99712 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Atropine sulphate, injection, 1 mg in 1 ml ampoule",14,1,17.99994 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Diazepam, injection, 5 mg/ml, in 2 ml ampoule",15,1,130.47636 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Lidocaine, injection, 1 % in 20 ml vial",16,1,149.99712 Maternal/Newborn and Reproductive Health,Female sterilization,5,"Lidocaine, spray, 10%, 500 ml bottle",17,0.02,1244.0022 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Syringe, needle + swab",9,3.0,7.7469 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Gauze pad, 10 x 10 cm, sterile",18,2.0,14.72268 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Needle, suture, assorted sizes, round body",19,3.0,600.00276 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Suture, catgut, chromic, 0, 150 cm",20,3.0,3744.0018 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Tape, adhesive, 2.5 cm wide, zinc oxide, 5 m roll",21,1.0,426.10092 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,2.0,137.45928 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Paracetamol, tablet, 500 mg",23,8.0,4.3554 -Maternal/Newborn and Reproductive Health,Female sterilization,5,"Povidone iodine, solution, 10 %, 5 ml per injection",5,2.0,2.00634 -Maternal/Newborn and Reproductive Health,Female sterilization,5,Cotton swab,24,2.0,1.9992 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Gauze pad, 10 x 10 cm, sterile",18,1.0,14.72268 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,1.0,137.45928 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Lidocaine, injection, 1 % in 20 ml vial",16,1.0,149.99712 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Needle, suture, assorted sizes, round body",19,1.0,600.00276 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Povidone iodine, solution, 10 %, 5 ml per injection",5,1.0,2.00634 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Suture, catgut, chromic, 0, 150 cm",20,1.0,3744.0018 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Syringe, needle + swab",9,1.0,7.7469 -Maternal/Newborn and Reproductive Health,Male sterilization,6,"Tape, adhesive, 2.5 cm wide, zinc oxide, 5 m roll",21,1.0,426.10092 -Maternal/Newborn and Reproductive Health,Female Condom,7,Female Condom_Each_CMST,25,120.0,33.72222 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Misoprostol, tablet, 200 mcg",26,4.0,132.33276 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Paracetamol, tablet, 500 mg",23,9.0,4.3554 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Ampicillin, powder for injection, 500 mg, vial",27,24.0,118.4526 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,6.0,41.74758 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Metronidazole, injection, 500 mg in 100 ml vial",29,8.0,51.48654 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Tetracycline, tablet, 500 mg",30,40.0,0.9996 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,1.0,52.00062 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Misoprostol, tablet, 200 mcg",26,2.0,132.33276 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Syringe, needle + swab",9,1.0,7.7469 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Methylergometrine, Injection 0.2 mg/ml, 1 ml amp",31,3.0,14.00154 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Paracetamol, tablet, 500 mg",23,12.0,4.3554 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Pethidine, 50 mg/ml, 2 ml ampoule",32,2.0,522.77652 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2.0,840.29946 -Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2.0,840.29946 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,1.0,52.00062 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,2.0,808.94772 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Syringe, needle + swab",9,3,7.7469 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Gauze pad, 10 x 10 cm, sterile",18,2,14.72268 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Needle, suture, assorted sizes, round body",19,3,600.00276 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Suture, catgut, chromic, 0, 150 cm",20,3,3744.0018 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Tape, adhesive, 2.5 cm wide, zinc oxide, 5 m roll",21,1,426.10092 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,2,137.45928 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Paracetamol, tablet, 500 mg",23,8,4.3554 +Maternal/Newborn and Reproductive Health,Female sterilization,5,"Povidone iodine, solution, 10 %, 5 ml per injection",5,2,2.00634 +Maternal/Newborn and Reproductive Health,Female sterilization,5,Cotton swab,24,2,1.9992 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Gauze pad, 10 x 10 cm, sterile",18,1,14.72268 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,1,137.45928 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Lidocaine, injection, 1 % in 20 ml vial",16,1,149.99712 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Needle, suture, assorted sizes, round body",19,1,600.00276 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Povidone iodine, solution, 10 %, 5 ml per injection",5,1,2.00634 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Suture, catgut, chromic, 0, 150 cm",20,1,3744.0018 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Syringe, needle + swab",9,1,7.7469 +Maternal/Newborn and Reproductive Health,Male sterilization,6,"Tape, adhesive, 2.5 cm wide, zinc oxide, 5 m roll",21,1,426.10092 +Maternal/Newborn and Reproductive Health,Female Condom,7,Female Condom_Each_CMST,25,120,33.72222 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Misoprostol, tablet, 200 mcg",26,4,132.33276 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Paracetamol, tablet, 500 mg",23,9,4.3554 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Ampicillin, powder for injection, 500 mg, vial",27,24,118.4526 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,6,41.74758 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Metronidazole, injection, 500 mg in 100 ml vial",29,8,51.48654 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Tetracycline, tablet, 500 mg",30,40,0.9996 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,1,52.00062 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Misoprostol, tablet, 200 mcg",26,2,132.33276 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Syringe, needle + swab",9,1,7.7469 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Methylergometrine, Injection 0.2 mg/ml, 1 ml amp",31,3,14.00154 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Paracetamol, tablet, 500 mg",23,12,4.3554 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Pethidine, 50 mg/ml, 2 ml ampoule",32,2,522.77652 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2,840.29946 +Maternal/Newborn and Reproductive Health,Post-abortion case management,8,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2,840.29946 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,1,52.00062 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,2,808.94772 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Syringe, needle + swab",9,0.1,7.7469 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Epinephrine, ampoule, 1 mg/ml",36,0.1,82.0029 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Suture, absorbable, synthetic, 2/0, curved needle",37,0.01,75.99816 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Suture, catgut, chromic, 0, 150 cm",20,0.01,3744.0018 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Suture, non-absorbable, synthetic, 3/0, curved needle",38,0.01,1699.9983 Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Gauze pad, 10 x 10 cm, sterile",18,0.03,14.72268 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Ampicillin, powder for injection, 500 mg, vial",27,64.0,118.4526 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,12.0,41.74758 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Metronidazole, injection, 500 mg in 100 ml vial",29,12.0,51.48654 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,8.0,840.29946 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Paracetamol, tablet, 500 mg",23,12.0,4.3554 -Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Pethidine, 50 mg/ml, 2 ml ampoule",32,2.0,522.77652 -Maternal/Newborn and Reproductive Health,Tetanus toxoid (pregnant women),10,"Tetanus toxoid, injection",39,2.0,13.00194 -Maternal/Newborn and Reproductive Health,Tetanus toxoid (pregnant women),10,"Syringe, needle + swab",9,2.0,7.7469 -Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Blood collecting tube, 5 ml",40,1.0,122.42958 -Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Gloves, exam, latex, disposable, pair",4,1.0,31.90866 -Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Syringe, needle + swab",9,1.0,7.7469 -Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Test, Rapid plasma reagin (RPR)",41,1.0,66.4377 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Ampicillin, powder for injection, 500 mg, vial",27,64,118.4526 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,12,41.74758 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Metronidazole, injection, 500 mg in 100 ml vial",29,12,51.48654 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,8,840.29946 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Paracetamol, tablet, 500 mg",23,12,4.3554 +Maternal/Newborn and Reproductive Health,Ectopic case management,9,"Pethidine, 50 mg/ml, 2 ml ampoule",32,2,522.77652 +Maternal/Newborn and Reproductive Health,Tetanus toxoid (pregnant women),10,"Tetanus toxoid, injection",39,2,13.00194 +Maternal/Newborn and Reproductive Health,Tetanus toxoid (pregnant women),10,"Syringe, needle + swab",9,2,7.7469 +Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Blood collecting tube, 5 ml",40,1,122.42958 +Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Gloves, exam, latex, disposable, pair",4,1,31.90866 +Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Syringe, needle + swab",9,1,7.7469 +Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Test, Rapid plasma reagin (RPR)",41,1,66.4377 Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Benzathine benzylpenicillin, powder for injection, 2.4 million IU",42,0.2,484.07058 Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Syringe, needle + swab",9,0.2,7.7469 Maternal/Newborn and Reproductive Health,Syphilis detection and treatment (pregnant women),11,"Water for injection, 5 ml ampoule",43,0.2,25.8111 -Maternal/Newborn and Reproductive Health,Basic ANC,12,Ferrous sulphate 200mg _1000_CMST,44,0.0,1791.21894 -Maternal/Newborn and Reproductive Health,Basic ANC,12,Albendazole 200mg_1000_CMST,45,0.0,6375.6987 -Maternal/Newborn and Reproductive Health,Basic ANC,12,Carbon antigen VDRL 10ml_each_CMST,46,1.0,1942.00146 -Maternal/Newborn and Reproductive Health,Basic ANC,12,Urine analysis,47,4.0,627.9987 -Maternal/Newborn and Reproductive Health,Basic ANC,12,HIV EIA Elisa test,48,0.0,120.35898 +Maternal/Newborn and Reproductive Health,Basic ANC,12,Ferrous sulphate 200mg _1000_CMST,44,0,1791.21894 +Maternal/Newborn and Reproductive Health,Basic ANC,12,Albendazole 200mg_1000_CMST,45,0,6375.6987 +Maternal/Newborn and Reproductive Health,Basic ANC,12,Carbon antigen VDRL 10ml_each_CMST,46,1,1942.00146 +Maternal/Newborn and Reproductive Health,Basic ANC,12,Urine analysis,47,4,627.9987 +Maternal/Newborn and Reproductive Health,Basic ANC,12,HIV EIA Elisa test,48,0,120.35898 Maternal/Newborn and Reproductive Health,Basic ANC,12,"Cotton wool, 500g_1_CMST",49,0.001,416.99742 -Maternal/Newborn and Reproductive Health,Basic ANC,12,Haemoglobin test (HB),50,1.0,78.99696 -Maternal/Newborn and Reproductive Health,Hypertensive disorder case management,13,Proteinuria test (dipstick),51,5.0,3.9984 +Maternal/Newborn and Reproductive Health,Basic ANC,12,Haemoglobin test (HB),50,1,78.99696 +Maternal/Newborn and Reproductive Health,Hypertensive disorder case management,13,Proteinuria test (dipstick),51,5,3.9984 Maternal/Newborn and Reproductive Health,Deworming (pregnant women),14,"Albendazole, tablet, 400 mg",52,0.25,63.7602 Maternal/Newborn and Reproductive Health,Deworming (pregnant women),14,"Mebendazole, chewable tablet, 500 mg",53,0.25,18.98526 Maternal/Newborn and Reproductive Health,Deworming (pregnant women),14,"Praziquantel, 600 mg",54,0.75,2.8203 Maternal/Newborn and Reproductive Health,Deworming (pregnant women),14,"Levamisole, 80 mg",55,1.5,9.48906 -Maternal/Newborn and Reproductive Health,Active management of the 3rd stage of labour,15,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1.0,39.24144 -Maternal/Newborn and Reproductive Health,Active management of the 3rd stage of labour,15,"Syringe, needle + swab",9,1.0,7.7469 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Bag, urine, collecting, 2000 ml",57,1.0,157.40844 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,Foley catheter,58,1.0,306.44166 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Test strips, urine analysis",59,8.0,3.9984 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Hydralazine, powder for injection, 20 mg ampoule",60,1.0,676.85058 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,1.0,808.94772 +Maternal/Newborn and Reproductive Health,Active management of the 3rd stage of labour,15,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1,39.24144 +Maternal/Newborn and Reproductive Health,Active management of the 3rd stage of labour,15,"Syringe, needle + swab",9,1,7.7469 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Bag, urine, collecting, 2000 ml",57,1,157.40844 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,Foley catheter,58,1,306.44166 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Test strips, urine analysis",59,8,3.9984 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Hydralazine, powder for injection, 20 mg ampoule",60,1,676.85058 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,1,808.94772 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Misoprostol, tablet, 200 mcg",26,0.8,132.33276 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,0.8,39.24144 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,0.4,840.29946 @@ -106,15 +106,15 @@ Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Water for i Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Test strips, urine analysis",59,2.5,3.9984 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.1,52.00062 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.1,439.38132 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.6000000000000001,52.00062 -Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.6000000000000001,439.38132 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.6,52.00062 +Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.6,439.38132 Maternal/Newborn and Reproductive Health,Management of eclampsia,16,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.1,439.38132 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Bag, urine, collecting, 2000 ml",57,1.0,157.40844 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,Foley catheter,58,1.0,306.44166 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Test strips, urine analysis",59,8.0,3.9984 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Hydralazine, powder for injection, 20 mg ampoule",60,1.0,676.85058 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,1.0,808.94772 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Bag, urine, collecting, 2000 ml",57,1,157.40844 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,Foley catheter,58,1,306.44166 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Test strips, urine analysis",59,8,3.9984 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Hydralazine, powder for injection, 20 mg ampoule",60,1,676.85058 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,1,808.94772 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Misoprostol, tablet, 200 mcg",26,0.8,132.33276 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,0.8,39.24144 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,0.4,840.29946 @@ -125,12 +125,12 @@ Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Water f Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Test strips, urine analysis",59,2.5,3.9984 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.1,52.00062 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.1,439.38132 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.6000000000000001,52.00062 -Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.6000000000000001,439.38132 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.6,52.00062 +Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.6,439.38132 Maternal/Newborn and Reproductive Health,Management of pre-eclampsia,17,"Magnesium sulfate, injection, 500 mg/ml in 10-ml ampoule",61,0.1,439.38132 Maternal/Newborn and Reproductive Health,Neonatal resuscitation (institutional),18,"Resuscitator,hand-oper.,infant/child,set",63,0.005,0 -Maternal/Newborn and Reproductive Health,Neonatal resuscitation (institutional),18,"Infant resuscitator, clear plastic + mask + bag_each_CMST",64,1.0,5892.34212 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,4.0,137.45928 +Maternal/Newborn and Reproductive Health,Neonatal resuscitation (institutional),18,"Infant resuscitator, clear plastic + mask + bag_each_CMST",64,1,5892.34212 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,4,137.45928 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"IV giving/infusion set, with needle",34,0.9,231.84294 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Lidocaine HCl (in dextrose 7.5%), ampoule 2 ml",8,0.9,52.00062 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,1.8,808.94772 @@ -143,182 +143,182 @@ Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"IV Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,0.2,808.94772 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Syringe, needle + swab",9,0.2,7.7469 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Ketamine, 10 ml vial, 50 mg/ml",65,0.1,607.12848 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Ampicillin, powder for injection, 500 mg, vial",27,0.0,118.4526 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Cefazolin, ampoule, 500 mg",66,4.0,20.2419 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Bag, urine, collecting, 2000 ml",57,1.0,157.40844 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,Foley catheter,58,1.0,306.44166 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gauze pad, 10 x 10 cm, sterile",18,5.0,14.72268 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Needle, suture, assorted sizes, round body",19,3.0,600.00276 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Povidone iodine, solution, 10 %, 5 ml per injection",5,1.0,2.00634 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Suture, catgut, chromic, 0, 150 cm",20,1.0,3744.0018 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Suture, non-absorbable, synthetic, 3/0, curved needle",38,1.0,1699.9983 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Blade, surgical, no. 22, sterile, disposable",67,1.0,39.85548 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Ampicillin, powder for injection, 500 mg, vial",27,16.0,118.4526 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,7.0,41.74758 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Ampicillin, powder for injection, 500 mg, vial",27,0,118.4526 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Cefazolin, ampoule, 500 mg",66,4,20.2419 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Bag, urine, collecting, 2000 ml",57,1,157.40844 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,Foley catheter,58,1,306.44166 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gauze pad, 10 x 10 cm, sterile",18,5,14.72268 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Needle, suture, assorted sizes, round body",19,3,600.00276 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Povidone iodine, solution, 10 %, 5 ml per injection",5,1,2.00634 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Suture, catgut, chromic, 0, 150 cm",20,1,3744.0018 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Suture, non-absorbable, synthetic, 3/0, curved needle",38,1,1699.9983 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Blade, surgical, no. 22, sterile, disposable",67,1,39.85548 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Ampicillin, powder for injection, 500 mg, vial",27,16,118.4526 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,7,41.74758 Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"IV giving/infusion set, with needle",34,0.25,231.84294 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Metronidazole, injection, 500 mg in 100 ml vial",29,3.0,51.48654 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2.0,840.29946 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,2.0,39.24144 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Paracetamol, tablet, 500 mg",23,12.0,4.3554 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Pethidine, 50 mg/ml, 2 ml ampoule",32,1.0,522.77652 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,8.0,808.94772 -Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Syringe, needle + swab",9,1.0,7.7469 -Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Gloves, exam, latex, disposable, pair",4,2.0,31.90866 -Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Tetracycline eye ointment, 1 %, tube 5 mg",68,0.9000000000000001,31.68018 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Metronidazole, injection, 500 mg in 100 ml vial",29,3,51.48654 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,2,840.29946 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,2,39.24144 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Paracetamol, tablet, 500 mg",23,12,4.3554 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Pethidine, 50 mg/ml, 2 ml ampoule",32,1,522.77652 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,8,808.94772 +Maternal/Newborn and Reproductive Health,Management of obstructed labour,19,"Syringe, needle + swab",9,1,7.7469 +Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Gloves, exam, latex, disposable, pair",4,2,31.90866 +Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Tetracycline eye ointment, 1 %, tube 5 mg",68,0.9,31.68018 Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Gentian violet, powder 25 mg",69,0.1,992.90268 -Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Amoxicillin, powder/oral suspension, 125 mg/5 ml",70,1.0,3.9984 -Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,1.0,869.28072 +Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,"Amoxicillin, powder/oral suspension, 125 mg/5 ml",70,1,3.9984 +Maternal/Newborn and Reproductive Health,Treatment of local infections (newborn),20,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,1,869.28072 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Glove disposable powdered latex large_100_CMST,72,0.3,50.32986 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Iodine strong 10% solution_500ml_CMST,73,0.1,1641.60024 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Chlorhexidine 1.5% solution_5_CMST,74,0.04,12183.18906 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,0.1,17.14314 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1.0,39.24144 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1,39.24144 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Scalpel blade size 22 (individually wrapped)_100_CMST,76,0.1,3985.34808 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Catgut chromic 1 needle round bodied ½ circle 50mm_12_CMST,77,1.0,600.00276 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Catgut chromic 1 needle round bodied ½ circle 50mm_12_CMST,77,1,600.00276 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"suture Vicryl® (2/0) 70cm + 1/2 rb ndl 26mm, V317H_36_IDA",78,0.08333,20999.99664 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Cannula iv (winged with injection pot) 20_each_CMST,79,2.0,118.43832 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1.0,43.99668 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Cannula iv (winged with injection pot) 20_each_CMST,79,2,118.43832 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1,43.99668 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Gauze pad, 10 x 10 cm, sterile",18,0.3,14.72268 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Ceftriaxone 1g, PFR_each_CMST",81,2.0,207.10998 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1.0,115.99644 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Pethidine hydrochloride 50mg/1ml, 2ml_each_CMST",83,2.0,522.77652 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Declofenac injection_each_CMST,84,14.0,20.99874 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Ceftriaxone 1g, PFR_each_CMST",81,2,207.10998 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1,115.99644 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Pethidine hydrochloride 50mg/1ml, 2ml_each_CMST",83,2,522.77652 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Declofenac injection_each_CMST,84,14,20.99874 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Plaster, elastic adhesive 10cm x 5m_each_CMST",85,0.05,539.07 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Ampicillin injection 500mg, PFR_each_CMST",86,2.0,118.4526 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Cotton wool, 500g_1_CMST",49,1.0,416.99742 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Diazepam 5mg/ml, 2ml_each_CMST",87,1.0,130.47636 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Ampicillin injection 500mg, PFR_each_CMST",86,2,118.4526 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Cotton wool, 500g_1_CMST",49,1,416.99742 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Diazepam 5mg/ml, 2ml_each_CMST",87,1,130.47636 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"surgical face mask, disp., with metal nose piece_50_IDA",88,0.1,833.00238 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Glove surgeon's size 8 sterile_2_CMST,89,7.0,273.7476 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Glove surgeon's size 8 sterile_2_CMST,89,7,273.7476 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Halothane (fluothane)_250ml_CMST,90,0.2,21517.04688 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Ketamine, 10 ml vial, 50 mg/ml",65,0.04,607.12848 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Lignocaine hydrochloride 5%+glucose 7.5%,heavy spinal,2ml_each_CMST",91,0.9,451.31226 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Metronidazole 200mg_1000_CMST,92,0.001,5271.83328 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Saline solution,93,4.0,135.00312 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Saline solution,93,4,135.00312 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Paracetamol 500mg _1000_CMST,94,0.018,4353.87918 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Needle spinal disposable Luer 22g x 10cm cutting bevel/pencil point_each_CMST,95,0.9,249.02178 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Suture, catgut, chromic, 0, 150 cm",20,0.0,3744.0018 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Suture, non-absorbable, synthetic, 1/0, curved needle",96,1.0,35.00028 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Suture, catgut, chromic, 0, 150 cm",20,0,3744.0018 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Suture, non-absorbable, synthetic, 1/0, curved needle",96,1,35.00028 Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,Catgut chromic 0 needle round bodied ½ circle 40mm_12_CMST,97,0.16667,3744.0018 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Water for injection, 10ml_Each_CMST",98,1.0,32.57268 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Benzylpenicillin 3g (5MU), PFR_each_CMST",99,1.0,194.6007 -Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2.0,182.91252 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Iodine strong 10% solution_500ml_CMST,73,0.0,1641.60024 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Water for injection, 10ml_Each_CMST",98,1,32.57268 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Benzylpenicillin 3g (5MU), PFR_each_CMST",99,1,194.6007 +Maternal/Newborn and Reproductive Health,Cesearian section with indication,21,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2,182.91252 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Iodine strong 10% solution_500ml_CMST,73,0,1641.60024 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Chlorhexidine 1.5% solution_5_CMST,74,0.004,12183.18906 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gauze, absorbent 90cm x 40m_each_CMST",101,1.0,5650.6317 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Oxytocin 10 IU/ml, 1ml_each_CMST",102,0.0,39.24144 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gauze, absorbent 90cm x 40m_each_CMST",101,1,5650.6317 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Oxytocin 10 IU/ml, 1ml_each_CMST",102,0,39.24144 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Glove disposable powdered latex large_100_CMST,72,0.3,50.32986 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Scalpel blade size 22 (individually wrapped)_100_CMST,76,0.01,3985.34808 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Catgut chromic 1 needle round bodied ½ circle 50mm_12_CMST,77,0.1,600.00276 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Bandage, plaster of paris 15cm_12_CMST",103,0.33,1688.0031 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"suture Vicryl® (2/0) 70cm + 1/2 rb ndl 26mm, V317H_36_IDA",78,0.0,20999.99664 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Plaster, elastic adhesive 10cm x 5m_each_CMST",85,6.0,539.07 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Cannula iv (winged with injection pot) 14_each_CMST,104,2.0,102.00204 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1.0,43.99668 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gauze pad, 10 x 10 cm, sterile",18,12.0,14.72268 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Ceftriaxone 1g, PFR_each_CMST",81,2.0,207.10998 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1.0,115.99644 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Pethidine, 50 mg/ml, 2 ml ampoule",32,12.0,522.77652 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Declofenac injection_each_CMST,84,14.0,20.99874 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2.0,182.91252 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Metronidazole 5mg/ml, 100ml_each_CMST",105,6.0,215.34954 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Ampicillin injection 500mg, PFR_each_CMST",86,12.0,118.4526 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gentamicin Sulphate 40mg/ml, 2ml_each_CMST",106,12.0,27.00348 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"suture Vicryl® (2/0) 70cm + 1/2 rb ndl 26mm, V317H_36_IDA",78,0,20999.99664 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Plaster, elastic adhesive 10cm x 5m_each_CMST",85,6,539.07 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Cannula iv (winged with injection pot) 14_each_CMST,104,2,102.00204 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1,43.99668 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gauze pad, 10 x 10 cm, sterile",18,12,14.72268 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Ceftriaxone 1g, PFR_each_CMST",81,2,207.10998 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1,115.99644 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Pethidine, 50 mg/ml, 2 ml ampoule",32,12,522.77652 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Declofenac injection_each_CMST,84,14,20.99874 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2,182.91252 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Metronidazole 5mg/ml, 100ml_each_CMST",105,6,215.34954 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Ampicillin injection 500mg, PFR_each_CMST",86,12,118.4526 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Gentamicin Sulphate 40mg/ml, 2ml_each_CMST",106,12,27.00348 Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,Metronidazole 200mg_1000_CMST,92,1.764,5271.83328 -Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Syringe, 5ml, disposable, hypoluer with 21g needle_each_CMST",107,40.0,149.98284 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Glove disposable powdered latex large_100_CMST,72,2.0,50.32986 +Maternal/Newborn and Reproductive Health,Cesearian Section with indication (with complication),22,"Syringe, 5ml, disposable, hypoluer with 21g needle_each_CMST",107,40,149.98284 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Glove disposable powdered latex large_100_CMST,72,2,50.32986 Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,0.2,17.14314 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Cotton swab,24,20.0,1.9992 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"umbilical cord clamp, disposable_50_IDA",108,1.0,26.26806 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Cotton swab,24,20,1.9992 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"umbilical cord clamp, disposable_50_IDA",108,1,26.26806 Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Filter paper No. 1_100_CMST,109,0.01,370.00194 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Apron, disposable, polythene_100_CMST",110,1.0,74.19888 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Oxytocin 10 IU/ml, 1ml_each_CMST",102,1.0,39.24144 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,1.0,182.94822 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Apron, disposable, polythene_100_CMST",110,1,74.19888 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Oxytocin 10 IU/ml, 1ml_each_CMST",102,1,39.24144 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,1,182.94822 Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Chlorhexidine 1.5% solution_5_CMST,74,0.1,12183.18906 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Cannula iv (winged with injection pot) 20_each_CMST,79,1.0,118.43832 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Cotton wool, 500g_1_CMST",49,1.0,416.99742 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Cannula iv (winged with injection pot) 20_each_CMST,79,1,118.43832 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Cotton wool, 500g_1_CMST",49,1,416.99742 Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"surgical face mask, disp., with metal nose piece_50_IDA",88,0.02,833.00238 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Ampicillin injection 500mg, PFR_each_CMST",86,2.0,118.4526 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Glove surgeon's size 7 sterile_2_CMST,112,4.0,137.45928 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Paracetamol 500mg_1000_CMST,113,1.0,4.16262 -Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Catheter Foley's suction 53cm FG 10_each_CMST,114,1.0,71.99976 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Cannula iv (winged with injection pot) 20_each_CMST,79,2.0,118.43832 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,"Ampicillin injection 500mg, PFR_each_CMST",86,2,118.4526 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Glove surgeon's size 7 sterile_2_CMST,112,4,137.45928 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Paracetamol 500mg_1000_CMST,113,1,4.16262 +Maternal/Newborn and Reproductive Health,Vaginal delivery - skilled attendance,23,Catheter Foley's suction 53cm FG 10_each_CMST,114,1,71.99976 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Cannula iv (winged with injection pot) 20_each_CMST,79,2,118.43832 Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Glove disposable powdered latex large_100_CMST,72,0.2,50.32986 Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,0.3,17.14314 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Cotton swab,24,20.0,1.9992 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"umbilical cord clamp, disposable_50_IDA",108,1.0,26.26806 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Apron, disposable, polythene_100_CMST",110,1.0,74.19888 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,5.0,39.24144 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,4.0,182.94822 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Cotton swab,24,20,1.9992 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"umbilical cord clamp, disposable_50_IDA",108,1,26.26806 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Apron, disposable, polythene_100_CMST",110,1,74.19888 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,5,39.24144 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,4,182.94822 Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Chlorhexidine 1.5% solution_5_CMST,74,0.01,12183.18906 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Needle suture abdominal straight 10cm_6_CMST,115,2.0,115.99644 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Needle suture abdominal straight 10cm_6_CMST,115,2,115.99644 Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Bandage, plaster of paris 15cm_12_CMST",103,0.2,1688.0031 Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,0.1,216.45624 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1.0,115.99644 -Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Pethidine hydrochloride 50mg/1ml, 2ml_each_CMST",83,1.0,522.77652 -Maternal/Newborn and Reproductive Health,Clean practices and immediate essential newborn care (in facility),25,Clean delivery kit,117,1.0,977.63736 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Dexamethasone, 1 ml injection, 4 mg/ml",118,6.0,128.72706 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,4.0,840.29946 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Syringe, needle + swab",9,2.0,7.7469 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Nifedipine,119,4.0,9.91032 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Cannula iv (winged with injection pot) 16_each_CMST,120,1.0,77.34048 -Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Saline solution,93,1.0,135.00312 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,Catheter Foley's + urine bag (2000ml) 14g_each_CMST,82,1,115.99644 +Maternal/Newborn and Reproductive Health,Vaginal Delivery - with complication,24,"Pethidine hydrochloride 50mg/1ml, 2ml_each_CMST",83,1,522.77652 +Maternal/Newborn and Reproductive Health,Clean practices and immediate essential newborn care (in facility),25,Clean delivery kit,117,1,977.63736 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Dexamethasone, 1 ml injection, 4 mg/ml",118,6,128.72706 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,4,840.29946 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,"Syringe, needle + swab",9,2,7.7469 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Nifedipine,119,4,9.91032 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Cannula iv (winged with injection pot) 16_each_CMST,120,1,77.34048 +Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Saline solution,93,1,135.00312 Maternal/Newborn and Reproductive Health,Antenatal corticosteroids for preterm labour,26,Salbutamol 4mg_1000_CMST,121,0.03,2.76318 -Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Amoxicillin, caplet, 250 mg",122,33.60000000000001,1.9992 -Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Erythromycin, tablet, 250 mg",123,5.6000000000000005,5.9976 -Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,Metronidazole 200mg_1000_CMST,92,1.0,5271.83328 -Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Ampicillin injection 500mg, PFR_each_CMST",86,2.0,118.4526 -Maternal/Newborn and Reproductive Health,Induction of labour (beyond 41 weeks),28,"Misoprostol, tablet, 200 mcg",26,1.0,132.33276 -Maternal/Newborn and Reproductive Health,Induction of labour (beyond 41 weeks),28,Induction of labour (beyond 41 weeks) drugs/supplies to service a client,124,1.0,0 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Ampicillin, powder for injection, 500 mg, vial",27,64.0,118.4526 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,9.0,41.74758 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Metronidazole, injection, 500 mg in 100 ml vial",29,12.0,51.48654 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Syringe, needle + swab",9,64.0,7.7469 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Water for injection, 5 ml ampoule",43,64.0,25.8111 +Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Amoxicillin, caplet, 250 mg",122,33.6,1.9992 +Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Erythromycin, tablet, 250 mg",123,5.6,5.9976 +Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,Metronidazole 200mg_1000_CMST,92,1,5271.83328 +Maternal/Newborn and Reproductive Health,Antibiotics for pPRoM,27,"Ampicillin injection 500mg, PFR_each_CMST",86,2,118.4526 +Maternal/Newborn and Reproductive Health,Induction of labour (beyond 41 weeks),28,"Misoprostol, tablet, 200 mcg",26,1,132.33276 +Maternal/Newborn and Reproductive Health,Induction of labour (beyond 41 weeks),28,Induction of labour (beyond 41 weeks) drugs/supplies to service a client,124,1,0 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Ampicillin, powder for injection, 500 mg, vial",27,64,118.4526 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,9,41.74758 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Metronidazole, injection, 500 mg in 100 ml vial",29,12,51.48654 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Syringe, needle + swab",9,64,7.7469 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Water for injection, 5 ml ampoule",43,64,25.8111 Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Amoxycillin 250mg_1000_CMST,125,0.18,16460.99868 Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Metronidazole 200mg_1000_CMST,92,0.03,5271.83328 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Bag, urine, collecting, 2000 ml",57,1.0,157.40844 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Foley catheter,58,1.0,306.44166 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,1.0,137.45928 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Lancet, blood, disposable",126,1.0,0.9996 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Bag, urine, collecting, 2000 ml",57,1,157.40844 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Foley catheter,58,1,306.44166 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,1,137.45928 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Lancet, blood, disposable",126,1,0.9996 Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Oxygen, 1000 liters, primarily with oxygen cylinders",127,0.375,322.99932 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Paracetamol, tablet, 500 mg",23,8.0,4.3554 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,24.0,840.29946 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Complete blood count,128,1.0,378.99834 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Paracetamol, tablet, 500 mg",23,8,4.3554 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,24,840.29946 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Complete blood count,128,1,378.99834 Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Plaster, elastic adhesive 5cm x 5m_each_CMST",129,0.05,1451.99754 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Cannula iv (winged with injection pot) 16_each_CMST,120,2.0,77.34048 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gentamicin 40mg/ml, 2ml_each_CMST",130,15.0,48.14502 -Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Saline solution,93,6.0,135.00312 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Cannula iv (winged with injection pot) 16_each_CMST,120,2,77.34048 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,"Gentamicin 40mg/ml, 2ml_each_CMST",130,15,48.14502 +Maternal/Newborn and Reproductive Health,Maternal sepsis case management,29,Saline solution,93,6,135.00312 Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Cephalotin, 100 ml vial",131,1.2,125.99958 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,5.0,41.74758 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,5,41.74758 Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"IV giving/infusion set, with needle",34,0.2,231.84294 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Oxygen, 1000 liters, primarily with oxygen cylinders",127,0.0,322.99932 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Oxygen, 1000 liters, primarily with oxygen cylinders",127,0,322.99932 Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Plaster, elastic adhesive 10cm x 5m_each_CMST",85,0.0025,539.07 Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Amoxicillin, powder/oral suspension, 125 mg/5 ml",70,0.01,3.9984 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Ampicillin injection 250mg, PFR_each_CMST",132,7.0,118.4526 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,Cannula iv (winged with injection pot) 16_each_CMST,120,2.0,77.34048 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Dextrose (glucose) 5%, 1000ml_each_CMST",133,2.0,1041.19764 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Tube, feeding CH 8_each_CMST",134,1.0,401.11092 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Gentamicin 40mg/ml, 2ml_each_CMST",130,0.0,48.14502 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Ampicillin injection 250mg, PFR_each_CMST",132,7,118.4526 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,Cannula iv (winged with injection pot) 16_each_CMST,120,2,77.34048 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Dextrose (glucose) 5%, 1000ml_each_CMST",133,2,1041.19764 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Tube, feeding CH 8_each_CMST",134,1,401.11092 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Gentamicin 40mg/ml, 2ml_each_CMST",130,0,48.14502 Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Disposables gloves, powder free, 100 pieces per box",135,0.3,5032.80036 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,1.0,869.28072 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Syringes, single use, 20 ml, 100 pieces per pack",136,3.0,182.94822 -Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Water for injection, 10ml_Each_CMST",98,7.0,32.57268 -Maternal/Newborn and Reproductive Health,Newborn sepsis - injectable antibiotics,31,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,5.0,41.74758 -Maternal/Newborn and Reproductive Health,Newborn sepsis - injectable antibiotics,31,"Procaine benzylpenicillin, powder for injection, 1 g (= 1 million IU) in vial",137,1.0,320.50746 -Maternal/Newborn and Reproductive Health,Mastitis,32,"Erythromycin, tablet, 250 mg",123,40.0,5.9976 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,1,869.28072 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Syringes, single use, 20 ml, 100 pieces per pack",136,3,182.94822 +Maternal/Newborn and Reproductive Health,Newborn sepsis - full supportive care,30,"Water for injection, 10ml_Each_CMST",98,7,32.57268 +Maternal/Newborn and Reproductive Health,Newborn sepsis - injectable antibiotics,31,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,5,41.74758 +Maternal/Newborn and Reproductive Health,Newborn sepsis - injectable antibiotics,31,"Procaine benzylpenicillin, powder for injection, 1 g (= 1 million IU) in vial",137,1,320.50746 +Maternal/Newborn and Reproductive Health,Mastitis,32,"Erythromycin, tablet, 250 mg",123,40,5.9976 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Albendazole, tablet, 400 mg",52,0.25,63.7602 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Lancet, blood, disposable",126,1.0,0.9996 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Test, hemoglobin",138,1.0,0 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Saline solution,93,6.0,135.00312 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Complete blood count,128,1.0,378.99834 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Haemoglobin test (HB),50,1.0,78.99696 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Lancet, blood, disposable",126,1,0.9996 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Test, hemoglobin",138,1,0 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Saline solution,93,6,135.00312 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Complete blood count,128,1,378.99834 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Haemoglobin test (HB),50,1,78.99696 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ampicillin, powder for injection, 500 mg, vial",27,6.4,118.4526 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,1.2000000000000002,41.74758 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,1.2,41.74758 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"IV giving/infusion set, with needle",34,0.1,231.84294 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Metronidazole, injection, 500 mg in 100 ml vial",29,1.2000000000000002,51.48654 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Metronidazole, injection, 500 mg in 100 ml vial",29,1.2,51.48654 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Sodium chloride, injectable solution, 0,9 %, 500 ml",33,0.8,840.29946 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Water for injection, 5 ml ampoule",43,6.4,25.8111 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Cotton swab,24,0.5,1.9992 @@ -327,373 +327,373 @@ Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33," Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Needle, suture, assorted sizes, round body",19,1.5,600.00276 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Pethidine, 50 mg/ml, 2 ml ampoule",32,0.5,522.77652 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Povidone iodine, solution, 10 %, 5 ml per injection",5,0.5,2.00634 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Suture, catgut, chromic, 0, 150 cm",20,1.0,3744.0018 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Suture, catgut, chromic, 0, 150 cm",20,1,3744.0018 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Suture, non-absorbable, synthetic, 2/0, needle",139,0.5,34.00068 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,45.0,1.79214 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,45.0,1.79214 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,135.0,1.79214 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,3.0,39.24144 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Bag, urine, collecting, 2000 ml",57,1.0,157.40844 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,45,1.79214 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,45,1.79214 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,135,1.79214 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,3,39.24144 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Bag, urine, collecting, 2000 ml",57,1,157.40844 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Blood, one unit",141,0.5,0 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Foley catheter,58,1.0,306.44166 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,4.0,137.45928 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"IV giving/infusion set, with needle",34,1.0,231.84294 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1.0,39.24144 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,2.0,808.94772 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Syringe, needle + swab",9,1.0,7.7469 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Foley catheter,58,1,306.44166 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Gloves, surgeon’s, latex, disposable, sterile, pair",22,4,137.45928 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"IV giving/infusion set, with needle",34,1,231.84294 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Oxytocin, injection, 10 IU in 1 ml ampoule",56,1,39.24144 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Sodium lactate injection (Ringer's), 500 ml, with giving set",35,2,808.94772 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Syringe, needle + swab",9,1,7.7469 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Plaster, elastic adhesive 10cm x 5m_each_CMST",85,0.05,539.07 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Cannula iv (winged with injection pot) 16_each_CMST,120,2.0,77.34048 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,Cannula iv (winged with injection pot) 16_each_CMST,120,2,77.34048 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"surgical face mask, disp., with metal nose piece_50_IDA",88,0.06,833.00238 -Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"gauze compresses 5 x 5 cm ,12 ply, non sterile_100_IDA",142,1.0,295.00338 +Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"gauze compresses 5 x 5 cm ,12 ply, non sterile_100_IDA",142,1,295.00338 Maternal/Newborn and Reproductive Health,Treatment of postpartum hemorrhage,33,"Disposables gloves, powder free, 100 pieces per box",135,0.05,5032.80036 -Maternal/Newborn and Reproductive Health,Chlorhexidine ,34,Chlorhexidine digluconate (10 ml bottle) ,143,1.0,53.99982 -Child Health,Hand washing with soap,35,Hand washing with soap - cost per client,144,1.0,143.64966 -Child Health,Hygienic disposal of children's stools,36,Hygienic disposal of children's stools - cost per client,145,1.0,3830.7885 -Child Health,ORS,37,"ORS, sachet",146,3.0,12.00234 -Child Health,Zinc for Children 0-6 months,38,"Zinc, tablet, 20 mg",147,7.0,9.639 -Child Health,Zinc for Children 6-59 months,39,"Zinc, tablet, 20 mg",147,14.0,9.639 -Child Health,Antibiotics for treatment of dysentery,40,Ciprofloxacin 250mg_100_CMST,148,12.0,16.20066 -Child Health,Antibiotics for treatment of dysentery,40,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,6.0,869.28072 -Child Health,Treatment of severe diarrhea,41,"ORS, sachet",146,3.0,12.00234 -Child Health,Treatment of severe diarrhea,41,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1.0,43.99668 -Child Health,Treatment of severe diarrhea,41,Saline solution,93,1.0,135.00312 -Child Health,Treatment of severe diarrhea,41,Cotton swab,24,1.0,1.9992 +Maternal/Newborn and Reproductive Health,Chlorhexidine ,34,Chlorhexidine digluconate (10 ml bottle) ,143,1,53.99982 +Child Health,Hand washing with soap,35,Hand washing with soap - cost per client,144,1,143.64966 +Child Health,Hygienic disposal of children's stools,36,Hygienic disposal of children's stools - cost per client,145,1,3830.7885 +Child Health,ORS,37,"ORS, sachet",146,3,12.00234 +Child Health,Zinc for Children 0-6 months,38,"Zinc, tablet, 20 mg",147,7,9.639 +Child Health,Zinc for Children 6-59 months,39,"Zinc, tablet, 20 mg",147,14,9.639 +Child Health,Antibiotics for treatment of dysentery,40,Ciprofloxacin 250mg_100_CMST,148,12,16.20066 +Child Health,Antibiotics for treatment of dysentery,40,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,6,869.28072 +Child Health,Treatment of severe diarrhea,41,"ORS, sachet",146,3,12.00234 +Child Health,Treatment of severe diarrhea,41,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1,43.99668 +Child Health,Treatment of severe diarrhea,41,Saline solution,93,1,135.00312 +Child Health,Treatment of severe diarrhea,41,Cotton swab,24,1,1.9992 Child Health,Treatment of severe diarrhea,41,"ringer's lactate (Hartmann's solution), 1000 ml_12_IDA",149,0.08333,1309.02618 -Vaccine Preventable Diseases,Rotavirus vaccine,42,Rotavirus vaccine,150,4.0,395.97726 -Vaccine Preventable Diseases,Polio vaccine,43,Polio vaccine,151,4.0,20.66316 -Vaccine Preventable Diseases,BCG vaccine,44,BCG vaccine,152,1.0,12.03804 -Vaccine Preventable Diseases,BCG vaccine,44,"Syringe, autodisposable, BCG, 0.1 ml, with needle",153,1.0,110.96988 -Vaccine Preventable Diseases,BCG vaccine,44,"Safety box for used syringes/needles, 5 liter",154,1.0,11.45256 -Vaccine Preventable Diseases,Pneumococcal vaccine,45,Pneumococcal vaccine,155,3.0,526.56786 -Vaccine Preventable Diseases,Pneumococcal vaccine,45,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,3.0,182.91252 -Vaccine Preventable Diseases,Pneumococcal vaccine,45,"Syringe, auto-disposable, 0.5 ml, with needle",156,3.0,7.9968 -Vaccine Preventable Diseases,HPV vaccine,46,"Syringe, auto-disposable, 0.5 ml, with needle",156,3.0,7.9968 -Vaccine Preventable Diseases,HPV vaccine,46,"Safety box for used syringes/needles, 5 liter",154,3.0,11.45256 -Vaccine Preventable Diseases,HPV vaccine,46,HPV vaccine,157,3.0,151.99632 -Vaccine Preventable Diseases,Measles rubella vaccine,47,Measles vaccine,158,2.0,41.01216 -Vaccine Preventable Diseases,Measles rubella vaccine,47,"Safety box for used syringes/needles, 5 liter",154,2.0,11.45256 -Vaccine Preventable Diseases,Measles rubella vaccine,47,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2.0,182.91252 -Malaria ,Larviciding,48,Larviciding,159,1.0,256853003.4 -Malaria ,ITN distribution to pregnant women,49,Insecticide-treated net,160,0.33299999999999996,677.02194 -Malaria ,Indoor residual spraying drugs,50,Indoor residual spraying drugs/supplies to service a client,161,1.0,4998 -Malaria ,IPT (pregnant women),51,"Sulfamethoxazole + trimethropin, tablet 400 mg + 80 mg",162,6.0,21.42 -Malaria ,"Uncomplicated (adult, <36 kg) ",52,Malaria test kit (RDT),163,1.0,292.74 -Malaria ,"Uncomplicated (adult, <36 kg) ",52,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3.0,299.88 -Malaria ,"Uncomplicated (adult, <36 kg) ",52,Paracetamol 500mg_1000_CMST,113,18.0,4.16262 -Malaria ,"Uncomplicated (adult, >36 kg)",53,Malaria test kit (RDT),163,1.0,292.74 +Vaccine Preventable Diseases,Rotavirus vaccine,42,Rotavirus vaccine,150,4,395.97726 +Vaccine Preventable Diseases,Polio vaccine,43,Polio vaccine,151,4,20.66316 +Vaccine Preventable Diseases,BCG vaccine,44,BCG vaccine,152,1,12.03804 +Vaccine Preventable Diseases,BCG vaccine,44,"Syringe, autodisposable, BCG, 0.1 ml, with needle",153,1,110.96988 +Vaccine Preventable Diseases,BCG vaccine,44,"Safety box for used syringes/needles, 5 liter",154,1,11.45256 +Vaccine Preventable Diseases,Pneumococcal vaccine,45,Pneumococcal vaccine,155,3,526.56786 +Vaccine Preventable Diseases,Pneumococcal vaccine,45,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,3,182.91252 +Vaccine Preventable Diseases,Pneumococcal vaccine,45,"Syringe, auto-disposable, 0.5 ml, with needle",156,3,7.9968 +Vaccine Preventable Diseases,HPV vaccine,46,"Syringe, auto-disposable, 0.5 ml, with needle",156,3,7.9968 +Vaccine Preventable Diseases,HPV vaccine,46,"Safety box for used syringes/needles, 5 liter",154,3,11.45256 +Vaccine Preventable Diseases,HPV vaccine,46,HPV vaccine,157,3,151.99632 +Vaccine Preventable Diseases,Measles rubella vaccine,47,Measles vaccine,158,2,41.01216 +Vaccine Preventable Diseases,Measles rubella vaccine,47,"Safety box for used syringes/needles, 5 liter",154,2,11.45256 +Vaccine Preventable Diseases,Measles rubella vaccine,47,"Syringe, 50ml, disposable, with 19g needle_each_CMST",100,2,182.91252 +Malaria ,Larviciding,48,Larviciding,159,1,256853003.4 +Malaria ,ITN distribution to pregnant women,49,Insecticide-treated net,160,0.333,677.02194 +Malaria ,Indoor residual spraying drugs,50,Indoor residual spraying drugs/supplies to service a client,161,1,4998 +Malaria ,IPT (pregnant women),51,"Sulfamethoxazole + trimethropin, tablet 400 mg + 80 mg",162,6,21.42 +Malaria ,"Uncomplicated (adult, <36 kg) ",52,Malaria test kit (RDT),163,1,292.74 +Malaria ,"Uncomplicated (adult, <36 kg) ",52,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3,299.88 +Malaria ,"Uncomplicated (adult, <36 kg) ",52,Paracetamol 500mg_1000_CMST,113,18,4.16262 +Malaria ,"Uncomplicated (adult, >36 kg)",53,Malaria test kit (RDT),163,1,292.74 Malaria ,"Uncomplicated (adult, >36 kg)",53,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3.61905,299.88 -Malaria ,"Uncomplicated (adult, >36 kg)",53,Paracetamol 500mg_1000_CMST,113,18.0,4.16262 -Malaria ,"Uncomplicated - 2nd line (adult, <36 kg)",54,ASAQ (Artesunate + Amodiaquine) 100 + 270 mg,165,1.0,585.48 -Malaria ,"Uncomplicated - 2nd line (adult, >36 kg)",55,ASAQ (Artesunate + Amodiaquine) 100 + 270 mg,165,1.0,585.48 -Malaria ,"Uncomplicated (children, <15 kg)",56,Malaria test kit (RDT),163,1.0,292.74 -Malaria ,"Uncomplicated (children, <15 kg)",56,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,1.0,299.88 -Malaria ,"Uncomplicated (children, <15 kg)",56,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,18.0,869.28072 -Malaria ,"Uncomplicated (children, >15 kg)",57,Malaria test kit (RDT),163,1.0,292.74 -Malaria ,"Uncomplicated (children, >15 kg)",57,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3.0,299.88 -Malaria ,"Uncomplicated (children, >15 kg)",57,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,18.0,869.28072 -Malaria ,"Uncomplicated - 2nd line (children, <15 kg)",58,artesunate 25mg + amodiaquine 67.5mg tab_25X3 _IDA,166,1.0,171.36 -Malaria ,"Uncomplicated - 2nd line (children, >15 kg)",59,ASAQ (Artesunate + Amodiaquine) 50 + 135 Mg,167,1.0,228.48 -Malaria ,First trimester - uncomplicated,60,Quinine sulphate 300mg_1000_CMST,168,42.0,35.7 -Malaria ,First trimester - uncomplicated,60,"Clindamycin, tabcap, 300 mg",169,42.0,49.98 +Malaria ,"Uncomplicated (adult, >36 kg)",53,Paracetamol 500mg_1000_CMST,113,18,4.16262 +Malaria ,"Uncomplicated - 2nd line (adult, <36 kg)",54,ASAQ (Artesunate + Amodiaquine) 100 + 270 mg,165,1,585.48 +Malaria ,"Uncomplicated - 2nd line (adult, >36 kg)",55,ASAQ (Artesunate + Amodiaquine) 100 + 270 mg,165,1,585.48 +Malaria ,"Uncomplicated (children, <15 kg)",56,Malaria test kit (RDT),163,1,292.74 +Malaria ,"Uncomplicated (children, <15 kg)",56,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,1,299.88 +Malaria ,"Uncomplicated (children, <15 kg)",56,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,18,869.28072 +Malaria ,"Uncomplicated (children, >15 kg)",57,Malaria test kit (RDT),163,1,292.74 +Malaria ,"Uncomplicated (children, >15 kg)",57,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3,299.88 +Malaria ,"Uncomplicated (children, >15 kg)",57,Paracetamol syrup 120mg/5ml_0.0119047619047619_CMST,71,18,869.28072 +Malaria ,"Uncomplicated - 2nd line (children, <15 kg)",58,artesunate 25mg + amodiaquine 67.5mg tab_25X3 _IDA,166,1,171.36 +Malaria ,"Uncomplicated - 2nd line (children, >15 kg)",59,ASAQ (Artesunate + Amodiaquine) 50 + 135 Mg,167,1,228.48 +Malaria ,First trimester - uncomplicated,60,Quinine sulphate 300mg_1000_CMST,168,42,35.7 +Malaria ,First trimester - uncomplicated,60,"Clindamycin, tabcap, 300 mg",169,42,49.98 Malaria ,First trimester - uncomplicated,60,Paracetamol 500mg_1000_CMST,113,4.5,4.16262 -Malaria ,Second trimester - uncomplicated,61,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3.0,299.88 -Malaria ,Second trimester - uncomplicated,61,Paracetamol 500mg_1000_CMST,113,18.0,4.16262 -Malaria ,"Complicated (adults, injectable artesunate)",62,Injectable artesunate,170,1.0,1406.58 -Malaria ,"Complicated (adults, injectable artesunate)",62,Cannula iv (winged with injection pot) 18_each_CMST,171,3.0,130.07652 -Malaria ,"Complicated (adults, injectable artesunate)",62,Glove disposable latex medium_100_CMST,172,3.0,24.57588 -Malaria ,"Complicated (adults, injectable artesunate)",62,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,3.0,17.14314 -Malaria ,"Complicated (adults, injectable artesunate)",62,"Water for injection, 10ml_Each_CMST",98,3.0,32.57268 +Malaria ,Second trimester - uncomplicated,61,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",164,3,299.88 +Malaria ,Second trimester - uncomplicated,61,Paracetamol 500mg_1000_CMST,113,18,4.16262 +Malaria ,"Complicated (adults, injectable artesunate)",62,Injectable artesunate,170,1,1406.58 +Malaria ,"Complicated (adults, injectable artesunate)",62,Cannula iv (winged with injection pot) 18_each_CMST,171,3,130.07652 +Malaria ,"Complicated (adults, injectable artesunate)",62,Glove disposable latex medium_100_CMST,172,3,24.57588 +Malaria ,"Complicated (adults, injectable artesunate)",62,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,3,17.14314 +Malaria ,"Complicated (adults, injectable artesunate)",62,"Water for injection, 10ml_Each_CMST",98,3,32.57268 Malaria ,"Complicated (children, injectable artesunate)",63,Injectable artesunate,170,0.25,1406.58 -Malaria ,"Complicated (children, injectable artesunate)",63,Cannula iv (winged with injection pot) 18_each_CMST,171,3.0,130.07652 -Malaria ,"Complicated (children, injectable artesunate)",63,Glove disposable latex medium_100_CMST,172,3.0,24.57588 -Malaria ,"Complicated (children, injectable artesunate)",63,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,3.0,17.14314 -Malaria ,"Complicated (children, injectable artesunate)",63,"Water for injection, 10ml_Each_CMST",98,3.0,32.57268 -Malaria ,Pregnant women - complicated,64,"Quinine dihydrochloride 300mg/ml, 2ml_each_CMST",173,6.0,211.35828 -Malaria ,Pregnant women - complicated,64,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1.0,43.99668 -Malaria ,Pregnant women - complicated,64,Cannula iv (winged with injection pot) 18_each_CMST,171,1.0,130.07652 -Malaria ,Pregnant women - complicated,64,Bags syringe sterilization 15cm_1000_CMST,174,1.0,993.00264 -Malaria ,Pregnant women - complicated,64,Quinine sulphate 300mg_1000_CMST,168,21.0,35.7 -Malaria ,Pregnant women - complicated,64,"Clindamycin, tabcap, 300 mg",169,21.0,49.98 -Malaria ,Pregnant women - complicated,64,"Dextrose (glucose) 5%, 1000ml_each_CMST",133,1.0,1041.19764 -Tuberculosis,VCT for TB patients,65,HIV EIA Elisa test,48,1.0,120.35898 -Tuberculosis,First line treatment for new TB cases for adults,66,X-ray,175,1.0,182.51982 -Tuberculosis,First line treatment for new TB cases for adults,66,Cat. I & III Patient Kit A,176,1.0,14328.195 -Tuberculosis,First line treatment for retreatment TB cases for adults,67,X-ray,175,1.0,182.51982 -Tuberculosis,First line treatment for retreatment TB cases for adults,67,Cat. II Patient Kit A1,177,1.0,62248.305 -Tuberculosis,First line treatment for new TB cases for children,68,X-ray,175,2.0,182.51982 -Tuberculosis,First line treatment for new TB cases for children,68,Cat. I & III Patient Kit B,178,1.0,24188.0352 -Tuberculosis,First line treatment for retreatment TB cases for children,69,Cat. II Patient Kit A2,179,1.0,54397.6608 -Tuberculosis,First line treatment for retreatment TB cases for children,69,X-ray,175,1.0,182.51982 +Malaria ,"Complicated (children, injectable artesunate)",63,Cannula iv (winged with injection pot) 18_each_CMST,171,3,130.07652 +Malaria ,"Complicated (children, injectable artesunate)",63,Glove disposable latex medium_100_CMST,172,3,24.57588 +Malaria ,"Complicated (children, injectable artesunate)",63,"Gauze, swabs 8-ply 10cm x 10cm_100_CMST",75,3,17.14314 +Malaria ,"Complicated (children, injectable artesunate)",63,"Water for injection, 10ml_Each_CMST",98,3,32.57268 +Malaria ,Pregnant women - complicated,64,"Quinine dihydrochloride 300mg/ml, 2ml_each_CMST",173,6,211.35828 +Malaria ,Pregnant women - complicated,64,Giving set iv administration + needle 15 drops/ml_each_CMST,80,1,43.99668 +Malaria ,Pregnant women - complicated,64,Cannula iv (winged with injection pot) 18_each_CMST,171,1,130.07652 +Malaria ,Pregnant women - complicated,64,Bags syringe sterilization 15cm_1000_CMST,174,1,993.00264 +Malaria ,Pregnant women - complicated,64,Quinine sulphate 300mg_1000_CMST,168,21,35.7 +Malaria ,Pregnant women - complicated,64,"Clindamycin, tabcap, 300 mg",169,21,49.98 +Malaria ,Pregnant women - complicated,64,"Dextrose (glucose) 5%, 1000ml_each_CMST",133,1,1041.19764 +Tuberculosis,VCT for TB patients,65,HIV EIA Elisa test,48,1,120.35898 +Tuberculosis,First line treatment for new TB cases for adults,66,X-ray,175,1,182.51982 +Tuberculosis,First line treatment for new TB cases for adults,66,Cat. I & III Patient Kit A,176,1,14328.195 +Tuberculosis,First line treatment for retreatment TB cases for adults,67,X-ray,175,1,182.51982 +Tuberculosis,First line treatment for retreatment TB cases for adults,67,Cat. II Patient Kit A1,177,1,62248.305 +Tuberculosis,First line treatment for new TB cases for children,68,X-ray,175,2,182.51982 +Tuberculosis,First line treatment for new TB cases for children,68,Cat. I & III Patient Kit B,178,1,24188.0352 +Tuberculosis,First line treatment for retreatment TB cases for children,69,Cat. II Patient Kit A2,179,1,54397.6608 +Tuberculosis,First line treatment for retreatment TB cases for children,69,X-ray,175,1,182.51982 Tuberculosis,MDR notification among new patients,70,X-ray,175,0.01,182.51982 -Tuberculosis,MDR notification among new patients,70,Category IV,180,1.0,2031548.11272 +Tuberculosis,MDR notification among new patients,70,Category IV,180,1,2031548.113 Tuberculosis,MDR notification among previously treated patients,71,X-ray,175,0.01,182.51982 -Tuberculosis,MDR notification among previously treated patients,71,Category IV,180,1.0,2031548.11272 -Tuberculosis,Case management of MDR cases,72,Treatment: second-line drugs,181,1.0,346030.9965 -Tuberculosis,Case management of MDR cases,72,MDR Fuel,182,1.0,276347.03124 -Tuberculosis,Care and support for TB HIV+ patients,73,Care and support for TB HIV+ patients,183,1.0,149.99712 -Tuberculosis,Microscopy Test,74,Solid culture and DST,184,1.0,9887.5791 -Tuberculosis,LED test,75,Fluorescent stain,185,1.0,176.49366 -Tuberculosis,ZN test,76,ZN Stain,186,1.0,203.98266 -Tuberculosis,Xpert test,77,Xpert,187,1.0,7125.70572 -Tuberculosis,MGIT test,78,MGIT960 Culture and DST,188,1.0,23012.22 -Tuberculosis,LGA test,79,Line Probe Assay,189,1.0,149.99712 -HIV/AIDS,Viral Load,80,VL Test,190,1.0,5537.9982 -HIV/AIDS,CD4 Test,81,CD4 test,191,4.0,3403.23102 -HIV/AIDS,Isoniazid preventative therapy for HIV+ no TB,82,"Isoniazid/Pyridoxine, tablet 300 mg",192,1.0,1094.4192 -HIV/AIDS,Chemistry and hematology,83,Chemistry and hematology,193,1.0,1406.58 -HIV/AIDS,Interventions focused on female sex workers ,84,Interventions focused on sex workers and their clients drugs/supplies to service a client,194,1.0,21177.58986 -HIV/AIDS,Interventions focused on male sex workers ,85,Interventions focused on sex workers and their clients drugs/supplies to service a client,194,1.0,21177.58986 -HIV/AIDS,Interventions focused on men who have sex with men ,86,Interventions focused on men who have sex with men drugs/supplies to service a client,195,1.0,28234.50168 -HIV/AIDS,HIV Testing Services,87,"Test, HIV EIA Elisa",196,1.0,3430.67718 -HIV/AIDS,Condoms,88,"Condom, male",2,5.0,20.97018 -HIV/AIDS,Condoms,88,"Condom, male",2,10.0,20.97018 -HIV/AIDS,Condoms,88,"Condom, male",2,50.0,20.97018 -HIV/AIDS,Condoms,88,"Condom, male",2,40.0,20.97018 -HIV/AIDS,Male circumcision ,89,"Test, HIV EIA Elisa",196,0.0,3430.67718 -HIV/AIDS,Male circumcision ,89,"male circumcision kit, consumables (10 procedures)_1_IDA",197,1.0,669.41784 -HIV/AIDS,PMTCT,90,"Blood collecting tube, 5 ml",40,1.0,122.42958 -HIV/AIDS,PMTCT,90,"Gloves, exam, latex, disposable, pair",4,0.0,31.90866 -HIV/AIDS,PMTCT,90,HIV EIA Elisa test,48,2.0,120.35898 -HIV/AIDS,PMTCT,90,"Syringe, needle + swab",9,0.0,7.7469 -HIV/AIDS,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0.0,1870.65858 -HIV/AIDS,PMTCT,90,"Nevirapine, tablet, 200 mg",199,0.0,27.3819 -HIV/AIDS,PMTCT,90,DNA PCR for infant after birth,200,1.0,7705.2024 -HIV/AIDS,PMTCT,90,"Blood collecting tube, 5 ml",40,1.0,122.42958 -HIV/AIDS,PMTCT,90,"Gloves, exam, latex, disposable, pair",4,1.0,31.90866 -HIV/AIDS,PMTCT,90,HIV EIA Elisa test,48,0.0,120.35898 -HIV/AIDS,PMTCT,90,"Syringe, needle + swab",9,0.0,7.7469 -HIV/AIDS,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0.0,1870.65858 -PMTCT,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0.0,1870.65858 -PMTCT,PMTCT,90,"Nevirapine, tablet, 200 mg",199,0.0,27.3819 -PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0.0,90.17106 -PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0.0,90.17106 -PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0.0,90.17106 -PMTCT,Cotrimoxazole for children,91,"Sulfamethoxazole + trimethropin, oral suspension, 240 mg, 100 ml",202,0.0,322.71372 -PMTCT,Cotrimoxazole for children,91,"Sulfamethoxazole + trimethropin, tablet 400 mg + 80 mg",162,0.0,21.42 -PMTCT,Cotrimoxazole for children,91,Cotrimoxazole 120mg_1000_CMST,203,1.0,3734.22 -PMTCT,Management of opportunistic infections associated with HIV/AIDS,92,"Cotrimoxizole, 960mg pppy",204,730.0,6.99006 -PMTCT,Nutrition supplements in first 6 months for HIV/AIDS cases ,93,Nutrition supplements in first six months drugs/supplies to service a client,205,1.0,2344.419 -PMTCT,Screen HIV+ cases for TB,94,X-ray,175,1.0,182.51982 -PMTCT,Screen HIV+ cases for TB,94,Culture test,206,0.8999999999999999,9887.5791 -PMTCT,Screen HIV+ cases for TB,94,Smear test,207,3.0,203.98266 -PMTCT,ART (+CPT) for TB HIV+ patients,95,"Cotrimoxizole, 960mg pppy",204,730.0,6.99006 -PMTCT,HIV prevention for TB patients,96,"Condom, male",2,1.0,20.97018 -Nutrition,Nutritional care and support (HIV+ pregnant and lactating women),97,Corn Soya Blend (or Supercereal - CSB++),208,36.0,856.8 -Nutrition,Vitamin A supplementation in pregnant women,98,"Vitamin A, caplet, 100,000 IU",209,84.0,19.89204 -Nutrition,Daily iron and folic acid supplementation (pregnant women),99,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,270.0,1.79214 -Nutrition,Management of moderate acute malnutrition (pregnant and lactating women),100,Vegetable oil,210,3.5999999999999996,703.29 -Nutrition,Management of moderate acute malnutrition (pregnant and lactating women),100,Corn Soya Blend (or Supercereal - CSB++),208,36.0,856.8 +Tuberculosis,MDR notification among previously treated patients,71,Category IV,180,1,2031548.113 +Tuberculosis,Case management of MDR cases,72,Treatment: second-line drugs,181,1,346030.9965 +Tuberculosis,Case management of MDR cases,72,MDR Fuel,182,1,276347.0312 +Tuberculosis,Care and support for TB HIV+ patients,73,Care and support for TB HIV+ patients,183,1,149.99712 +Tuberculosis,Microscopy Test,74,Solid culture and DST,184,1,9887.5791 +Tuberculosis,LED test,75,Fluorescent stain,185,1,176.49366 +Tuberculosis,ZN test,76,ZN Stain,186,1,203.98266 +Tuberculosis,Xpert test,77,Xpert,187,1,7125.70572 +Tuberculosis,MGIT test,78,MGIT960 Culture and DST,188,1,23012.22 +Tuberculosis,LGA test,79,Line Probe Assay,189,1,149.99712 +HIV/AIDS,Viral Load,80,VL Test,190,1,5537.9982 +HIV/AIDS,CD4 Test,81,CD4 test,191,4,3403.23102 +HIV/AIDS,Isoniazid preventative therapy for HIV+ no TB,82,"Isoniazid/Pyridoxine, tablet 300 mg",192,1,1094.4192 +HIV/AIDS,Chemistry and hematology,83,Chemistry and hematology,193,1,1406.58 +HIV/AIDS,Interventions focused on female sex workers ,84,Interventions focused on sex workers and their clients drugs/supplies to service a client,194,1,21177.58986 +HIV/AIDS,Interventions focused on male sex workers ,85,Interventions focused on sex workers and their clients drugs/supplies to service a client,194,1,21177.58986 +HIV/AIDS,Interventions focused on men who have sex with men ,86,Interventions focused on men who have sex with men drugs/supplies to service a client,195,1,28234.50168 +HIV/AIDS,HIV Testing Services,87,"Test, HIV EIA Elisa",196,1,3430.67718 +HIV/AIDS,Condoms,88,"Condom, male",2,5,20.97018 +HIV/AIDS,Condoms,88,"Condom, male",2,10,20.97018 +HIV/AIDS,Condoms,88,"Condom, male",2,50,20.97018 +HIV/AIDS,Condoms,88,"Condom, male",2,40,20.97018 +HIV/AIDS,Male circumcision ,89,"Test, HIV EIA Elisa",196,0,3430.67718 +HIV/AIDS,Male circumcision ,89,"male circumcision kit, consumables (10 procedures)_1_IDA",197,1,669.41784 +HIV/AIDS,PMTCT,90,"Blood collecting tube, 5 ml",40,1,122.42958 +HIV/AIDS,PMTCT,90,"Gloves, exam, latex, disposable, pair",4,0,31.90866 +HIV/AIDS,PMTCT,90,HIV EIA Elisa test,48,2,120.35898 +HIV/AIDS,PMTCT,90,"Syringe, needle + swab",9,0,7.7469 +HIV/AIDS,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0,1870.65858 +HIV/AIDS,PMTCT,90,"Nevirapine, tablet, 200 mg",199,0,27.3819 +HIV/AIDS,PMTCT,90,DNA PCR for infant after birth,200,1,7705.2024 +HIV/AIDS,PMTCT,90,"Blood collecting tube, 5 ml",40,1,122.42958 +HIV/AIDS,PMTCT,90,"Gloves, exam, latex, disposable, pair",4,1,31.90866 +HIV/AIDS,PMTCT,90,HIV EIA Elisa test,48,0,120.35898 +HIV/AIDS,PMTCT,90,"Syringe, needle + swab",9,0,7.7469 +HIV/AIDS,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0,1870.65858 +PMTCT,PMTCT,90,"Nevirapine, oral solution, 10 mg/ml",198,0,1870.65858 +PMTCT,PMTCT,90,"Nevirapine, tablet, 200 mg",199,0,27.3819 +PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0,90.17106 +PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0,90.17106 +PMTCT,PMTCT,90,"Zidovudine (AZT), capsule, 300 mg",201,0,90.17106 +PMTCT,Cotrimoxazole for children,91,"Sulfamethoxazole + trimethropin, oral suspension, 240 mg, 100 ml",202,0,322.71372 +PMTCT,Cotrimoxazole for children,91,"Sulfamethoxazole + trimethropin, tablet 400 mg + 80 mg",162,0,21.42 +PMTCT,Cotrimoxazole for children,91,Cotrimoxazole 120mg_1000_CMST,203,1,3734.22 +PMTCT,Management of opportunistic infections associated with HIV/AIDS,92,"Cotrimoxizole, 960mg pppy",204,730,6.99006 +PMTCT,Nutrition supplements in first 6 months for HIV/AIDS cases ,93,Nutrition supplements in first six months drugs/supplies to service a client,205,1,2344.419 +PMTCT,Screen HIV+ cases for TB,94,X-ray,175,1,182.51982 +PMTCT,Screen HIV+ cases for TB,94,Culture test,206,0.9,9887.5791 +PMTCT,Screen HIV+ cases for TB,94,Smear test,207,3,203.98266 +PMTCT,ART (+CPT) for TB HIV+ patients,95,"Cotrimoxizole, 960mg pppy",204,730,6.99006 +PMTCT,HIV prevention for TB patients,96,"Condom, male",2,1,20.97018 +Nutrition,Nutritional care and support (HIV+ pregnant and lactating women),97,Corn Soya Blend (or Supercereal - CSB++),208,36,856.8 +Nutrition,Vitamin A supplementation in pregnant women,98,"Vitamin A, caplet, 100,000 IU",209,84,19.89204 +Nutrition,Daily iron and folic acid supplementation (pregnant women),99,"Ferrous Salt + Folic Acid, tablet, 200 + 0.25 mg",140,270,1.79214 +Nutrition,Management of moderate acute malnutrition (pregnant and lactating women),100,Vegetable oil,210,3.6,703.29 +Nutrition,Management of moderate acute malnutrition (pregnant and lactating women),100,Corn Soya Blend (or Supercereal - CSB++),208,36,856.8 Nutrition,Nutrition care and support program for Individuals with TB or other chronic diseases,101,Corn Soya Blend (or Supercereal - CSB++),208,24.48,856.8 -Nutrition,Nutrition care and support program for Individuals with TB or other chronic diseases,101,Vegetable oil,210,2.4480000000000004,703.29 -Nutrition,Nutrition care and support program for Individuals with TB or other chronic diseases,101,"Ready-to-use therapeutic food (RUTF), tablet",211,115.19999999999999,20.08482 +Nutrition,Nutrition care and support program for Individuals with TB or other chronic diseases,101,Vegetable oil,210,2.448,703.29 +Nutrition,Nutrition care and support program for Individuals with TB or other chronic diseases,101,"Ready-to-use therapeutic food (RUTF), tablet",211,115.2,20.08482 Nutrition,Vitamin A supplementation in infants and children 6-59 months,102,"Vitamin A, caplet, 100,000 IU",209,0.2,19.89204 Nutrition,Vitamin A supplementation in infants and children 6-59 months,102,"Vitamin A, caplet, 200,000 IU",212,3.2,19.89204 -Nutrition,Deworming (children) for Children 12-23 months,103,"Albendazole, tablet, 400 mg",52,1.0,63.7602 +Nutrition,Deworming (children) for Children 12-23 months,103,"Albendazole, tablet, 400 mg",52,1,63.7602 Nutrition,Deworming (children),104,"Albendazole, tablet, 400 mg",52,1.86,63.7602 -Nutrition,Management of moderate acute malnutrition (children),105,Corn Soya Blend (or Supercereal - CSB++),208,36.0,856.8 -Nutrition,Management of severe malnutrition (children),106,SAM theraputic foods,213,1.0,48625.87044 -Nutrition,Management of severe malnutrition (children),106,SAM medicines,214,1.0,15988.82334 -Non-communicable diseases,Treatment of cases with rheumatic heart disease ,107,"Penicillin G Benzathine, 1440 mg",215,30.0,268.19982 +Nutrition,Management of moderate acute malnutrition (children),105,Corn Soya Blend (or Supercereal - CSB++),208,36,856.8 +Nutrition,Management of severe malnutrition (children),106,SAM theraputic foods,213,1,48625.87044 +Nutrition,Management of severe malnutrition (children),106,SAM medicines,214,1,15988.82334 +Non-communicable diseases,Treatment of cases with rheumatic heart disease ,107,"Penicillin G Benzathine, 1440 mg",215,30,268.19982 Non-communicable diseases,Screening for risk of CVD/Diabetes,108,Blood glucose level test,216,0.3,685.99692 Non-communicable diseases,Screening for risk of CVD/Diabetes,108,Cholesterol test,217,0.3,685.99692 Non-communicable diseases,Screening for risk of CVD/Diabetes,108,Urine analysis,47,0.3,627.9987 -Non-communicable diseases,Screening for risk of CVD/Diabetes,108,Urine sugar analysis,218,1.0,230.00082 -Non-communicable diseases,Hypertension,109,"Enalapril, tablet, 20 mg",219,72.0,9.48906 -Non-communicable diseases,Hypertension,109,Nifedipine 10mg_100_CMST,220,288.0,3.12018 -Non-communicable diseases,Hypertension,109,Hydrochlorothiazide 25mg_1000_CMST,221,360.0,2.12058 -Non-communicable diseases,Hypertension,109,Methyldopa 250mg_1000_CMST,222,108.00000000000001,25.01856 -Non-communicable diseases,Hypertension,109,Hydralazine 25mg_100_CMST,223,0.0,915.99774 +Non-communicable diseases,Screening for risk of CVD/Diabetes,108,Urine sugar analysis,218,1,230.00082 +Non-communicable diseases,Hypertension,109,"Enalapril, tablet, 20 mg",219,72,9.48906 +Non-communicable diseases,Hypertension,109,Nifedipine 10mg_100_CMST,220,288,3.12018 +Non-communicable diseases,Hypertension,109,Hydrochlorothiazide 25mg_1000_CMST,221,360,2.12058 +Non-communicable diseases,Hypertension,109,Methyldopa 250mg_1000_CMST,222,108,25.01856 +Non-communicable diseases,Hypertension,109,Hydralazine 25mg_100_CMST,223,0,915.99774 Non-communicable diseases,Hypertension,109,"Hydralazine, powder for injection, 20 mg ampoule",60,0.25,676.85058 -Non-communicable diseases,Hypertension,109,Atenolol 100mg_1000_CMST,224,108.0,6.59736 +Non-communicable diseases,Hypertension,109,Atenolol 100mg_1000_CMST,224,108,6.59736 Non-communicable diseases,Hypertension,109,Frusemide 40mg_1000_CMST,225,0.0002,2630.61162 Non-communicable diseases,Hypertension,109,Aspirin 300mg_1000_CMST,226,0.09,3034.77132 -Non-communicable diseases,Diabetes Type I,110,"Insulin soluble 100 IU/ml, 10ml_each_CMST",227,12.0,3336.3792 -Non-communicable diseases,Diabetes Type I,110,"Insulin zinc suspension (lente) 100 IU/ml, 10ml_each_CMST",228,24.0,3357.0495 -Non-communicable diseases,Diabetes Type I,110,Creatinine test kit-Human_ 200ml _CMST,229,1.0,24000.0033 -Non-communicable diseases,Diabetes Type I,110,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1.0,34670.74758 -Non-communicable diseases,Diabetes Type I,110,"Syringe, NSEP, 1 cc",231,1.0,264.18 -Non-communicable diseases,Diabetes Type I,110,Glove disposable latex medium_100_CMST,172,1.0,24.57588 -Non-communicable diseases,Diabetes Type II,111,Glibenclamide 5mg_1000_CMST,232,1080.0,3.59856 -Non-communicable diseases,Diabetes Type II,111,Metformin hydrochloride 500mg_100_CMST,233,1080.0,10.26018 -Non-communicable diseases,Diabetes Type II,111,Blood glucose level test,216,1.0,685.99692 -Non-communicable diseases,Diabetes Type II,111,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1.0,34670.74758 -Non-communicable diseases,Diabetes Type II,111,Creatinine test kit-Human_ 200ml _CMST,229,1.0,24000.0033 -Non-communicable diseases,High cholesterol,112,"Simvastatin, 15 mg",234,24.0,223.99608 -Non-communicable diseases,High cholesterol,112,Creatinine test kit-Human_ 200ml _CMST,229,1.0,24000.0033 -Non-communicable diseases,High cholesterol,112,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1.0,34670.74758 +Non-communicable diseases,Diabetes Type I,110,"Insulin soluble 100 IU/ml, 10ml_each_CMST",227,12,3336.3792 +Non-communicable diseases,Diabetes Type I,110,"Insulin zinc suspension (lente) 100 IU/ml, 10ml_each_CMST",228,24,3357.0495 +Non-communicable diseases,Diabetes Type I,110,Creatinine test kit-Human_ 200ml _CMST,229,1,24000.0033 +Non-communicable diseases,Diabetes Type I,110,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1,34670.74758 +Non-communicable diseases,Diabetes Type I,110,"Syringe, NSEP, 1 cc",231,1,264.18 +Non-communicable diseases,Diabetes Type I,110,Glove disposable latex medium_100_CMST,172,1,24.57588 +Non-communicable diseases,Diabetes Type II,111,Glibenclamide 5mg_1000_CMST,232,1080,3.59856 +Non-communicable diseases,Diabetes Type II,111,Metformin hydrochloride 500mg_100_CMST,233,1080,10.26018 +Non-communicable diseases,Diabetes Type II,111,Blood glucose level test,216,1,685.99692 +Non-communicable diseases,Diabetes Type II,111,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1,34670.74758 +Non-communicable diseases,Diabetes Type II,111,Creatinine test kit-Human_ 200ml _CMST,229,1,24000.0033 +Non-communicable diseases,High cholesterol,112,"Simvastatin, 15 mg",234,24,223.99608 +Non-communicable diseases,High cholesterol,112,Creatinine test kit-Human_ 200ml _CMST,229,1,24000.0033 +Non-communicable diseases,High cholesterol,112,Albumin test kit (HUMAN)_ 1000ml _CMST,230,1,34670.74758 Non-communicable diseases,Ischemic heart disease,113,Aspirin 300mg_1000_CMST,226,0.03,3034.77132 -Non-communicable diseases,Screening: Mammography,114,X-ray film,235,4.0,420.3318 -Non-communicable diseases,Screening: Mammography,114,X-ray film chemistry,236,1.0,47.45958 -Non-communicable diseases,Breast Cancer (first line),115,Cyclophosphamide 1000mg Injection,237,6.0,2065.7091 -Non-communicable diseases,Breast Cancer (first line),115,"Doxorubicin, 50 mg vial",238,12.0,6850.85142 -Non-communicable diseases,Cervical cancer (first line),116,Cisplatin 50mg Injection,239,12.0,4891.77108 -Non-communicable diseases,Cervical cancer (first line),116,5-Fluorouracil 500mg injection,240,36.0,625.52112 +Non-communicable diseases,Screening: Mammography,114,X-ray film,235,4,420.3318 +Non-communicable diseases,Screening: Mammography,114,X-ray film chemistry,236,1,47.45958 +Non-communicable diseases,Breast Cancer (first line),115,Cyclophosphamide 1000mg Injection,237,6,2065.7091 +Non-communicable diseases,Breast Cancer (first line),115,"Doxorubicin, 50 mg vial",238,12,6850.85142 +Non-communicable diseases,Cervical cancer (first line),116,Cisplatin 50mg Injection,239,12,4891.77108 +Non-communicable diseases,Cervical cancer (first line),116,5-Fluorouracil 500mg injection,240,36,625.52112 Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Tetanus toxin vaccine (TTV),241,0.2,1199.99838 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"diclofenac sodium 25 mg, enteric coated_1000_IDA",242,60.0,0.92106 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Paracetamol 500mg_1000_CMST,113,80.0,4.16262 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"diclofenac sodium 25 mg, enteric coated_1000_IDA",242,60,0.92106 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Paracetamol 500mg_1000_CMST,113,80,4.16262 Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"morphine sulphate 10 mg/ml, 1 ml, injection (nt)_10_IDA",243,0.4,549.50154 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Bandage, crepe 7.5cm x 1.4m long , when stretched",244,4.0,119.28798 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Gauze, swabs 8-ply 10cm x 10cm",245,10.0,14.72268 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Bandage, crepe 7.5cm x 1.4m long , when stretched",244,4,119.28798 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Gauze, swabs 8-ply 10cm x 10cm",245,10,14.72268 Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Iodine solution, weak (iodine tincture) 0.5%_500ml_CMST",246,0.1,1742.63838 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Glove disposable latex medium_100_CMST,172,8.0,24.57588 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Glove disposable latex medium_100_CMST,172,8,24.57588 Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Suture pack,247,0.05,2856 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Flucloxacillin 250mg_100_CMST,248,22.400000000000002,40.39812 -Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Cotton wool, 500g_1_CMST",49,10.0,416.99742 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,Flucloxacillin 250mg_100_CMST,248,22.4,40.39812 +Non-communicable diseases,Treatment of Injuries (Blunt Trauma - Soft Tissue Injury),117,"Cotton wool, 500g_1_CMST",49,10,416.99742 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Tetanus toxin vaccine (TTV),241,0.2,1199.99838 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"diclofenac sodium 25 mg, enteric coated_1000_IDA",242,60.0,0.92106 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Paracetamol 500mg_1000_CMST,113,80.0,4.16262 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"morphine sulphate 10 mg/ml, 1 ml, injection (nt)_10_IDA",243,2.0,549.50154 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Bandage, crepe 7.5cm x 1.4m long , when stretched",244,8.0,119.28798 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Gauze, swabs 8-ply 10cm x 10cm",245,10.0,14.72268 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"diclofenac sodium 25 mg, enteric coated_1000_IDA",242,60,0.92106 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Paracetamol 500mg_1000_CMST,113,80,4.16262 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"morphine sulphate 10 mg/ml, 1 ml, injection (nt)_10_IDA",243,2,549.50154 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Bandage, crepe 7.5cm x 1.4m long , when stretched",244,8,119.28798 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Gauze, swabs 8-ply 10cm x 10cm",245,10,14.72268 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Iodine strong 10% solution_500ml_CMST,73,0.1,1641.60024 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Plaster of Paris (POP) 10cm x 7.5cm slab_12_CMST,249,12.0,16.9218 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Monochromatic blue senstive X-ray Film, screen SizeSize: 30cm x 40cm",250,6.0,723.0678 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Plaster of Paris (POP) 10cm x 7.5cm slab_12_CMST,249,12,16.9218 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Monochromatic blue senstive X-ray Film, screen SizeSize: 30cm x 40cm",250,6,723.0678 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Glove surgeon's size 7 sterile_2_CMST,112,0.4,137.45928 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Glove disposable latex medium_100_CMST,172,8.0,24.57588 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Glove disposable latex medium_100_CMST,172,8,24.57588 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Ketamine hydrochloride 50mg/ml, 10ml",251,0.024,607.12848 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Syringe, 5ml, disposable, hypoluer with 21g needle_each_CMST",107,1.0,149.98284 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Apron laboratory disposable_50_CMST,252,2.0,74.19888 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Ceftriaxone 1g, PFR_each_CMST",81,1.4000000000000001,207.10998 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"cloxacillin 500 mg, powder for injection_50_IDA",253,8.400000000000002,59.04066 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,2.1000000000000005,41.74758 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Syringe, 5ml, disposable, hypoluer with 21g needle_each_CMST",107,1,149.98284 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Apron laboratory disposable_50_CMST,252,2,74.19888 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Ceftriaxone 1g, PFR_each_CMST",81,1.4,207.10998 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"cloxacillin 500 mg, powder for injection_50_IDA",253,8.4,59.04066 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Gentamycin, injection, 40 mg/ml in 2 ml vial",28,2.1,41.74758 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Vancomycin 500mg for injection,254,3.6,5999.99904 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Chloramphenicol Sodium 1g, PFR_each_CMST",255,7.0,338.5431 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Flucloxacillin 250mg_100_CMST,248,22.400000000000002,40.39812 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,"Chloramphenicol Sodium 1g, PFR_each_CMST",255,7,338.5431 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Flucloxacillin 250mg_100_CMST,248,22.4,40.39812 Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,External fixator,256,0.01,42840 -Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Chloramphenicol 250mg_1000_CMST,257,112.0,28.06734 -Non-communicable diseases,Kaposi sarcoma - first line,119,"Doxorubicin, 50 mg vial",238,7.0,6850.85142 -Non-communicable diseases,Kaposi sarcoma - first line,119,Belomycin 15lu inj,258,7.0,5941.67952 -Non-communicable diseases,Kaposi sarcoma - first line,119,Vincristin 1mg Injection,259,7.0,901.13226 +Non-communicable diseases,Treatment of injuries (Fracture and dislocation),118,Chloramphenicol 250mg_1000_CMST,257,112,28.06734 +Non-communicable diseases,Kaposi sarcoma - first line,119,"Doxorubicin, 50 mg vial",238,7,6850.85142 +Non-communicable diseases,Kaposi sarcoma - first line,119,Belomycin 15lu inj,258,7,5941.67952 +Non-communicable diseases,Kaposi sarcoma - first line,119,Vincristin 1mg Injection,259,7,901.13226 Non-communicable diseases,Kaposi sarcoma - second line,120,Paclitaxel 100mg Injection,260,2.33331,31493.11914 -Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Cyclophosphamide, 1 g",261,5.0,2065.7091 -Non-communicable diseases,"Lymphomas, nonhodgkins",121,Vincristin 1mg Injection,259,10.0,901.13226 -Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Methylprednisolone acetate sub-conj. 40mg/ml,2ml_each_CMST",262,0.0,1623.07194 -Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Doxorubicin, 50 mg vial",238,5.0,6850.85142 -Non-communicable diseases,Hodgkin's lymphoma,122,"bleomycin powder 15 mg (15,000 IU) (**)_1_IDA",263,0.0,7709.25078 -Non-communicable diseases,Hodgkin's lymphoma,122,Belomycin 15lu inj,258,12.0,5941.67952 -Non-communicable diseases,Hodgkin's lymphoma,122,Vinblastin 10mg injection,264,12.0,5913.59076 -Non-communicable diseases,Hodgkin's lymphoma,122,Dacarbazine 500mg injection,265,18.0,12034.61994 -Non-communicable diseases,Hodgkin's lymphoma,122,"Doxorubicin, 50 mg vial",238,12.0,6850.85142 +Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Cyclophosphamide, 1 g",261,5,2065.7091 +Non-communicable diseases,"Lymphomas, nonhodgkins",121,Vincristin 1mg Injection,259,10,901.13226 +Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Methylprednisolone acetate sub-conj. 40mg/ml,2ml_each_CMST",262,0,1623.07194 +Non-communicable diseases,"Lymphomas, nonhodgkins",121,"Doxorubicin, 50 mg vial",238,5,6850.85142 +Non-communicable diseases,Hodgkin's lymphoma,122,"bleomycin powder 15 mg (15,000 IU) (**)_1_IDA",263,0,7709.25078 +Non-communicable diseases,Hodgkin's lymphoma,122,Belomycin 15lu inj,258,12,5941.67952 +Non-communicable diseases,Hodgkin's lymphoma,122,Vinblastin 10mg injection,264,12,5913.59076 +Non-communicable diseases,Hodgkin's lymphoma,122,Dacarbazine 500mg injection,265,18,12034.61994 +Non-communicable diseases,Hodgkin's lymphoma,122,"Doxorubicin, 50 mg vial",238,12,6850.85142 Non-communicable diseases,Head and neck cancer (esophageal),123,Cisplatin 50mg Injection,239,12.5,4891.77108 Non-communicable diseases,Head and neck cancer (esophageal),123,5-Fluorouracil 500mg injection,240,8.5,625.52112 Non-communicable diseases,"GIT, intestine cancer",124,5-Fluorouracil 500mg injection,240,10.2,625.52112 -Non-communicable diseases,"GIT, intestine cancer",124,Leucovorin 50mg injection,266,3.5999999999999996,1931.16294 -"Mental, neurological, and substance use disorders",Anxiety,125,Amitriptyline 25mg_100_CMST,267,180.0,5.49066 -"Mental, neurological, and substance use disorders",Anxiety,125,Fluoxetine 20mg_1000_CMST,268,180.0,103.80846 -"Mental, neurological, and substance use disorders",Treatment of depression,126,Amitriptyline 25mg_100_CMST,267,180.0,5.49066 -"Mental, neurological, and substance use disorders",Treatment of depression,126,Fluoxetine 20mg_1000_CMST,268,180.0,103.80846 +Non-communicable diseases,"GIT, intestine cancer",124,Leucovorin 50mg injection,266,3.6,1931.16294 +"Mental, neurological, and substance use disorders",Anxiety,125,Amitriptyline 25mg_100_CMST,267,180,5.49066 +"Mental, neurological, and substance use disorders",Anxiety,125,Fluoxetine 20mg_1000_CMST,268,180,103.80846 +"Mental, neurological, and substance use disorders",Treatment of depression,126,Amitriptyline 25mg_100_CMST,267,180,5.49066 +"Mental, neurological, and substance use disorders",Treatment of depression,126,Fluoxetine 20mg_1000_CMST,268,180,103.80846 "Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,Haloperidol 5mg_100_CMST,269,1.825,766.75032 "Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,Chlorpromazine 100mg_1000_CMST,270,0.27375,8873.99898 -"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Fluphenazine decanoate 25mg/ml, 2ml_each_CMST",271,1.2000000000000002,3156.951 -"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Risperidone, 2 mg tab",272,146.0,14.2086 -"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Biperiden, 2 mg tab",273,7.0,12.00234 +"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Fluphenazine decanoate 25mg/ml, 2ml_each_CMST",271,1.2,3156.951 +"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Risperidone, 2 mg tab",272,146,14.2086 +"Mental, neurological, and substance use disorders",Treatment of acute psychotic disorders,127,"Biperiden, 2 mg tab",273,7,12.00234 "Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,"Lithium, 300 mg",274,547.5,5.9976 -"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,Sodium valproate 200mg_100_CMST,275,5.475000000000001,3154.11642 -"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,Carbamazepine 200mg_1000_CMST,276,0.07300000000000001,11382.73794 -"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,"Diazepam 5mg/ml, 2ml_each_CMST",87,12.0,130.47636 +"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,Sodium valproate 200mg_100_CMST,275,5.475,3154.11642 +"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,Carbamazepine 200mg_1000_CMST,276,0.073,11382.73794 +"Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,"Diazepam 5mg/ml, 2ml_each_CMST",87,12,130.47636 "Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,"Syringe, 10 cc with needle",277,0.4,298.809 "Mental, neurological, and substance use disorders",Treatment of bipolar disorder,128,Glove disposable latex medium_100_CMST,172,0.4,24.57588 "Mental, neurological, and substance use disorders",Anti-epileptic medication,129,"Phenobarbital, 100 mg",278,729.99927,4.04124 -"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Phenytoin sodium 100mg_1000_CMST,279,328.49999999999994,3.84132 -"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Carbamazepine 200mg_1000_CMST,276,0.07300000000000001,11382.73794 -"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Sodium valproate 200mg_100_CMST,275,0.0,3154.11642 +"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Phenytoin sodium 100mg_1000_CMST,279,328.5,3.84132 +"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Carbamazepine 200mg_1000_CMST,276,0.073,11382.73794 +"Mental, neurological, and substance use disorders",Anti-epileptic medication,129,Sodium valproate 200mg_100_CMST,275,0,3154.11642 "Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,Haloperidol 5mg_100_CMST,269,1.825,766.75032 "Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,Chlorpromazine 100mg_1000_CMST,270,0.27375,8873.99898 -"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Fluphenazine decanoate 25mg/ml, 2ml_each_CMST",271,1.2000000000000002,3156.951 -"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Risperidone, 2 mg tab",272,146.0,14.2086 -"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Biperiden, 2 mg tab",273,7.0,12.00234 +"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Fluphenazine decanoate 25mg/ml, 2ml_each_CMST",271,1.2,3156.951 +"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Risperidone, 2 mg tab",272,146,14.2086 +"Mental, neurological, and substance use disorders",Treatment of schizophrenia,130,"Biperiden, 2 mg tab",273,7,12.00234 "Mental, neurological, and substance use disorders",Substance use disorder - alcohol,131,Diazepam 5mg_1000_CMST,280,0.002,2380.0833 -"Mental, neurological, and substance use disorders",Substance use disorder - alcohol,131,"Thiamine (vitamin B1), 100 mg",281,1.0,6.9972 +"Mental, neurological, and substance use disorders",Substance use disorder - alcohol,131,"Thiamine (vitamin B1), 100 mg",281,1,6.9972 "Mental, neurological, and substance use disorders",Substance use disorder - cannabis,132,"Buprenorphine, 8 mg",282,1.25,450.9981 "Mental, neurological, and substance use disorders",Substance use disorder - cannabis,132,"Methadone, 5 mg",283,1.75,606.00036 "Mental, neurological, and substance use disorders",Substance use disorder - cannabis,132,"Clonidine, .1 mg",284,3.5,213.56454 -Neglected Tropical Diseases,Onchocerciasis mass drug administration,133,Mectizan,285,1.0,2142 +Neglected Tropical Diseases,Onchocerciasis mass drug administration,133,Mectizan,285,1,2142 Neglected Tropical Diseases,Schistosomiasis mass drug administration,134,Praziquantel 600mg_1000_CMST,286,2.5,2.77032 -Neglected Tropical Diseases,LF hydrocele surgery,135,I/V R/lactate 3Lts,287,3.0,1309.02618 -Neglected Tropical Diseases,LF hydrocele surgery,135,"Ampicillin injection 500mg, PFR_each_CMST",86,1.0,118.4526 -Neglected Tropical Diseases,LF hydrocele surgery,135,"Metronidazole 5mg/ml, 100ml_each_CMST",105,1.0,215.34954 +Neglected Tropical Diseases,LF hydrocele surgery,135,I/V R/lactate 3Lts,287,3,1309.02618 +Neglected Tropical Diseases,LF hydrocele surgery,135,"Ampicillin injection 500mg, PFR_each_CMST",86,1,118.4526 +Neglected Tropical Diseases,LF hydrocele surgery,135,"Metronidazole 5mg/ml, 100ml_each_CMST",105,1,215.34954 Neglected Tropical Diseases,LF hydrocele surgery,135,Amoxycillin 250mg_1000_CMST,125,0.001,16460.99868 Neglected Tropical Diseases,LF hydrocele surgery,135,Metronidazole 200mg_1000_CMST,92,0.001,5271.83328 Neglected Tropical Diseases,LF hydrocele surgery,135,Diclofenac sodium 100mg _100_CMST,288,0.1,240.86076 -Neglected Tropical Diseases,LF hydrocele surgery,135,Catheter Foley's + urine bag (2000ml) 10g_each_CMST,289,1.0,297.98076 -Neglected Tropical Diseases,LF hydrocele surgery,135,Cannula iv (winged with injection pot) 18_each_CMST,171,1.0,130.07652 -Neglected Tropical Diseases,LF hydrocele surgery,135,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,1.0,182.94822 -Neglected Tropical Diseases,LF hydrocele surgery,135,"Water for injection, 10ml_Each_CMST",98,1.0,32.57268 -Neglected Tropical Diseases,LF hydrocele surgery,135,Underpants,290,1.0,2427.6 -Acute Respiratory Infections,Asthma,136,Prednisolone 5mg_100_CMST,291,18.0,8.3181 -Acute Respiratory Infections,Asthma,136,"Aminophylline 100mg, tablets",292,30.0,3.22728 -Acute Respiratory Infections,Asthma,136,Salbutamol Inhaler 100mcg/dose - 200 doses ,293,1.0,960.73698 -Acute Respiratory Infections,Asthma,136,Salbutamol 4mg_1000_CMST,121,30.0,2.76318 -Acute Respiratory Infections,Asthma,136,"Beclomethasone diproprionate inhalation, 50mcg/dose, 200 doses",294,1.0,1400.39676 -Acute Respiratory Infections,Pneumonia treatment (children),137,"Paracetamol, tablet, 100 mg",295,12.0,4.34826 +Neglected Tropical Diseases,LF hydrocele surgery,135,Catheter Foley's + urine bag (2000ml) 10g_each_CMST,289,1,297.98076 +Neglected Tropical Diseases,LF hydrocele surgery,135,Cannula iv (winged with injection pot) 18_each_CMST,171,1,130.07652 +Neglected Tropical Diseases,LF hydrocele surgery,135,"Syringe, 20ml, disposable with 21g needle_each_CMST",111,1,182.94822 +Neglected Tropical Diseases,LF hydrocele surgery,135,"Water for injection, 10ml_Each_CMST",98,1,32.57268 +Neglected Tropical Diseases,LF hydrocele surgery,135,Underpants,290,1,2427.6 +Acute Respiratory Infections,Asthma,136,Prednisolone 5mg_100_CMST,291,18,8.3181 +Acute Respiratory Infections,Asthma,136,"Aminophylline 100mg, tablets",292,30,3.22728 +Acute Respiratory Infections,Asthma,136,Salbutamol Inhaler 100mcg/dose - 200 doses ,293,1,960.73698 +Acute Respiratory Infections,Asthma,136,Salbutamol 4mg_1000_CMST,121,30,2.76318 +Acute Respiratory Infections,Asthma,136,"Beclomethasone diproprionate inhalation, 50mcg/dose, 200 doses",294,1,1400.39676 +Acute Respiratory Infections,Pneumonia treatment (children),137,"Paracetamol, tablet, 100 mg",295,12,4.34826 Acute Respiratory Infections,Pneumonia treatment (children),137,"Salbutamol, tablet, 4 mg",296,0.08,2.76318 Acute Respiratory Infections,Pneumonia treatment (children),137,"Salbutamol, syrup, 2 mg/5 ml",297,0.36,6.9972 Acute Respiratory Infections,Pneumonia treatment (children),137,"Salbutamol sulphate 1mg/ml, 5ml_each_CMST",298,0.024,86.0013 Acute Respiratory Infections,Pneumonia treatment (children),137,"Amoxycillin 125mg/5ml suspension, PFR_0.025_CMST",299,0.4,345.6117 -Acute Respiratory Infections,Pneumonia treatment (children),137,Amoxycillin 250mg_1000_CMST,125,0.005999999999999999,16460.99868 -Acute Respiratory Infections,Treatment of severe pneumonia,138,"Benzylpenicillin 3g (5MU), PFR_each_CMST",99,12.0,194.6007 -Acute Respiratory Infections,Treatment of severe pneumonia,138,"Gentamicin Sulphate 40mg/ml, 2ml_each_CMST",106,25.0,27.00348 +Acute Respiratory Infections,Pneumonia treatment (children),137,Amoxycillin 250mg_1000_CMST,125,0.006,16460.99868 +Acute Respiratory Infections,Treatment of severe pneumonia,138,"Benzylpenicillin 3g (5MU), PFR_each_CMST",99,12,194.6007 +Acute Respiratory Infections,Treatment of severe pneumonia,138,"Gentamicin Sulphate 40mg/ml, 2ml_each_CMST",106,25,27.00348 Acute Respiratory Infections,Treatment of severe pneumonia,138,"Ceftriaxone 1g, PFR_each_CMST",81,1.25,207.10998 Acute Respiratory Infections,Treatment of severe pneumonia,138,"Tube, nasogastric CH 8_each_CMST",300,0.2,1194.00078 Acute Respiratory Infections,Treatment of severe pneumonia,138,"Oxygen, 1000 liters, primarily with oxygen concentrators",301,0.576,224.88144 -Acute Respiratory Infections,Treatment of severe pneumonia,138,Prednisolone 5mg_100_CMST,291,1.7999999999999998,8.3181 +Acute Respiratory Infections,Treatment of severe pneumonia,138,Prednisolone 5mg_100_CMST,291,1.8,8.3181 Acute Respiratory Infections,Treatment of severe pneumonia,138,"Salbutamol, syrup, 2 mg/5 ml",297,0.4,6.9972 Acute Respiratory Infections,Treatment of severe pneumonia,138,"Syringe, needle + swab",9,0.36,7.7469 Acute Respiratory Infections,Treatment of severe pneumonia,138,Amoxycillin 250mg_1000_CMST,125,0.006,16460.99868 -Acute Respiratory Infections,Treatment of severe pneumonia,138,Cannula iv (winged with injection pot) 16_each_CMST,120,1.0,77.34048 -Acute Respiratory Infections,Treatment of severe pneumonia,138,X-ray,175,1.0,182.51982 -Acute Respiratory Infections,Asthma severe 1 step adult,139,Prednisolone 5mg_100_CMST,291,56.0,8.3181 +Acute Respiratory Infections,Treatment of severe pneumonia,138,Cannula iv (winged with injection pot) 16_each_CMST,120,1,77.34048 +Acute Respiratory Infections,Treatment of severe pneumonia,138,X-ray,175,1,182.51982 +Acute Respiratory Infections,Asthma severe 1 step adult,139,Prednisolone 5mg_100_CMST,291,56,8.3181 Acute Respiratory Infections,Asthma severe 1 step adult,139,Amoxycillin 250mg_1000_CMST,125,0.03,16460.99868 -Acute Respiratory Infections,Asthma severe 1 step adult,139,Glove disposable latex medium_100_CMST,172,6.0,24.57588 -Acute Respiratory Infections,Asthma severe 1 step adult,139,"Salbutamol solution for nebulising 5mg/ml, 30ml",302,2.0,676.25082 -Acute Respiratory Infections,Asthma severe 1 step adult,139,"IV giving/infusion set, with needle",34,1.0,231.84294 -Acute Respiratory Infections,Asthma severe 1 step adult,139,X-Ray developer for manual process,303,1.0,2.6418 -Acute Respiratory Infections,Asthma severe 1 step adult,139,Cannula iv (winged with injection pot) 18_each_CMST,171,1.0,130.07652 -Acute Respiratory Infections,Asthma severe 1 step adult,139,"Plaster, elastic adhesive 7.5cm x 5m_each_CMST",304,1.0,869.57346 -Acute Respiratory Infections,Asthma severe 1 step adult,139,Hydrocotisone IV - 200mg,305,15.0,478.33002 -Acute Respiratory Infections,Asthma severe 1 step adult,139,"Oxygen, 1000 liters, primarily with oxygen concentrators",301,1.0,224.88144 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Prednisolone 5mg_100_CMST,291,56.0,8.3181 +Acute Respiratory Infections,Asthma severe 1 step adult,139,Glove disposable latex medium_100_CMST,172,6,24.57588 +Acute Respiratory Infections,Asthma severe 1 step adult,139,"Salbutamol solution for nebulising 5mg/ml, 30ml",302,2,676.25082 +Acute Respiratory Infections,Asthma severe 1 step adult,139,"IV giving/infusion set, with needle",34,1,231.84294 +Acute Respiratory Infections,Asthma severe 1 step adult,139,X-Ray developer for manual process,303,1,2.6418 +Acute Respiratory Infections,Asthma severe 1 step adult,139,Cannula iv (winged with injection pot) 18_each_CMST,171,1,130.07652 +Acute Respiratory Infections,Asthma severe 1 step adult,139,"Plaster, elastic adhesive 7.5cm x 5m_each_CMST",304,1,869.57346 +Acute Respiratory Infections,Asthma severe 1 step adult,139,Hydrocotisone IV - 200mg,305,15,478.33002 +Acute Respiratory Infections,Asthma severe 1 step adult,139,"Oxygen, 1000 liters, primarily with oxygen concentrators",301,1,224.88144 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Prednisolone 5mg_100_CMST,291,56,8.3181 Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Amoxycillin 250mg_1000_CMST,125,0.03,16460.99868 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Glove disposable latex medium_100_CMST,172,6.0,24.57588 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Salbutamol solution for nebulising 5mg/ml, 30ml",302,2.0,676.25082 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"IV giving/infusion set, with needle",34,1.0,231.84294 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Sodium chloride 0.9%, 1000ml_each_CMST",306,1.0,783.05808 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Cannula iv (winged with injection pot) 18_each_CMST,171,1.0,130.07652 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Plaster, elastic adhesive 7.5cm x 5m_each_CMST",304,1.0,869.57346 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Hydrocotisone IV - 200mg,305,15.0,478.33002 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Glove disposable latex medium_100_CMST,172,6,24.57588 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Salbutamol solution for nebulising 5mg/ml, 30ml",302,2,676.25082 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"IV giving/infusion set, with needle",34,1,231.84294 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Sodium chloride 0.9%, 1000ml_each_CMST",306,1,783.05808 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Cannula iv (winged with injection pot) 18_each_CMST,171,1,130.07652 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Plaster, elastic adhesive 7.5cm x 5m_each_CMST",304,1,869.57346 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,Hydrocotisone IV - 200mg,305,15,478.33002 Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Oxygen, 1000 liters, primarily with oxygen concentrators",301,0.05,224.88144 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Aminophylline 100mg, tablets",292,2.0,3.22728 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Atropine sulphate 600 micrograms/ml, 1ml_each_CMST",307,2.0,170.84592 -Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Adrenaline 1/1000, 1ml_each_CMST",308,1.0,251.52792 -Acute Respiratory Infections,COPD,141,Prednisolone 5mg_100_CMST,291,80.0,8.3181 -Acute Respiratory Infections,COPD,141,Amoxycillin 250mg_1000_CMST,125,0.0,16460.99868 -Acute Respiratory Infections,COPD,141,Glove disposable latex medium_100_CMST,172,1.0,24.57588 -Acute Respiratory Infections,COPD,141,Salbutamol 4mg_1000_CMST,121,2.0,2.76318 -Acute Respiratory Infections,COPD,141,Salbutamol Inhaler 100mcg/dose - 200 doses ,293,1.0,960.73698 -Acute Respiratory Infections,COPD,141,X-ray,175,1.0,182.51982 -Acute Respiratory Infections,COPD,141,Complete blood count,128,1.0,378.99834 -Eye and Ear infection,Treatment of conjunctivitis,142,"Tetracycline eye ointment, 1 %, tube 5 mg",68,21.0,31.68018 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Aminophylline 100mg, tablets",292,2,3.22728 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Atropine sulphate 600 micrograms/ml, 1ml_each_CMST",307,2,170.84592 +Acute Respiratory Infections,Asthma severe +n't resp 1 step,140,"Adrenaline 1/1000, 1ml_each_CMST",308,1,251.52792 +Acute Respiratory Infections,COPD,141,Prednisolone 5mg_100_CMST,291,80,8.3181 +Acute Respiratory Infections,COPD,141,Amoxycillin 250mg_1000_CMST,125,0,16460.99868 +Acute Respiratory Infections,COPD,141,Glove disposable latex medium_100_CMST,172,1,24.57588 +Acute Respiratory Infections,COPD,141,Salbutamol 4mg_1000_CMST,121,2,2.76318 +Acute Respiratory Infections,COPD,141,Salbutamol Inhaler 100mcg/dose - 200 doses ,293,1,960.73698 +Acute Respiratory Infections,COPD,141,X-ray,175,1,182.51982 +Acute Respiratory Infections,COPD,141,Complete blood count,128,1,378.99834 +Eye and Ear infection,Treatment of conjunctivitis,142,"Tetracycline eye ointment, 1 %, tube 5 mg",68,21,31.68018 Eye and Ear infection,Treatment of conjunctivitis,142,Paracetamol 500mg _1000_CMST,94,0.03,4353.87918 -Eye and Ear infection,Treatment of conjunctivitis,142,Cotton swab,24,1.0,1.9992 +Eye and Ear infection,Treatment of conjunctivitis,142,Cotton swab,24,1,1.9992 Eye and Ear infection,Acute otitis media in under 5s,143,Paracetamol 500mg _1000_CMST,94,0.015,4353.87918 -Eye and Ear infection,Acute otitis media in under 5s,143,Cotrimoxazole 480mg_1000_CMST,309,2.0,14.12292 -Eye and Ear infection,Scabies and other skin diseases,144,"Benzyl benzoate 25% lotion, 1000 ml bottle",310,1.0,3147.76896 -Eye and Ear infection,Scabies and other skin diseases,144,Erythromycin 250mg_1000_CMST,311,13.200000000000001,54.64956 +Eye and Ear infection,Acute otitis media in under 5s,143,Cotrimoxazole 480mg_1000_CMST,309,2,14.12292 +Eye and Ear infection,Scabies and other skin diseases,144,"Benzyl benzoate 25% lotion, 1000 ml bottle",310,1,3147.76896 +Eye and Ear infection,Scabies and other skin diseases,144,Erythromycin 250mg_1000_CMST,311,13.2,54.64956 Eye and Ear infection,Trachoma mass drug administration,145,Azithromycin 500mg_10_CMST,312,1.6,96.62562 Eye and Ear infection,Trachoma mass drug administration,145,"Tetracycline eye ointment, 1 %, tube 5 mg",68,1.92,31.68018 Eye and Ear infection,Trachoma mass drug administration,145,"azithromycin 200 mg/5 ml, pwd for or. susp., 15 ml_120_IDA",313,0.36,469.9191 Eye and Ear infection,Treatment of cataracts,146,Cataract set,314,0.1,940338 -Oral Health,Management of severe tooth pain - tooth extraction,147,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Management of severe tooth pain - tooth extraction,147,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 -Oral Health,Management of mild tooth pain - tooth filling,148,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Management of mild tooth pain - tooth filling,148,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 -Oral Health,Management of mild tooth pain - tooth filling,148,"Amalgam capsule no. 2, non-gamma _50_CMST",316,1.0,761.03118 +Oral Health,Management of severe tooth pain - tooth extraction,147,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Management of severe tooth pain - tooth extraction,147,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 +Oral Health,Management of mild tooth pain - tooth filling,148,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Management of mild tooth pain - tooth filling,148,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 +Oral Health,Management of mild tooth pain - tooth filling,148,"Amalgam capsule no. 2, non-gamma _50_CMST",316,1,761.03118 Oral Health,Management of mild tooth pain - tooth filling,148,Composite chemical cure & etching system,317,0.02,0 Oral Health,Management of mild tooth pain - tooth filling,148,Zinc oxide eugenol liquid+powder_10_CMST,318,0.02,4008.66732 Oral Health,Management of mild tooth pain - tooth filling,148,Zinc oxide eugenol powder_pack_CMST,319,0.02,6563.47356 Oral Health,Management of mild tooth pain - tooth filling,148,Glass ionomer reinforced powder & liquid (Fujii IX),320,0.02,30565.26186 -Oral Health,Root canal therapy,149,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Root canal therapy,149,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Root canal therapy,149,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Root canal therapy,149,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Root canal therapy,149,Root canal spreader S/E NI-TI_each_CMST,321,0.02,21583.99152 Oral Health,Root canal therapy,149,"Gutta Percha points, PD 15-80",322,0.02,0 Oral Health,Root canal therapy,149,Root canal sealant ( Regular),323,0.02,0 @@ -702,34 +702,34 @@ Oral Health,Root canal therapy,149,Cavit medium,325,0.02,6537.39114 Oral Health,Root canal therapy,149,"Amalgam capsule no. 2, non-gamma _50_CMST",316,0.02,761.03118 Oral Health,Root canal therapy,149,Composite chemical cure & etching system,317,0.02,0 Oral Health,Tooth scaling and polishing,150,Polishing system enhance (Detisply),326,0.01,96233.0271 -Oral Health,Intermaxillary Fixation,151,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Intermaxillary Fixation,151,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Intermaxillary Fixation,151,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Intermaxillary Fixation,151,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Intermaxillary Fixation,151,"Ligature wire, 0.16 inches (0.406mm) roll",327,0.05,11601.33618 Oral Health,Intermaxillary Fixation,151,"Wire ligature 0.5mm, roll _each_CMST",328,0.05,10625.64804 -Oral Health,Bone plating,152,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Bone plating,152,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Bone plating,152,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Bone plating,152,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Bone plating,152,"Ligature wire, 0.16 inches (0.406mm) roll",327,0.05,11601.33618 Oral Health,Bone plating,152,"Wire ligature 0.5mm, roll _each_CMST",328,0.05,10625.64804 -Oral Health,Intraoseous wiring,153,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Intraoseous wiring,153,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Intraoseous wiring,153,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Intraoseous wiring,153,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Intraoseous wiring,153,"Ligature wire, 0.16 inches (0.406mm) roll",327,0.05,11601.33618 Oral Health,Intraoseous wiring,153,"Wire ligature 0.5mm, roll _each_CMST",328,0.05,10625.64804 -Oral Health,Tooth splinting,154,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Tooth splinting,154,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Tooth splinting,154,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Tooth splinting,154,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Tooth splinting,154,"Ligature wire, 0.16 inches (0.406mm) roll",327,0.05,11601.33618 -Oral Health,Enucleation and marsupulization of dental cysts,155,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Enucleation and marsupulization of dental cysts,155,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 -Oral Health,Excision and incisional biopsy of dental tumors,156,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Excision and incisional biopsy of dental tumors,156,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 -Oral Health,Incision and drainage of dental abscess,157,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Incision and drainage of dental abscess,157,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Enucleation and marsupulization of dental cysts,155,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Enucleation and marsupulization of dental cysts,155,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 +Oral Health,Excision and incisional biopsy of dental tumors,156,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Excision and incisional biopsy of dental tumors,156,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 +Oral Health,Incision and drainage of dental abscess,157,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Incision and drainage of dental abscess,157,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Denture,158,Alginate impression material (Supreme),329,0.1,6288.47646 Oral Health,Denture,158,"POP dental stone, ortho",330,0.1,38361.01374 Oral Health,Denture,158,"POP dental stone, yellow",331,0.1,3049.05846 Oral Health,Denture,158,"Wax, modelling, no. 4 gauge",332,0.05,0 Oral Health,Denture,158,"Tungstein Carbide Acrylic Trimmers, C75/060",333,0.05,16362.26676 -Oral Health,Tooth implants,159,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1.0,216.45624 -Oral Health,Tooth implants,159,"Needle, disposable dental, 27g long sharewood",315,1.0,0.79254 +Oral Health,Tooth implants,159,"Lignocaine 2% Adrenaline 1/80,000 cartridge 1.8ml_50_CMST",116,1,216.45624 +Oral Health,Tooth implants,159,"Needle, disposable dental, 27g long sharewood",315,1,0.79254 Oral Health,Tooth implants,159,Alginate impression material (Supreme),329,0.1,6288.47646 Oral Health,Tooth implants,159,"POP dental stone, ortho",330,0.1,38361.01374 Oral Health,Tooth implants,159,"POP dental stone, yellow",331,0.1,3049.05846 @@ -748,1710 +748,1710 @@ Oral Health,Orthodontic appliances,161,Pumice,334,0.03333,14069.07726 Oral Health,Orthodontic appliances,161,Orthodontic wire (tubing size 0.8),336,0.05,9694.49922 Oral Health,Topical tooth fluoride application,162,Fluoride varnish (Duraphat),337,0.02,30412.17312 Oral Health,Topical tooth fluoride application,162,Prophylactic paste,338,0.02,5399.99628 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Acetyl salysilic acid (aspirin), tablet, 75 mg",339,365.0,9.48906 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Enalapril, tablet, 20 mg",219,365.0,9.48906 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Acetyl salysilic acid (aspirin), tablet, 75 mg",339,365,9.48906 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Enalapril, tablet, 20 mg",219,365,9.48906 Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Atenolol, tablets, 50 mg",340,547.5,1.89924 Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Simvastatin, 15 mg",234,273.75,223.99608 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Prednisolone, tablet, 5 mg",341,54.60000000000001,59.99742 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Blood glucose level test,216,2.0,685.99692 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Cholesterol test,217,2.0,685.99692 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Urine analysis,47,2.0,627.9987 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Acetyl salysilic acid (aspirin), tablet, 75 mg",339,365.0,9.48906 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Enalapril, tablet, 20 mg",219,365.0,9.48906 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Prednisolone, tablet, 5 mg",341,54.6,59.99742 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Blood glucose level test,216,2,685.99692 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Cholesterol test,217,2,685.99692 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Urine analysis,47,2,627.9987 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Acetyl salysilic acid (aspirin), tablet, 75 mg",339,365,9.48906 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Enalapril, tablet, 20 mg",219,365,9.48906 Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Atenolol, tablets, 50 mg",340,547.5,1.89924 Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Simvastatin, 15 mg",234,273.75,223.99608 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Prednisolone, tablet, 5 mg",341,54.60000000000001,59.99742 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Blood glucose level test,216,2.0,685.99692 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Cholesterol test,217,2.0,685.99692 -Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Urine analysis,47,2.0,627.9987 -Imported From One Health,Misc,-99,"Artemether + Lumefantrine, tablets, 20 + 120 mg, 6 x 1 blister",1000,1.0,99.66012 -Imported From One Health,Misc,-99,Artemether 20 mg/ml injection/1 ml,1001,1.0,484.07058 -Imported From One Health,Misc,-99,"Artesunate + Amodiaquine, tablets, 50 mg + 153 mg, 3 + 3 blister",1002,1.0,218.3055 -Imported From One Health,Misc,-99,"Artesunate + SP, tablets, 50 mg + 500 mg + 25 mg, 3 + 1 blister",1003,1.0,393.89952 -Imported From One Health,Misc,-99,Bacteriuria test,1004,1.0,85.42296 -Imported From One Health,Misc,-99,"Betamethasone, 12 mg injection",1005,1.0,10279.45086 -Imported From One Health,Misc,-99,Blood culture,1006,1.0,0.0 -Imported From One Health,Misc,-99,"Calcium, tablet, 600 mg",1007,1.0,14.23716 -Imported From One Health,Misc,-99,"Ceftriaxone, powder for injection, 250 ml vial",1008,1.0,207.10998 -Imported From One Health,Misc,-99,"Chloramphenicol, powder/inj, 1 g vial",1009,1.0,930.17778 -Imported From One Health,Misc,-99,"Chloramphenicol, oral suspension 125 mg/5 ml, 60 ml bottle",1010,1.0,484.07058 -Imported From One Health,Misc,-99,"Ciprofloxacin, tablet, 250 mg",1011,1.0,16.20066 -Imported From One Health,Misc,-99,"Condom, female",1012,1.0,427.12194 -Imported From One Health,Misc,-99,Depot-Medroxyprogesterone Acetate 25 mg + estradiol cypionate 5 mg - 1 monthly,1013,1.0,0.0 -Imported From One Health,Misc,-99,"Desogestrel 0.15 mg + Ethinyl estradiol 30 mcg, cycle",1014,1.0,0.0 -Imported From One Health,Misc,-99,Dietary supplements (country-specific),1015,1.0,0.0 -Imported From One Health,Misc,-99,"Digoxin, tabcap, 250 mcg",1016,1.0,9.48906 -Imported From One Health,Misc,-99,DTP vaccine,1017,1.0,99.66012 -Imported From One Health,Misc,-99,Drug kit for C-section and complex deliveries,1018,1.0,1434505.11834 -Imported From One Health,Misc,-99,"Ergometrine, tablet, 0.2 mg",1019,1.0,14.23716 -Imported From One Health,Misc,-99,"Ethambutol, tab-cap, 100 mg",1020,1.0,9.48906 -Imported From One Health,Misc,-99,"Ethambutol, tab-cap, 400 mg",1021,1.0,28.47432 -Imported From One Health,Misc,-99,"F-100 therapeutic diet, sachet, 456 g for 2.4 liters liquid diet",1022,1.0,455.59626 -Imported From One Health,Misc,-99,"F-100 therapeutic milk,sachet, 456 g",1023,1.0,1414.2555 -Imported From One Health,Misc,-99,"F-75 therapeutic diet, sachet, 410 g for 2.4 liters liquid diet",1024,1.0,346.44708 -Imported From One Health,Misc,-99,"Folic acid, tablet, 5 mg",1025,1.0,4.7481 -Imported From One Health,Misc,-99,"Furosemide, tablets, 40 mg",1026,1.0,4.7481 -Imported From One Health,Misc,-99,"Gauze pad, 10 x 10 cm, non-sterile",1027,1.0,23.72622 -Imported From One Health,Misc,-99,Gentamicin inj 10 mg/ml 2 ml amp,1028,1.0,90.17106 -Imported From One Health,Misc,-99,"Glucose inj 5 %, 500 ml with giving set",1029,1.0,688.14606 -Imported From One Health,Misc,-99,"Glucose inj 5 %, 500 ml with giving set",1030,1.0,683.39796 -Imported From One Health,Misc,-99,Hib vaccine,1031,1.0,0.0 -Imported From One Health,Misc,-99,"Injection supplies (cotton, tape, etc)",1032,1.0,37.96338 -Imported From One Health,Misc,-99,"IUD, Multiload 375 Standard/SL",1033,1.0,991.87452 -Imported From One Health,Misc,-99,"Levonorgestrel 0.03 mg, cycle of 28 pills",1034,1.0,199.32738 -Imported From One Health,Misc,-99,"Levonorgestrel 0.05/0.075/0.125 mg +Ethinyl estradiol 30/40/30 mcg, cycle",1035,1.0,151.8678 -Imported From One Health,Misc,-99,"Levonorgestrel 0.15/0.2 mg + Ethinyl estradiol 30/40 mcg, cycle",1036,1.0,0.0 -Imported From One Health,Misc,-99,"Lynestrenol 0.5 mg, cycle",1037,1.0,802.04334 -Imported From One Health,Misc,-99,"Mebendazole, chewable tablet, 100 mg",1038,1.0,901.70346 -Imported From One Health,Misc,-99,"Metformin, tablet, 500 mg",1039,1.0,4.7481 -Imported From One Health,Misc,-99,"Metronidazole, tablet, 200 mg",1040,1.0,4.7481 -Imported From One Health,Misc,-99,"Micronutrient, film-coated tablet",1041,1.0,9.48906 -Imported From One Health,Misc,-99,Microscopy,1042,1.0,0.0 -Imported From One Health,Misc,-99,Mucus extractor,1043,1.0,683.39796 -Imported From One Health,Misc,-99,"Multiple micronutrient powder, sachet",1044,1.0,14.23716 -Imported From One Health,Misc,-99,"Nasogastric tube, CH12, 125 cm, disposable",1045,1.0,294.2394 -Imported From One Health,Misc,-99,Nitrite test,1046,1.0,0.0 -Imported From One Health,Misc,-99,FBC,1047,1.0,1043.60382 -Imported From One Health,Misc,-99,Norethisterone enanthate 200 mg - 2 monthly,1048,1.0,830.51766 -Imported From One Health,Misc,-99,Norethisterone enanthate 200 mg + 5 mg estradiol valerate - 1 monthly,1049,1.0,607.46406 -Imported From One Health,Misc,-99,"Norgestrel 0.30 mcg + Ethinyl estradiol 30 mcg (Lofemenal), cycle",1050,1.0,175.59402 -Imported From One Health,Misc,-99,"Nutrition Kit for therapeutic feeding, clinic based",1051,1.0,13326.26736 -Imported From One Health,Misc,-99,Partograph,1052,1.0,0.0 -Imported From One Health,Misc,-99,"Pyrazinamide, tablets, 500 mg",1053,1.0,28.47432 -Imported From One Health,Misc,-99,"Quinine, injection, 300 mg/ml, 2 ml ampoule",1054,1.0,194.57928 -Imported From One Health,Misc,-99,"ReSoMal, 42 g sachet for 1 liter",1055,1.0,271.32 -Imported From One Health,Misc,-99,"Rifampicin + Isoniazid + Pyrazinamide, 150 mg + 75 mg + 400 mg, tablet",1056,1.0,33.22242 -Imported From One Health,Misc,-99,"Rifampicin + Isoniazid, 150 mg + 75 mg, tablet",1057,1.0,0.0 -Imported From One Health,Misc,-99,RPR test kit,1058,1.0,66.4377 -Imported From One Health,Misc,-99,"Salbutamol, oral inhaler, 0.1 mg/dose",1059,1.0,4.7481 -Imported From One Health,Misc,-99,Slide and stain for microscopy,1060,1.0,109.15632 -Imported From One Health,Misc,-99,"Soap, bar",1061,1.0,0.0 -Imported From One Health,Misc,-99,"Suture, absorbable, synthetic, 1/0, curved needle",1062,1.0,403.39572 -Imported From One Health,Misc,-99,"Suture, absorbable, synthetic, 3/0, curved needle",1063,1.0,341.69898 -Imported From One Health,Misc,-99,"Test, blood glucose",1064,1.0,0.0 -Imported From One Health,Misc,-99,"Test, blood group, anti A + B, 10 ml",1065,1.0,0.0 -Imported From One Health,Misc,-99,"Vaginal cream (Benzalkonium Chloride) with applicator, tube for 30 applications",1066,1.0,2277.99558 -Imported From One Health,Misc,-99,"Vaginal Foaming Tablet, Neo Sampoon, tube of 20 tablets",1067,1.0,1428.49266 -Imported From One Health,Misc,-99,"Vaginal Foaming Tablets (Benzalkonium Chloride), tube with 12 tablets",1068,1.0,650.17554 -Imported From One Health,Misc,-99,"Vitamin A, caplet, 50,000 IU",1069,1.0,23.72622 -Imported From One Health,Misc,-99,Slides/reagents required for TB detection,1070,1.0,147.1197 -Imported From One Health,Misc,-99,Sputum container,1071,1.0,37.96338 -Imported From One Health,Misc,-99,Cat. II Patient Kit B1,1072,1.0,0.0 -Imported From One Health,Misc,-99,Cat. II Patient Kit B2,1073,1.0,0.0 -Imported From One Health,Misc,-99,Pediatric patient kit,1074,1.0,2913.93396 -Imported From One Health,Misc,-99,"Ethambutol/Isoniazid, tablet, 400 mg + 150 mg",1075,1.0,18.98526 -Imported From One Health,Misc,-99,"Ethambutol/Isoniazid, tablet, 400 mg + 150 mg, on blister sheet",1076,1.0,18.98526 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 150 mg + 150 mg",1077,1.0,28.47432 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 150 mg + 150 mg, on blister sheet",1078,1.0,18.98526 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablets, 150 mg + 75 mg",1079,1.0,33.22242 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablets, 150 mg + 75 mg, on blister sheet",1080,1.0,14.23716 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Ethambutol, tablet, 150 mg + 75 mg + 275 mg",1081,1.0,23.72622 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Ethambutol, tablet, 150 mg + 75 mg + 275 mg, on blister sheet",1082,1.0,37.96338 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide/Ethambutol, tablet, 150 mg + 75 mg + 400 mg + 275 mg",1083,1.0,28.47432 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide/Ethambutol, tablet, 150 mg + 75 mg + 400 mg + 275 mg, on blister sheet",1084,1.0,33.22242 -Imported From One Health,Misc,-99,Rifampicin 150 mg / Isoniazid 75 mg / Pyrazinamide 400 mg / Ethambutol 275 mg - Box of 24 blister sheets,1085,1.0,52.20054 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 60 mg + 30 mg",1086,1.0,0.0 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 60 mg + 30 mg, in jar",1087,1.0,14.23716 -Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide, tablet, 60 mg + 30 mg + 150 mg",1088,1.0,14.23716 -Imported From One Health,Misc,-99,"Amikacin, powder for injection, 500 mg vial",1089,1.0,0.0 -Imported From One Health,Misc,-99,"Amikacin, solution for injection, 500 mg/2 ml vial",1090,1.0,0.0 -Imported From One Health,Misc,-99,"Capreomycin, powder for injection, 1 g vial",1091,1.0,10611.65364 -Imported From One Health,Misc,-99,"Cycloserine, capsule, 250 mg, on strip",1092,1.0,0.0 -Imported From One Health,Misc,-99,"Ethionamide, tablet, 250 mg, in jar",1093,1.0,113.89728 -Imported From One Health,Misc,-99,"Ethionamide, tablet, 250 mg, on blister sheet",1094,1.0,0.0 -Imported From One Health,Misc,-99,"Kanamycin, solution for injection, 1 g/4 ml vial",1095,1.0,223.0536 -Imported From One Health,Misc,-99,"Levofloxacin, tablet, 250 mg, on blister sheet",1096,1.0,0.0 -Imported From One Health,Misc,-99,"Levofloxacin, tablet, 500 mg, on blister sheet",1097,1.0,403.39572 -Imported From One Health,Misc,-99,"Moxifloxacin, tablet, 400 mg, on blister sheet",1098,1.0,0.0 -Imported From One Health,Misc,-99,"Ofloxacin, tablet, 200 mg, on blister sheet",1099,1.0,232.54266 -Imported From One Health,Misc,-99,"Ofloxacin, tablet, 400 mg, on blister sheet",1100,1.0,156.6159 -Imported From One Health,Misc,-99,"PAS, acid sachet granules, 4 g",1101,1.0,0.0 -Imported From One Health,Misc,-99,"PAS sodium mini-granules (60% PAS), 100 g jar",1102,1.0,0.0 -Imported From One Health,Misc,-99,"Prothionamide, tablet, 250 mg, in jar",1103,1.0,0.0 -Imported From One Health,Misc,-99,"TB drugs, MDR, average cost per patient",1104,1.0,1642201.23522 -Imported From One Health,Misc,-99,TB/HIV Care and support for 6 months,1105,1.0,0.0 -Imported From One Health,Misc,-99,"Abacavir (ABC), tablet, 300 mg",1106,1.0,422.38098 -Imported From One Health,Misc,-99,"Abacavir/Lamivudine (ABC+3TC), tablet, 600 + 150 mg",1107,1.0,0.0 -Imported From One Health,Misc,-99,AZT + 3TC + EFV (co-blister),1108,1.0,0.0 -Imported From One Health,Misc,-99,"Didanosine (ddl), unbuffered enteric coated capsule, 250 mg",1109,1.0,384.41046 -Imported From One Health,Misc,-99,"Didanosine (ddl), unbuffered enteric coated capsule, 400 mg",1110,1.0,550.51542 -Imported From One Health,Misc,-99,"Efavirenz (EFV), tablet, 600 mg ",1111,1.0,118.64538 -Imported From One Health,Misc,-99,"Emtricitabine (FTC), capsule 200 mg",1112,1.0,156.6159 -Imported From One Health,Misc,-99,"Lamiduvine/Zidovudine/Nevirapine (3TC + AZT + NVP), tablet, 150 + 300 + 200 mg",1113,1.0,80.682 -Imported From One Health,Misc,-99,"Lamivudine (3TC), tablet, 150 mg",1114,1.0,33.22242 -Imported From One Health,Misc,-99,"Lamivudine/Stavudine (3TC + d4T), tablet, 150 + 30 mg",1115,1.0,37.96338 -Imported From One Health,Misc,-99,"Lamivudine/Stavudine (3TC + d4T), tablet, 150 + 40 mg",1116,1.0,99.66012 -Imported From One Health,Misc,-99,"Lamivudine/Stavudine/Nevirapine (3TC + d4T + NVP), tablet, 150 + 30 + 200 mg",1117,1.0,227.8017 -Imported From One Health,Misc,-99,"Lamivudine/Stavudine/Nevirapine (3TC + d4T + NVP), tablet, 150 + 40 + 200 mg",1118,1.0,256.27602 -Imported From One Health,Misc,-99,"Lamivudine/Zidovudine, tablet (3TC+AZT), 150 + 300 mg",1119,1.0,223.0536 -Imported From One Health,Misc,-99,"Lamivudine/Zidovudine/Abacavir (3TC + AZT + ABC), tablet, 300 + 150 + 300 mg",1120,1.0,1072.55652 -Imported From One Health,Misc,-99,"Lopinavir/Ritonavir (LPV/r), capsule, 133.3 + 33.3 mg",1121,1.0,583.73784 -Imported From One Health,Misc,-99,"Nevirapine (NVP), tablet, 200 mg",1122,1.0,4.7481 -Imported From One Health,Misc,-99,"Stavudine (d4T), capsule, 40 mg",1123,1.0,23.72622 -Imported From One Health,Misc,-99,Fansidar (sulphadoxine / pyrimethamine tab),1124,1.0,327.46182 -Imported From One Health,Misc,-99,TDF + FTC + EFV (co-formulation),1125,1.0,0.0 -Imported From One Health,Misc,-99,"Tenofovir (TDF), tablet, 300 mg",1126,1.0,156.6159 -Imported From One Health,Misc,-99,"Test, HIV 1 + 2, Doublecheck, rapid test ",1127,1.0,934.92588 -Imported From One Health,Misc,-99,"Zidovudine (AZT), tablet/capsule, 250 mg ",1128,1.0,246.77982 -Imported From One Health,Misc,-99,"Zidovudine (AZT), tablet/capsule, 300 mg ",1129,1.0,94.91916 -Imported From One Health,Misc,-99,"Zidovudine (AZT), capsule, 100 mg",1130,1.0,56.94864 -Imported From One Health,Misc,-99,"Zidovudine (AZT), capsule, 250 mg",1131,1.0,322.71372 -Imported From One Health,Misc,-99,"Zidovudine (AZT), injection, 10 mg/ml in 20 ml vial",1132,1.0,15912.7395 -Imported From One Health,Misc,-99,"Zidovudine (AZT), oral solution, 10 mg/ml 100 mL, bottle ",1133,1.0,1314.59538 -Imported From One Health,Misc,-99,PEP Kit,1134,1.0,384131.50734 -Imported From One Health,Misc,-99,"Doxycycline, tablet, 500 mg",1135,1.0,17.16456 -Imported From One Health,Misc,-99,"Ferrous Salt + Folic Acid, tablet, 60 + 0.4 mg",1136,1.0,0.0 -Imported From One Health,Misc,-99,"Metronidazole, tablet, 500 mg",1137,1.0,5.26932 -Imported From One Health,Misc,-99,LAM drugs/supplies to service a client,1138,1.0,0.0 -Imported From One Health,Misc,-99,Other contraceptives drugs/supplies to service a client,1139,1.0,0.0 -Imported From One Health,Misc,-99,Other ANC components drugs/supplies to service a client,1140,1.0,0.0 -Imported From One Health,Misc,-99,Other complications drugs/supplies to service a client,1141,1.0,0.0 -Imported From One Health,Misc,-99,MgSO4 - Management of pre-eclampsia drugs/supplies to service a client,1142,1.0,0.0 -Imported From One Health,Misc,-99,Labor and delivery management drugs/supplies to service a client,1143,1.0,0.0 -Imported From One Health,Misc,-99,Pre-referal management of labor complications drugs/supplies to service a client,1144,1.0,0.0 -Imported From One Health,Misc,-99,KMC - Kangaroo mother care drugs/supplies to service a client,1145,1.0,0.0 -Imported From One Health,Misc,-99,Induction of labor (beyond 41 weeks) drugs/supplies to service a client,1146,1.0,0.0 -Imported From One Health,Misc,-99,Maternal Sepsis case management drugs/supplies to service a client,1147,1.0,0.0 -Imported From One Health,Misc,-99,Preventive postnatal care drugs/supplies to service a client,1148,1.0,0.0 -Imported From One Health,Misc,-99,Breast cancer screening drugs/supplies to service a client,1149,1.0,0.0 -Imported From One Health,Misc,-99,Identification and management of infertility drugs/supplies to service a client,1150,1.0,0.0 -Imported From One Health,Misc,-99,Treatment of severe diarrhea drugs/supplies to service a client,1151,1.0,0.0 -Imported From One Health,Misc,-99,Treatment of severe pneumonia drugs/supplies to service a client,1152,1.0,0.0 -Imported From One Health,Misc,-99,Treatment of severe malaria drugs/supplies to service a client,1153,1.0,0.0 -Imported From One Health,Misc,-99,Treatment of severe measles drugs/supplies to service a client,1154,1.0,0.0 -Imported From One Health,Misc,-99,Malaria case management drugs/supplies to service a client,1155,1.0,0.0 -Imported From One Health,Misc,-99,Mass media,1156,1.0,711.87228 -Imported From One Health,Misc,-99,Community mobilization,1157,1.0,5424.66498 -Imported From One Health,Misc,-99,Youth focused interventions - In-school drugs/supplies to service a client,1158,1.0,11588.20572 -Imported From One Health,Misc,-99,Workplace programs drugs/supplies to service a client,1159,1.0,5117.75208 -Imported From One Health,Misc,-99,Blood safety drugs/supplies to service a client,1160,1.0,64917.51546 -Imported From One Health,Misc,-99,Universal precautions drugs/supplies to service a client,1161,1.0,214131.44886 -Imported From One Health,Misc,-99,Additional ART for TB patients drugs/supplies to service a client,1162,1.0,0.0 -Imported From One Health,Misc,-99,Diagnostics/lab costs drugs/supplies to service a client,1163,1.0,0.0 -Imported From One Health,Misc,-99,Management of opportunistic infections drugs/supplies to service a client,1164,1.0,0.0 -Imported From One Health,Misc,-99,ART - Antiretroviral therapy for HIV positive children drugs/supplies to service a client,1165,1.0,0.0 -Imported From One Health,Misc,-99,VCT for TB cases drugs/supplies to service a client,1166,1.0,0.0 -Imported From One Health,Misc,-99,HIV prevention for TB patients drugs/supplies to service a client,1167,1.0,0.0 -Imported From One Health,Misc,-99,ART (+CPT) for TB HIV+ patients drugs/supplies to service a client,1168,1.0,0.0 -Imported From One Health,Misc,-99,Folic acid fortification drugs/supplies to service a client,1169,1.0,0.0 -Imported From One Health,Misc,-99,Breastfeeding promotion drugs/supplies to service a client,1170,1.0,0.0 -Imported From One Health,Misc,-99,Complementary feeding--education only drugs/supplies to service a client,1171,1.0,0.0 -Imported From One Health,Misc,-99,Improved water source - cost per HH,1172,1.0,0.0 -Imported From One Health,Misc,-99,Water connection in the home - cost per HH,1173,1.0,0.0 -Imported From One Health,Misc,-99,Improved sanitation - cost per HH,1174,1.0,0.0 -Imported From One Health,Misc,-99,ART (Second-Line Treatment) for adults drugs/supplies to service a client,1175,1.0,0.0 -Imported From One Health,Misc,-99,DST test for first-line drugs (liquid media),1176,1.0,57120.70686 -Imported From One Health,Misc,-99,DST test for first-line drugs,1177,1.0,57120.70686 -Imported From One Health,Misc,-99,DST test for second-line drugs,1178,1.0,57120.70686 -Imported From One Health,Misc,-99,First-line treatment – for new drug sensitive patients,1179,1.0,711.87228 -Imported From One Health,Misc,-99,First-line treatment – for re-retreatment patients,1180,1.0,711.87228 -Imported From One Health,Misc,-99,First-line treatment – children,1181,1.0,711.87228 -Imported From One Health,Misc,-99,HIV prevention education,1182,1.0,2641.80714 -Imported From One Health,Misc,-99,Cotrimoxazole preventive therapy for TB HIV+ patients,1183,1.0,711.87228 -Imported From One Health,Misc,-99,MSAM Drug Kit,1184,1.0,71400.87822 -Imported From One Health,Misc,-99,"Ferrous salt, tablets, 60 mg",1185,1.0,0.0 -Imported From One Health,Misc,-99,Infant formula,1186,1.0,71.1858 -Imported From One Health,Misc,-99,AZT + 3TC + NVP,1187,1.0,711.87228 -Imported From One Health,Misc,-99,"Cannula, IV, 18G, sterile, disposable ",1188,1.0,99.66012 -Imported From One Health,Misc,-99,"Lopinavir/ritonavir (LPV/r), tablet, 200/50 mg",1189,1.0,199.32738 -Imported From One Health,Misc,-99,"Didanosine(ddI), capsule, 400 or 250 mg ",1190,1.0,498.30774 -Imported From One Health,Misc,-99,"Tenofovir (TDF)/Emtricitabine (FTC), tablet, 300/200 mg",1191,1.0,251.52792 -Imported From One Health,Misc,-99,Meningococcal A vaccine,1192,1.0,1248.15054 -Imported From One Health,Misc,-99,Towel,1193,1.0,355.93614 -Imported From One Health,Misc,-99,AZT (60 mg) + 3TC (30 mg) + NVP (50 mg),1194,1.0,52.20054 -Imported From One Health,Misc,-99,AZT 10 mg/ml + 3TC 10 mg/ml + LPV/r (80 + 20 mg/ml),1195,1.0,227.8017 -Imported From One Health,Misc,-99,Hepatitis B vaccine,1196,1.0,151.8678 -Imported From One Health,Misc,-99,"Pentavalent vaccine (DPT, Hep B, Hib)",1197,1.0,248.09358 -Imported From One Health,Misc,-99,"Hydrochlorothiazide, tablet, 25 mg",1198,1.0,0.0 -Imported From One Health,Misc,-99,"Amlodipine, tablet, 10 mg",1199,1.0,137.63064 -Imported From One Health,Misc,-99,Insulin,1200,1.0,640.68648 -Imported From One Health,Misc,-99,"Beclometazone inhaler, 250 mcg/dose",1201,1.0,14.23716 -Imported From One Health,Misc,-99,IV line,1202,1.0,678.64986 -Imported From One Health,Misc,-99,"Doxycycline, capsule or tablet, 100 mg (hydrochloride)",1203,1.0,14.23716 -Imported From One Health,Misc,-99,"Tetracycline, capsule or tablet, 250 mg (hydrochloride)",1204,1.0,14.23716 -Imported From One Health,Misc,-99,"Nystatin 100,000 iu/ml",1205,1.0,18.98526 -Imported From One Health,Misc,-99,Cyclyphosphamide 1000mg injection,1206,1.0,2501.04918 -Imported From One Health,Misc,-99,"Metronidazole, oral solution 200 mg/5 ml",1207,1.0,308.47656 -Imported From One Health,Misc,-99,"Artusenate, 20 mg/ml, 1 ml ampoule",1208,1.0,1428.49266 -Imported From One Health,Misc,-99,"CareStartMal Pf (HRP2/pf-pLDH), kit/60 ",1209,1.0,455.59626 -Imported From One Health,Misc,-99,Gentamicine eye drops 0.3%/5ml,1210,1.0,379.6695 -Imported From One Health,Misc,-99,"Zinc oxide ointment, 10%",1211,1.0,721.36848 -Imported From One Health,Misc,-99,Miconazolenitrate cream 2%/TBE-30g ,1212,1.0,227.8017 -Imported From One Health,Misc,-99,Furosemide inj 10mg/ml 2ml amp,1213,1.0,33.22242 -Imported From One Health,Misc,-99,Paraffin compress,1214,1.0,104.40822 -Imported From One Health,Misc,-99,Cloxacillin,1215,1.0,128.13444 -Imported From One Health,Misc,-99,Erythromicine solution 125 mg/ml,1216,1.0,455.59626 -Imported From One Health,Misc,-99,Permetrine cream 5%,1217,1.0,3962.76426 -Imported From One Health,Misc,-99,"Permethrin shampoo/sol. 1%, 100ml bottle ",1218,1.0,1404.7593 -Imported From One Health,Misc,-99,Pyrantel 125 mg tablet,1219,1.0,14.23716 -Imported From One Health,Misc,-99,"F-75 therapeutic milk, 102.5 g",1220,1.0,3941.28 -Imported From One Health,Misc,-99,"Supplementary spread, sachet 92g/CAR-150",1221,1.0,218.3055 -Imported From One Health,Misc,-99,CSB,1222,1.0,13012.80708 -Imported From One Health,Misc,-99,"F-100 therapeutic diet, sach., 114g/CAR-90",1223,1.0,4533.9 -Imported From One Health,Misc,-99,"Iron syrup, 20 mg/ml",1224,1.0,4.7481 -Imported From One Health,Misc,-99,"Vitamin A caplet, 10,000 IU",1225,1.0,9.48906 -Imported From One Health,Misc,-99,"Iodized oil, 200 mg caplet",1226,1.0,166.10496 -Imported From One Health,Misc,-99,"Therapeutic spread, sachet 92g/CAR-150",1227,1.0,256.27602 -Imported From One Health,Misc,-99,"Ciprofloxacin, 250 mg / 5 ml",1228,1.0,2353.92948 -Imported From One Health,Misc,-99,Nasal prongs,1229,1.0,151.8678 -Imported From One Health,Misc,-99,Hartmann solution,1230,1.0,0.0 -Imported From One Health,Misc,-99,Diazotized reagent,1231,1.0,294.2394 -Imported From One Health,Misc,-99,Alkaline phosphatase reagents,1232,1.0,7825.86126 -Imported From One Health,Misc,-99,Pipettes,1233,1.0,28.47432 -Imported From One Health,Misc,-99,Buffer solution,1234,1.0,142.3716 -Imported From One Health,Misc,-99,Aspirating needle,1235,1.0,15993.41436 -Imported From One Health,Misc,-99,Aspirating syringe,1236,1.0,16007.65152 -Imported From One Health,Misc,-99,Specimen container,1237,1.0,47.45958 -Imported From One Health,Misc,-99,"Scalpel blade, disposable",1238,1.0,113.89728 -Imported From One Health,Misc,-99,Biopsy needle,1239,1.0,16002.91056 -Imported From One Health,Misc,-99,"Electrodes, electrocardiographic",1240,1.0,66.4377 -Imported From One Health,Misc,-99,"Paper, Recording ECG",1241,1.0,23.72622 -Imported From One Health,Misc,-99,"Butylscopolamine, one ampoule",1242,1.0,66.4377 -Imported From One Health,Misc,-99,Developer chemicals,1243,1.0,308.47656 -Imported From One Health,Misc,-99,Sponges,1244,1.0,28.47432 -Imported From One Health,Misc,-99,Sutures,1245,1.0,469.83342 -Imported From One Health,Misc,-99,Wound drainage kit,1246,1.0,18954.8079 -Imported From One Health,Misc,-99,"Doxorubicin, 10 mg vial",1247,1.0,4456.3239 -Imported From One Health,Misc,-99,"Cyclophosphamide, 500 mg",1248,1.0,6777.03096 -Imported From One Health,Misc,-99,"Dexamethasone, 4 mg, 1 ampoule",1249,1.0,109.15632 -Imported From One Health,Misc,-99,"Tamoxifen, 20 mg tablet",1250,1.0,94.91916 -Imported From One Health,Misc,-99,Cannulae,1251,1.0,1157.97948 -Imported From One Health,Misc,-99,Intravenous administration set,1252,1.0,1499.67846 -Imported From One Health,Misc,-99,"Fluoxetine, 20 mg tab",1253,1.0,14.23716 -Imported From One Health,Misc,-99,"Amitriptyline, 50 mg tab",1254,1.0,14.23716 -Imported From One Health,Misc,-99,"Haloperidol, 5 mg tab",1255,1.0,14.23716 -Imported From One Health,Misc,-99,"Chlorpromazine, 100 mg",1256,1.0,14.23716 -Imported From One Health,Misc,-99,"Fluphenazine decanoate, 25 mg/ml",1257,1.0,616.95312 -Imported From One Health,Misc,-99,EEG,1258,1.0,7137.7152 -Imported From One Health,Misc,-99,"Phenytoin, 100 mg",1259,1.0,3.84132 -Imported From One Health,Misc,-99,"Carbamazepine, 200 mg",1260,1.0,18.98526 -Imported From One Health,Misc,-99,"Valproate, 500 mg",1261,1.0,109.15632 -Imported From One Health,Misc,-99,Serum level test,1262,1.0,0.0 -Imported From One Health,Misc,-99,Thyroid function test,1263,1.0,0.0 -Imported From One Health,Misc,-99,"Diazepam, 5 mg",1264,1.0,0.0 -Imported From One Health,Misc,-99,"Methylphenidate, 10 mg",1265,1.0,56.94864 -Imported From One Health,Misc,-99,"Haloperidol, 5 mg",1266,1.0,14.23716 -Imported From One Health,Misc,-99,"Donepezil, 10 mg",1267,1.0,213.56454 -Imported From One Health,Misc,-99,"Acamprosate, 333 mg",1268,1.0,242.03886 -Imported From One Health,Misc,-99,"Naltrexone, 50 mg",1269,1.0,4760.0595 -Imported From One Health,Misc,-99,"Disulfiram, 250 mg",1270,1.0,555.26352 -Imported From One Health,Misc,-99,Diaphragm,1271,1.0,10711.3209 -Imported From One Health,Misc,-99,"Microscope slides, lime-soda-glass, pack of 50",1272,1.0,2140.36494 -Imported From One Health,Misc,-99,"Sputum containers, pack 100",1273,1.0,7854.33558 -Imported From One Health,Misc,-99,"Immersion oil, 500ml",1274,1.0,29272.22214 -Imported From One Health,Misc,-99,"Lens tissue (paper), 50 pages/block, 10 blocks/pack",1275,1.0,26419.98492 -Imported From One Health,Misc,-99,"Liquid soap for hands, 1 liter",1276,1.0,7137.7152 -Imported From One Health,Misc,-99,"Paper towels, single-use, box. 150 towels/pack, 30 packs/ carton",1277,1.0,42123.90798 -Imported From One Health,Misc,-99,"Nitril gloves, powder free, if Auramine O is used for staining",1278,1.0,12851.68584 -Imported From One Health,Misc,-99,"Laboratory request forms, pack of 1000",1279,1.0,19277.52162 -Imported From One Health,Misc,-99,"Laboratory report forms, pack of 1000",1280,1.0,19277.52162 -Imported From One Health,Misc,-99,Laboratory register,1281,1.0,9994.70052 -Imported From One Health,Misc,-99,"Filter paper round, diameter 150, packs of 100",1282,1.0,7137.7152 -Imported From One Health,Misc,-99,"Desinfectant, phenol, bottle of 5 kg",1283,1.0,68543.8929 -Imported From One Health,Misc,-99,"Stable chlorine desinfectant, pack of 100 tablets",1284,1.0,19277.52162 -Imported From One Health,Misc,-99,Protective eye glasses,1285,1.0,3568.8576 -Imported From One Health,Misc,-99,"Methylated ethanol for spirit lamps, bottle of 2.5 L",1286,1.0,2140.36494 -Imported From One Health,Misc,-99,"Basic fuchsine, 100g (bottle)",1287,1.0,44980.8933 -Imported From One Health,Misc,-99,"Methylene blue, 100g (bottle)",1288,1.0,77826.72114 -Imported From One Health,Misc,-99,"Phenol crystals colourless, 5Kg ",1289,1.0,68543.8929 -Imported From One Health,Misc,-99,"Ethanol, 96%, 2.5L (bottle), for stain solutions",1290,1.0,4997.35026 -Imported From One Health,Misc,-99,"Ethanol, 96%, 2.5L (bottle), for decolourization",1291,1.0,4997.35026 -Imported From One Health,Misc,-99,"Hydrochloric acid, 2.5L (bottle)",1292,1.0,19277.52162 -Imported From One Health,Misc,-99,"Concentrated sulphuric acid, 2.5L (bottle)",1293,1.0,58549.19238 -Imported From One Health,Misc,-99,"Auramine O, 50g (bottle)",1294,1.0,23562.9996 -Imported From One Health,Misc,-99,"Potassium permanganate, 250g (bottle)",1295,1.0,68543.8929 -Imported From One Health,Misc,-99,"Tube for liquid cultures, growth detection based on fluorescence signal, per test - 1 tubes per test + 10% repeat + 10% contamination",1296,1.0,3749.19972 -Imported From One Health,Misc,-99,"Growth supplement for liquid cultures, growth detection based on fluorescence signal, per test. BACTEC MGIT 960 Supplement Kit (100 tests, PANTA and OADC combined) + 10% repeat + 10% contamination",1297,1.0,1072.55652 -Imported From One Health,Misc,-99,"Petri-dishes, disposables, sterile; 20 per bag, 15 bags per package",1298,1.0,77826.72114 -Imported From One Health,Misc,-99,"Immunochromatographic tests for the rapid identification of Mycobacterium tuberculosis, per test",1299,1.0,1428.49266 -Imported From One Health,Misc,-99,"Droppers, disposable, 1.5 ml, 20 per bag and 25 bags per package",1300,1.0,58549.19238 -Imported From One Health,Misc,-99,"Culture tubes, diameter 16 mm, pack of 100",1301,1.0,29272.22214 -Imported From One Health,Misc,-99,"PP-tubes for centrifuge, 50 ml; 500 pieces/pack",1302,1.0,117093.6438 -Imported From One Health,Misc,-99,"PP-tubes for centrifuge, 15 ml; 500 pieces/pack",1303,1.0,117093.6438 -Imported From One Health,Misc,-99,"Loop, disposable 10 m, 500 pieces/pack",1304,1.0,17849.0361 -Imported From One Health,Misc,-99,"Plastic Pasteur pipettes, 1.5 ml, 500 pieces/pack",1305,1.0,39271.67076 -Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 2 ml",1306,1.0,142085.13606 -Imported From One Health,Misc,-99,"Deep freeze storage box with lid for 2 ml cryovials , autoclavable PP",1307,1.0,7854.33558 -Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size S, 100/pack",1308,1.0,11423.19318 -Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size M, 100/pack",1309,1.0,11423.19318 -Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size L, 100/pack",1310,1.0,11423.19318 -Imported From One Health,Misc,-99,"Plastic bags for waste bins, 1000 pieces per pack",1311,1.0,21417.8937 -Imported From One Health,Misc,-99,Stands for small plastic bags (2 litres),1312,1.0,7854.33558 -Imported From One Health,Misc,-99,"Autoclavable bags at 134°C, 410 x 620 mm, 100 pieces per pack",1313,1.0,39271.67076 -Imported From One Health,Misc,-99,"Filter paper round, diameter 185, packs of 100",1314,1.0,7854.33558 -Imported From One Health,Misc,-99,"Marker pen, water resistant",1315,1.0,4878.70488 -Imported From One Health,Misc,-99,"Adhesive labels, pack of 4800 labels",1316,1.0,44980.8933 -Imported From One Health,Misc,-99,"Cryo-tags sized to fit for use on cryo-tubes, rolls of 1000",1317,1.0,40970.6766 -Imported From One Health,Misc,-99,"Sterilindicator tape (rolls), 55 m long, for hot air sterilizer (green/brown)",1318,1.0,21417.8937 -Imported From One Health,Misc,-99,"Sterilindicator tape (rolls), 55 m long, for autoclave (beige/dark brown)",1319,1.0,12851.68584 -Imported From One Health,Misc,-99,"Parafilm, 100 mm width with dispenser",1320,1.0,22134.50694 -Imported From One Health,Misc,-99,"Plastic-foil rolls, 30 cm",1321,1.0,7854.33558 -Imported From One Health,Misc,-99,Tube brush 280 mm long,1322,1.0,2140.36494 -Imported From One Health,Misc,-99,"Laboratory coat, size L",1323,1.0,34274.3205 -Imported From One Health,Misc,-99,"Laboratory coat, size M",1324,1.0,34274.3205 -Imported From One Health,Misc,-99,"Laboratory coat, size S",1325,1.0,34274.3205 -Imported From One Health,Misc,-99,"FFP2 or FFP3 respirators, individually packed, packs of 10",1326,1.0,21417.8937 -Imported From One Health,Misc,-99,"Disinfectant for floors, container 10 litres ",1327,1.0,51406.73622 -Imported From One Health,Misc,-99,"Disinfectant, ethanol-based, container 5 litres",1328,1.0,45697.51368 -Imported From One Health,Misc,-99,Spray hand for bottle with disinfectant of 1 litre,1329,1.0,4997.35026 -Imported From One Health,Misc,-99,"Disinfectant for hands, alcohol-based, 1 litre bottle",1330,1.0,7854.33558 -Imported From One Health,Misc,-99,"Cotton wool, 1 kg",1331,1.0,2140.36494 -Imported From One Health,Misc,-99,"Tissue pulp, absorbent sheets, approx. 550 x 350 mm",1332,1.0,4997.35026 -Imported From One Health,Misc,-99,"Ready-to-use mix, 500g",1333,1.0,95675.7501 -Imported From One Health,Misc,-99,"Glycerol >99% purity, 1 litre",1334,1.0,27131.8572 -Imported From One Health,Misc,-99,"di-Sodium hydrogen phosphate anhydrous, Na2HPO4, MW: 141.96, 1 kg ",1335,1.0,64258.41492 -Imported From One Health,Misc,-99,"Potassium dihydrogen phosphate, KH2PO4, MW: 136,09, 1 kg ",1336,1.0,24991.49226 -Imported From One Health,Misc,-99,"N-acetyl-L-cysteine (NALC), C5H9NO3S, MW: 163.19,puriss. ? 99%, 250g",1337,1.0,146370.61404 -Imported From One Health,Misc,-99,"tri-Sodium citrate dihydrate, C6H5Na3O7 · 2H2O, MW: 294.10, 1 kg",1338,1.0,39983.54304 -Imported From One Health,Misc,-99,"Sodium hydroxide, NaOH, MW 40.00, purum ? 98%, pellets, 1kg",1339,1.0,11423.19318 -Imported From One Health,Misc,-99,"BACTEC™ MGIT™ 960 SIRE kit, One kit is sufficient for 40 test + 10% repeat",1340,1.0,1300.35822 -Imported From One Health,Misc,-99,"Tube and growth supplement for liquid cultures, growth detection based on fluorescence signal, per test - 5 tubes per test + 10% repeat",1341,1.0,3749.19972 -Imported From One Health,Misc,-99,"Syringe filters, 100 pieces per pack",1342,1.0,292741.22808 -Imported From One Health,Misc,-99,"Silica gel for desiccator, 0.5 kg",1343,1.0,29272.22214 -Imported From One Health,Misc,-99,"DNAse-/RNAse-free TIPS, for pipettes 0.1 - 10 µl, 10 boxes at 960 per pack",1344,1.0,89249.91432 -Imported From One Health,Misc,-99,"Sterile, DNA-/RNAse-free TIPS 100 - 1000 µl",1345,1.0,89249.91432 -Imported From One Health,Misc,-99,Dispenser-tips Universal 10ml sterile ,1346,1.0,89249.91432 -Imported From One Health,Misc,-99,"Isoniazid, 5 g",1347,1.0,16420.54344 -Imported From One Health,Misc,-99,"Rifampicin, 1 g",1348,1.0,58549.19238 -Imported From One Health,Misc,-99,"Ethambutol, 25 g",1349,1.0,68543.8929 -Imported From One Health,Misc,-99,"Dihydro-streptomycin, 5 g",1350,1.0,17849.0361 -Imported From One Health,Misc,-99,"Ofloxacin/Ciprofloxacin, 2 g",1351,1.0,21417.8937 -Imported From One Health,Misc,-99,"Protionamid, 2 g",1352,1.0,17849.0361 -Imported From One Health,Misc,-99,"Kanamycin, 2 g",1353,1.0,29988.84252 -Imported From One Health,Misc,-99,"capreomycin, 2 g",1354,1.0,112812.91392 -Imported From One Health,Misc,-99,"Dimethyl sulfoxide, 99,8%, p. a., 500 ml",1355,1.0,19277.52162 -Imported From One Health,Misc,-99,"Xpert Cartridge, one cartridge",1356,1.0,7125.70572 -Imported From One Health,Misc,-99,"Standard reaction tubes with O-ring, 1.5 ml, 1000 per pack",1357,1.0,126822.57924 -Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 2 ml, with outer winding; pack of 1000",1358,1.0,175595.38374 -Imported From One Health,Misc,-99,"PCR tubes, 0.2 ml with attached caps, sterile, DNAse- RNAse-free, 1000 per pack",1359,1.0,82923.73152 -Imported From One Health,Misc,-99,"DNAse-/RNAse-free TIPS, for pipettes 20 - 200 µl, 10 boxes at 960per pack",1360,1.0,89249.91432 -Imported From One Health,Misc,-99,"Pasteur-pipettes, plastic, sterile, 1.5ml, 500 per pack",1361,1.0,39020.14284 -Imported From One Health,Misc,-99,"Combitips for Multipette 10 ml, 100 pieces/pack ",1362,1.0,78040.28568 -Imported From One Health,Misc,-99,"Plastic bags, disposable PP, 100 pieces per pack",1363,1.0,9752.66166 -Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size M, 100 per pack",1364,1.0,11707.94352 -Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size S, 100 per pack",1365,1.0,11707.94352 -Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size L, 100 per pack",1366,1.0,11707.94352 -Imported From One Health,Misc,-99,Forceps plastic,1367,1.0,10730.29902 -Imported From One Health,Misc,-99,"Bottles, plastic",1368,1.0,21460.60518 -Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 6-7, 100 per pack",1369,1.0,13658.47014 -Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 7-8, 100 per pack",1370,1.0,14631.36654 -Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 8-9, 100 per pack",1371,1.0,15609.0039 -Imported From One Health,Misc,-99,"Strips for the rapid detection of resistance to isoniazid and rifampicin, per strip ",1372,1.0,44876.48508 -Imported From One Health,Misc,-99,Kit 4(RHZE 150/75/400/275) / 2(EH 400/75),1373,1.0,22082.3064 -Imported From One Health,Misc,-99,Kit 2(RHZE 150/75/400/275) / 4(RH 150/150)3,1374,1.0,11546.58666 -Imported From One Health,Misc,-99,Kit 2 (RHZE 150/75/400/275) / 4(RH 150/75),1375,1.0,15884.26518 -Imported From One Health,Misc,-99,"RHZE 150/75/400/275 in blister sheets, 1 box",1376,1.0,34449.91452 -Imported From One Health,Misc,-99,"RH 150/150 in blister sheet, 1 box",1377,1.0,16458.50682 -Imported From One Health,Misc,-99,"RH 150/75, in blister sheet, 1 box",1378,1.0,16600.87842 -Imported From One Health,Misc,-99,"RHE 150/75/275 in blister sheet, 1 box",1379,1.0,22405.02012 -Imported From One Health,Misc,-99,"E 400 in blister sheet, 1 box",1380,1.0,18328.35858 -Imported From One Health,Misc,-99,S 1 g (100 vials),1381,1.0,48549.7509 -Imported From One Health,Misc,-99,Kit 2S(RHZE) / 1(RHZE) / 5(RH)E + AD,1382,1.0,70613.07204 -Imported From One Health,Misc,-99,Kit 2S(RHZE) / 1(RHZE) / 5(RHE) + AD,1383,1.0,69545.26362 -Imported From One Health,Misc,-99,Kit 2S(RHZE) / 3(RHZE) / (5(RH 150/150)E)3 + AD,1384,1.0,64509.94998 -Imported From One Health,Misc,-99,2RHZ/4RH ,1385,1.0,17222.58678 -Imported From One Health,Misc,-99,2RHZE/4RH ,1386,1.0,20426.01204 -Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z/ 15 Lfx Eto Cs,1387,1.0,1332493.68924 -Imported From One Health,Misc,-99,6 Km Lfx Pto Cs Z E/ 18 Lfx Pto Cs Z E,1388,1.0,1485498.96264 -Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z (PAS) / 18 Lfx Eto Cs Z (PAS),1389,1.0,1518833.60916 -Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z E/ 18 Lfx Eto Cs Z E,1390,1.0,1645072.45056 -Imported From One Health,Misc,-99,10 Km (Cm)-Lfx-Pto-CS-(+/-E/Z) / 18 Lfx-Pto-CS-(+/-E/Z),1391,1.0,1692824.90622 -Imported From One Health,Misc,-99,10 Km(Cm) Z Lfx Pto Cs (PAS) / 12-18 Z Lfx Pto Cs (PAS),1392,1.0,3916844.82798 -Imported From One Health,Misc,-99,6 Cm-Lfx-Et-Cs-Z / 18 Lfx-Et-Cs,1393,1.0,2188796.43822 -Imported From One Health,Misc,-99,8 Km (Cm) Lfx(Mfx) Eto Cs (PAS) E/ 12-16 Lfx(Mfx) Eto Cs (PAS) E,1394,1.0,3148197.3957 -Imported From One Health,Misc,-99,6 Km (Cm) Lfx Eto Cs (PAS)  E Z / 18Lfx Eto Cs E Z,1395,1.0,2834389.4691 -Imported From One Health,Misc,-99,6 Amk-Z-Lfx-Cs-Eto-PAS/ 18 Z-Lfx-Cs-Eto-PAS,1396,1.0,3339363.81996 -Imported From One Health,Misc,-99,8 Km  (Cm) Z Ofx Eto Cs PAS/ 16 Z Ofx Eto Cs PAS,1397,1.0,3051994.8564 -Imported From One Health,Misc,-99,6 Cm Lfx (Ofx) Eto Cs PASER/ 18 Lfx (Ofx) Eto Cs PASER,1398,1.0,3944351.60658 -Imported From One Health,Misc,-99,9-12 Cm Lfx (Ofx) -Pto - PAS - Cs / 14 Lfx (Ofx) -Pto - PAS - Cs,1399,1.0,3060674.96154 -Imported From One Health,Misc,-99,6 Cm Lfx(Ofx) Cs Eto PASER Z E / 18 Lfx(Ofx) Cs Eto PASER Z E,1400,1.0,3192181.66638 -Imported From One Health,Misc,-99,8 Cm- Pto- Ofx- Cs- Z (PAS) / 12 Cs- Pto- Z- Ofx (PAS),1401,1.0,3471615.6195 -Imported From One Health,Misc,-99,12 Km(Cm) Z Lfx(Ofx) Pto Cs (PAS) / 12 Z Lfx(Ofx) Pto Cs (PAS),1402,1.0,1905964.48056 -Imported From One Health,Misc,-99,6 Cm (Km) Z Lfx Eto Cs (E) / 18  Z Lfx Eto Cs (E) ,1403,1.0,3051994.8564 -Imported From One Health,Misc,-99,8 Cm Cs Eto PAS Mfx /12 Eto PAS Mfx,1404,1.0,3695158.03104 -Imported From One Health,Misc,-99,8km Cs Lfx(HD) Eto Z/12 Cs Lfx(HD) Eto,1405,1.0,1505113.44228 -Imported From One Health,Misc,-99,12 Cm-Mfx-PASER- Cs-Amox/Clv – Z / 12 Mfx- PASER- CS- Amox/Clv,1406,1.0,5427828.84966 -Imported From One Health,Misc,-99,"Isoniazid, 300 mg tab",1407,1.0,14.3514 -Imported From One Health,Misc,-99,Surgical mask,1408,1.0,28.56 -Imported From One Health,Misc,-99,"Surgical cap, disposable",1409,1.0,235.62 -Imported From One Health,Misc,-99,Surgical scrub Betadine,1410,1.0,14.28 -Imported From One Health,Misc,-99,"Gauze pad, inadine",1411,1.0,121.38 -Imported From One Health,Misc,-99,Elastoplast/Dermaplast 25 mm/9mm,1412,1.0,121.38 -Imported From One Health,Misc,-99,Micropore,1413,1.0,121.38 -Imported From One Health,Misc,-99,Bandage,1414,1.0,42.84 -Imported From One Health,Misc,-99,"Lignocaine, 2%, injection 20 ml",1415,1.0,85.68 -Imported From One Health,Misc,-99,2(RH)3Z3E3,1416,1.0,42440.16 -Imported From One Health,Misc,-99,2(RH)ZE,1417,1.0,8736.38262 -Imported From One Health,Misc,-99,2(RHZE),1418,1.0,2011.695 -Imported From One Health,Misc,-99,"2HRZ, 21-30 kg weight band",1419,1.0,8017.02762 -Imported From One Health,Misc,-99,"2HRZ, 5-20 kg weight band",1420,1.0,4924.22238 -Imported From One Health,Misc,-99,"2RHZE, 21-30 kg weight band",1421,1.0,10122.735 -Imported From One Health,Misc,-99,"2RHZE, 5-20 kg weight band",1422,1.0,16639.6272 -Imported From One Health,Misc,-99,2S(RH)ZE/1(RH)ZE,1423,1.0,38694.3375 -Imported From One Health,Misc,-99,2S(RHZE)/1(RHZE),1424,1.0,36489.8625 -Imported From One Health,Misc,-99,2S3(RH)3Z3E3/1(RH)3Z3E3,1425,1.0,19165.15944 -Imported From One Health,Misc,-99,4(RH),1426,1.0,7022.19 -Imported From One Health,Misc,-99,4(RH)3,1427,1.0,3584.78694 -Imported From One Health,Misc,-99,"4RH, 21-30 kg weight band",1428,1.0,12734.19 -Imported From One Health,Misc,-99,"4RH, 5-20 kg weight band",1429,1.0,10081.68 -Imported From One Health,Misc,-99,5(RH)3E3,1430,1.0,9634.5375 -Imported From One Health,Misc,-99,5(RH)3Z3E3,1431,1.0,13663.53954 -Imported From One Health,Misc,-99,5(RH)E,1432,1.0,14790.21012 -Imported From One Health,Misc,-99,5(RH)ZE,1433,1.0,21840.96012 -Imported From One Health,Misc,-99,5(RHE),1434,1.0,14819.9625 -Imported From One Health,Misc,-99,5(RHZE),1435,1.0,18166.8375 -Imported From One Health,Misc,-99,6(EH),1436,1.0,14651.994 -Imported From One Health,Misc,-99,Albuterol,1437,1.0,0.0 -Imported From One Health,Misc,-99,Amikacin 500 mg,1438,1.0,574.77 -Imported From One Health,Misc,-99,"Amikacin (AMI), 5g",1439,1.0,228961.95 -Imported From One Health,Misc,-99,Amitriptyline 25 mg tablets,1440,1.0,5.1408 -Imported From One Health,Misc,-99,Amoxicillin 500 mg Clavulanic acid 125 mg,1441,1.0,106.4574 -Imported From One Health,Misc,-99,"BACTEC MGIT 960 Supplement Kit (100 tests, PANTA and OADC combined)",1442,1.0,505.512 -Imported From One Health,Misc,-99,BACTEC™ MGIT™ PZA Kit,1443,1.0,1293.768 -Imported From One Health,Misc,-99,BACTEC™ MGIT™ PZA Tubes - 25,1444,1.0,1529.388 -Imported From One Health,Misc,-99,BBL MGIT Tubes for use in Bactec MGIT 960 (7ml) - 100 tubes/pkg,1445,1.0,1392.3 -Imported From One Health,Misc,-99,Brain Heart Infusion agar,1446,1.0,119752.08 -Imported From One Health,Misc,-99,"Calamine lotion, 500 ml",1447,1.0,4.4982 -Imported From One Health,Misc,-99,Capreomycin 1000 mg,1448,1.0,3355.8 -Imported From One Health,Misc,-99,"Centrifuge tubes if specimens are further culture processed, pack 1000",1449,1.0,105.8148 -Imported From One Health,Misc,-99,Cilastatin 500 mg,1450,1.0,3648.54 -Imported From One Health,Misc,-99,Cimetidine,1451,1.0,0.0 -Imported From One Health,Misc,-99,Ciotrimazole,1452,1.0,0.0 -Imported From One Health,Misc,-99,Cladryl lotion,1453,1.0,0.0 -Imported From One Health,Misc,-99,Clarithromycin 500 mg,1454,1.0,102.00204 -Imported From One Health,Misc,-99,Clavunate 125 mg,1455,1.0,250.3998 -Imported From One Health,Misc,-99,Clofazimine 100 mg,1456,1.0,904.7808 -Imported From One Health,Misc,-99,Codeine 30 mg,1457,1.0,50.8368 -Imported From One Health,Misc,-99,Cryo-tags,1458,1.0,18.78534 -Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 1.5 ml",1459,1.0,179.89944 -Imported From One Health,Misc,-99,Culture tubes with screw cap,1460,1.0,185.4972 -Imported From One Health,Misc,-99,"Cutaneous reactions, itching",1461,1.0,125.9496 -Imported From One Health,Misc,-99,Cycloserin 250 mg,1462,1.0,235.62 -Imported From One Health,Misc,-99,"Dexamethasone 0.5 mg, tablet",1463,1.0,5.712 -Imported From One Health,Misc,-99,Dexamethasone 5 ml inj,1464,1.0,58.905 -Imported From One Health,Misc,-99,Diazepam 5mg/ml,1465,1.0,47.5524 -Imported From One Health,Misc,-99,Dihydro-streptomycin - for laboratory use (5g),1466,1.0,46845.54 -Imported From One Health,Misc,-99,"Dimenhydrinate 50 , tablet",1467,1.0,2427.6 -Imported From One Health,Misc,-99,"Dimenhydrinate 50 mg/ml, vial",1468,1.0,152.082 -Imported From One Health,Misc,-99,"Dimethyl sulfoxide, 99,8%",1469,1.0,11038.44 -Imported From One Health,Misc,-99,Disinfectant for BSCs surface,1470,1.0,27210.54 -Imported From One Health,Misc,-99,Disinfectant for cleaning instrument,1471,1.0,76483.68 -Imported From One Health,Misc,-99,Disinfectant for floors,1472,1.0,16314.9 -Imported From One Health,Misc,-99,Disinfectant for hands,1473,1.0,6490.26 -Imported From One Health,Misc,-99,di-Sodium hydrogen phosphate dodecahydrate,1474,1.0,29274.0 -Imported From One Health,Misc,-99,Dispenser for disinfectant/soap,1475,1.0,39334.26 -Imported From One Health,Misc,-99,"Disposable pasteur pipettes, graduated, non sterile, 155 mm, 3 ml",1476,1.0,13.33752 -Imported From One Health,Misc,-99,E100,1477,1.0,10627.7472 -Imported From One Health,Misc,-99,E400,1478,1.0,2404.98762 -Imported From One Health,Misc,-99,EH 400/150,1479,1.0,14651.994 -Imported From One Health,Misc,-99,Electrolyte wasting,1480,1.0,10363.8528 -Imported From One Health,Misc,-99,Ethambutol,1481,1.0,21.46998 -Imported From One Health,Misc,-99,Ethambutol - for laboratory use (25g),1482,1.0,4513.3368 -Imported From One Health,Misc,-99,"Ethionamid (ETH), 5g",1483,1.0,112594.23 -Imported From One Health,Misc,-99,Ethionamide 250 mg,1484,1.0,57.0486 -Imported From One Health,Misc,-99,Famotidine,1485,1.0,0.0 -Imported From One Health,Misc,-99,Filter paper - sheets,1486,1.0,845.376 -Imported From One Health,Misc,-99,Fluconazole 50 mg,1487,1.0,6837.264 -Imported From One Health,Misc,-99,"Forceps, individually wrap, sterile",1488,1.0,107.9568 -Imported From One Health,Misc,-99,Furosemide (RX) 20 mg,1489,1.0,1004.598 -Imported From One Health,Misc,-99,Gabapentin,1490,1.0,0.0 -Imported From One Health,Misc,-99,GenoType MTBDR plus V2 - 30496AM - Test kit only composed of: 30496A GenoType MTBDRplus Version 2.0 and 51610 GenoLyse,1491,1.0,7497.0 -Imported From One Health,Misc,-99,"Glass beads, massive glass, 3 mm diameter",1492,1.0,4419.66 -Imported From One Health,Misc,-99,"Glass beads, massive glass, 5 mm diameter",1493,1.0,4783.8 -Imported From One Health,Misc,-99,GT-Blot 48 reagent kits,1494,1.0,0.0 -Imported From One Health,Misc,-99,GT-Blot 48 Tray for 96 strips (black),1495,1.0,2070.6 -Imported From One Health,Misc,-99,H300,1496,1.0,6822.86976 -Imported From One Health,Misc,-99,Hair Cover,1497,1.0,7.9254 -Imported From One Health,Misc,-99,Haloperidol 2mg - tablets ,1498,1.0,3454.6176 -Imported From One Health,Misc,-99,"Haloperidol 5mg/ml, 2ml - injections",1499,1.0,206.8458 -Imported From One Health,Misc,-99,High-dose isoniazid,1500,1.0,40.61232 -Imported From One Health,Misc,-99,Hydrocortisone cream,1501,1.0,28.4886 -Imported From One Health,Misc,-99,Hyoscine Butylbromide 10 mg,1502,1.0,11407.4352 -Imported From One Health,Misc,-99,Ibuprofen 200 mg,1503,1.0,4.9266 -Imported From One Health,Misc,-99,Imipenem/Cilastin 500 mg,1504,1.0,7282.8 -Imported From One Health,Misc,-99,Ion exchanger cartridge,1505,1.0,440309.52 -Imported From One Health,Misc,-99,Ion exchanger resin for laboratory grade water,1506,1.0,12680.64 -Imported From One Health,Misc,-99,IPT for children under 20kg,1507,1.0,1786.428 -Imported From One Health,Misc,-99,Isoniazid 100 mg,1508,1.0,21.42 -Imported From One Health,Misc,-99,Isoniazid - for laboratory use (5g),1509,1.0,3791.34 -Imported From One Health,Misc,-99,Isoniazid 150 mg,1510,1.0,28.56 -Imported From One Health,Misc,-99,Isoniazid Preventive Therapy,1511,1.0,3251.556 -Imported From One Health,Misc,-99,Isopropanol,1512,1.0,2143.428 -Imported From One Health,Misc,-99,Kanamycin 1000 mg,1513,1.0,1228.9368 -Imported From One Health,Misc,-99,"Kanamycin (KAN), 1g",1514,1.0,9599.016 -Imported From One Health,Misc,-99,Lansoprazole,1515,1.0,0.0 -Imported From One Health,Misc,-99,L-Asparagine-momohydrate,1516,1.0,178500.0 -Imported From One Health,Misc,-99,"Latex gloves size L, 1000 per pack",1517,1.0,35.92848 -Imported From One Health,Misc,-99,"Latex gloves size M, 1000 per pack",1518,1.0,35.92848 -Imported From One Health,Misc,-99,"Latex gloves size S, 1000 per pack",1519,1.0,35.92848 -Imported From One Health,Misc,-99,Levofloxacin 250 mg,1520,1.0,39.27 -Imported From One Health,Misc,-99,Levothyroxine 50 mcg,1521,1.0,9.8532 -Imported From One Health,Misc,-99,Linezolid 600 mg,1522,1.0,3912.72 -Imported From One Health,Misc,-99,Long 1 ml tips with filter,1523,1.0,86.60106 -Imported From One Health,Misc,-99,Loperamide 2 mg,1524,1.0,7.14 -Imported From One Health,Misc,-99,"Lorazepam, 1 mg",1525,1.0,0.0 -Imported From One Health,Misc,-99,Magnesium sulfate-heptahydrate,1526,1.0,51408.0 -Imported From One Health,Misc,-99,Magnetic bars set of 12,1527,1.0,28060.2 -Imported From One Health,Misc,-99,Malachite green oxalate,1528,1.0,485520.0 -Imported From One Health,Misc,-99,Masks FFP2 (N95) - 3M 9320,1529,1.0,1432.284 -Imported From One Health,Misc,-99,Meclizine,1530,1.0,0.0 -Imported From One Health,Misc,-99,Metoclopramide HCL,1531,1.0,2087.1648 -Imported From One Health,Misc,-99,"Microscope slides with frosted end, pack of 50",1532,1.0,63.546 -Imported From One Health,Misc,-99,Molecular grade water,1533,1.0,8208.47958 -Imported From One Health,Misc,-99,Moxifloxacin 400 mg,1534,1.0,328.44 -Imported From One Health,Misc,-99,"Moxifloxacin (MOX), 2g",1535,1.0,7140.0 -Imported From One Health,Misc,-99,Mystatin,1536,1.0,0.0 -Imported From One Health,Misc,-99,odansetron 8 mg,1537,1.0,341791.2288 -Imported From One Health,Misc,-99,Ofloxacin 200 mg,1538,1.0,41.412 -Imported From One Health,Misc,-99,"Ofloxacin/Ciprofloxacin, 10 g",1539,1.0,225188.46 -Imported From One Health,Misc,-99,Oil 8cc for CX 21 / CX 22,1540,1.0,3277.26 -Imported From One Health,Misc,-99,Omeprazole 20 mg,1541,1.0,12.852 -Imported From One Health,Misc,-99,Other serotonin 5-THE receptor antagonist,1542,1.0,0.0 -Imported From One Health,Misc,-99,P-aminosalicylic acid 4000 mg,1543,1.0,951.99762 -Imported From One Health,Misc,-99,PCR tubes,1544,1.0,32.95824 -Imported From One Health,Misc,-99,Phenitoin,1545,1.0,0.0 -Imported From One Health,Misc,-99,Phenol,1546,1.0,49.73724 -Imported From One Health,Misc,-99,Plastic bags - 30L,1547,1.0,282.387 -Imported From One Health,Misc,-99,Plastic bags made from PP,1548,1.0,56.3346 -Imported From One Health,Misc,-99,Plastic-foil,1549,1.0,49194.6 -Imported From One Health,Misc,-99,PP-tubes for centrifuge non sterile 50 ml,1550,1.0,105.8148 -Imported From One Health,Misc,-99,"PP-tubes for centrifuge, non sterile, 15 ml",1551,1.0,121.86552 -Imported From One Health,Misc,-99,"PP-tubes for centrifuge, sterile, 50 ml",1552,1.0,105.8148 -Imported From One Health,Misc,-99,"Prednisone, 50 mg",1553,1.0,1673.3304 -Imported From One Health,Misc,-99,Prochlorperazine 5 mg,1554,1.0,14394.24 -Imported From One Health,Misc,-99,Promethazine,1555,1.0,510.00306 -Imported From One Health,Misc,-99,Protionamide 250 mg,1556,1.0,126.735 -Imported From One Health,Misc,-99,Pyrazinamide,1557,1.0,22.3482 -Imported From One Health,Misc,-99,"Rantidine, 150 mg tab",1558,1.0,0.0 -Imported From One Health,Misc,-99,Rapid test for Detection of MPT 64 Antigen,1559,1.0,999.6 -Imported From One Health,Misc,-99,"Ready mixed TB / LJ Base, 500g",1560,1.0,42840.0 -Imported From One Health,Misc,-99,Regimen 1: TDF+3TC+EFV,1561,1.0,43246.98 -Imported From One Health,Misc,-99,Regimen 2: TDF +FTC+EFV,1562,1.0,49570.164 -Imported From One Health,Misc,-99,Regimen 3: AZT + 3TC + EFV,1563,1.0,59646.132 -Imported From One Health,Misc,-99,Regimen 4: AZT+3TC+ NVP,1564,1.0,54672.408 -Imported From One Health,Misc,-99,Regimen 5: TDF+3TC+NVP,1565,1.0,65982.168 -Imported From One Health,Misc,-99,Regimen 6: TDF+FTC+NVP,1566,1.0,53091.612 -Imported From One Health,Misc,-99,RH 150/150,1567,1.0,24.89718 -Imported From One Health,Misc,-99,RH 150/75,1568,1.0,20.89878 -Imported From One Health,Misc,-99,RH 60/30,1569,1.0,13.00194 -Imported From One Health,Misc,-99,"RH 60/60, 5-20 kg weight band",1570,1.0,16.78614 -Imported From One Health,Misc,-99,"RH 60/60, 21-30 kg weight band",1571,1.0,25.49694 -Imported From One Health,Misc,-99,RHE 150/75/275,1572,1.0,35.28588 -Imported From One Health,Misc,-99,RHZ 60/30/150,1573,1.0,18.78534 -Imported From One Health,Misc,-99,RHZE,1574,1.0,43.25412 -Imported From One Health,Misc,-99,RHZE 150/75/400/275,1575,1.0,35.92134 -Imported From One Health,Misc,-99,Rifabutine 150 mg,1576,1.0,607.1142 -Imported From One Health,Misc,-99,Rifampicin,1577,1.0,60.69 -Imported From One Health,Misc,-99,Rifampicin - for laboratory use (1g),1578,1.0,108528.0 -Imported From One Health,Misc,-99,S1,1579,1.0,456.96 -Imported From One Health,Misc,-99,"Sertraline, 50 mg tab",1580,1.0,0.0 -Imported From One Health,Misc,-99,Shoe cover,1581,1.0,16.3149 -Imported From One Health,Misc,-99,Single use plastic Pasteur-pipettes sterile individually packed,1582,1.0,63.74592 -Imported From One Health,Misc,-99,"Single use syringes, sterile",1583,1.0,51.5508 -Imported From One Health,Misc,-99,Single-use paper towels,1584,1.0,10859.94 -Imported From One Health,Misc,-99,Spironolactone 25 mg,1585,1.0,30.8448 -Imported From One Health,Misc,-99,"Sterile, DNA-/RNAse-free TIPS, 10 - 100 µl",1586,1.0,54.10692 -Imported From One Health,Misc,-99,Streptomycin,1587,1.0,456.96 -Imported From One Health,Misc,-99,"Syringe filter for single use, sterile",1588,1.0,1726.0236 -Imported From One Health,Misc,-99,Terizidone 250 mg,1589,1.0,1189.524 -Imported From One Health,Misc,-99,Thioacetazone 150 mg,1590,1.0,0.0 -Imported From One Health,Misc,-99,Thorazine,1591,1.0,0.0 -Imported From One Health,Misc,-99,"TIPS, PP, 100-1000 ?l, sterile, autoclavable with Filter",1592,1.0,43.86102 -Imported From One Health,Misc,-99,Transparent polypropylene bag,1593,1.0,125.63544 -Imported From One Health,Misc,-99,tri-Magnesium di-citrate nonahydrate,1594,1.0,292740.0 -Imported From One Health,Misc,-99,"Valproic acid, 200 mg",1595,1.0,125.307 -Imported From One Health,Misc,-99,"Vitamine B6, 25 mg",1596,1.0,4.2126 -Imported From One Health,Misc,-99,Waste containers for sharps,1597,1.0,1150.254 -Imported From One Health,Misc,-99,Xpert MTB/RIF kit of 50 tests,1598,1.0,7125.72 -Imported From One Health,Misc,-99,Z400,1599,1.0,16.78614 -Imported From One Health,Misc,-99,"Nausea, vomiting, upset stomach",1600,1.0,343878.3936 -Imported From One Health,Misc,-99,"Heartburn, acid indigestion, sour stomach, ulcer",1601,1.0,2159.136 -Imported From One Health,Misc,-99,Oral candidiasis,1602,1.0,6837.264 -Imported From One Health,Misc,-99,Diarrhea,1603,1.0,5517.792 -Imported From One Health,Misc,-99,Depression,1604,1.0,8972.4096 -Imported From One Health,Misc,-99,Severe anxiety,1605,1.0,14490.2016 -Imported From One Health,Misc,-99,Insomnia,1606,1.0,2399.04 -Imported From One Health,Misc,-99,Psychosis,1607,1.0,3454.6176 -Imported From One Health,Misc,-99,Seizures,1608,1.0,11635.344 -Imported From One Health,Misc,-99,Prophylaxis of neurological complications of cycloserine and isoniazid,1609,1.0,22646.9376 -Imported From One Health,Misc,-99,Peripheral neuropathy,1610,1.0,4318.272 -Imported From One Health,Misc,-99,Vestibular symptoms,1611,1.0,14394.24 -Imported From One Health,Misc,-99,"Musculoskeletal pain, arthralgia, headaches",1612,1.0,0.0 -Imported From One Health,Misc,-99,Systemic hypersensitivity reactions,1613,1.0,1673.3304 -Imported From One Health,Misc,-99,Bronchospasm,1614,1.0,4948.02 -Imported From One Health,Misc,-99,Hypothyroidism,1615,1.0,3310.6752 -Imported From One Health,Misc,-99,Abdominal pain,1616,1.0,11407.4352 -Imported From One Health,Misc,-99,Tinnitus,1617,1.0,14394.24 -Imported From One Health,Misc,-99,Renal failure/nephrotoxicity,1618,1.0,1004.598 -Imported From One Health,Misc,-99,"Capreomycin (CM), 1g",1619,1.0,214285.68 -Imported From One Health,Misc,-99,Bedaquiline 100 mg,1620,1.0,11393.6193 -Imported From One Health,Misc,-99,6 Am-Lfx-Eto-Cs-Z/14 Lfx-Eto-Cs-Z,1621,1.0,632604.0 -Imported From One Health,Misc,-99,6 Km-Lfx-Pto-Cs-Z/12 Lfx-Pto-Cs-Z,1622,1.0,766836.0 -Imported From One Health,Misc,-99,6 Km-Lfx-Eto-Cs-Z-(E) / 12 Lfx-Eto-Cs-Z-(E),1623,1.0,774690.0 -Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs/12Z-Lfx-Eto-Cs,1624,1.0,882504.0 -Imported From One Health,Misc,-99,8 Km-Pto-Lfx-Cs-Z/12 Pto-Lfx-Cs-Z,1625,1.0,931056.0 -Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs / 16 Z-Lfx-Eto-Cs,1626,1.0,971040.0 -Imported From One Health,Misc,-99,8 Km-Lfx-Pto-Cs-Z-E/14 Lfx-Pto-Cs-Z-E,1627,1.0,1030302.0 -Imported From One Health,Misc,-99,6 Km-Lfx-Eto-Cs-Z-E/18 Lfx-Eto-Cs-E,1628,1.0,1042440.0 -Imported From One Health,Misc,-99,9 Z-Km-Lfx-Eto-Cs/15 Lfx-Eto-Cs-Z,1629,1.0,1140972.0 -Imported From One Health,Misc,-99,8 Z-Cm-Lfx-Pto-Cs / 12 Z-Lfx-Pto-Cs,1630,1.0,1189524.0 -Imported From One Health,Misc,-99,8 Cm-Pto-Lfx-Cs-Z/12 Pto-Lfx-Cs-Z,1631,1.0,1189524.0 -Imported From One Health,Misc,-99,8 Cm-Eto-Lfx-Cs-Z-E/16 Eto-Lfx-Cs-Z-E,1632,1.0,1276632.0 -Imported From One Health,Misc,-99,9 Km-Lfx-Eto-Cs-Z-E/18 Lfx-Eto-Cs-E,1633,1.0,1292340.0 -Imported From One Health,Misc,-99,8 Z-E-Cm-Lfx-Pto-Cs/14 E-Z-Lfx-Pto-Cs,1634,1.0,1295196.0 -Imported From One Health,Misc,-99,6 Am-Lfx-Eto-Cs-PAS-Z/14 Lfx-Eto-Cs-PAS-Z,1635,1.0,1929942.0 -Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs-PAS/12 Z-Lfx-Eto-PAS-Cs,1636,1.0,2179842.0 -Imported From One Health,Misc,-99,8 Am-Lfx-Eto-Cs-Z-PAS/16 Lfx-Eto-Cs-Z-PAS,1637,1.0,2341206.0 -Imported From One Health,Misc,-99,8 Cm-Lfx-Eto-PAS-Cs-Z/12 Lfx-Eto-PAS-Cs-Z,1638,1.0,2444022.0 -Imported From One Health,Misc,-99,12 Z-Ami-Lfx-Eto-Cs-PAS / 12 Z-Lfx-Eto-Cs-PAS,1639,1.0,2467584.0 -Imported From One Health,Misc,-99,12 Z-Am-Pto-Cs-PAS-Lfx/12 Z-Pto-Cs-PAS-Lfx,1640,1.0,2518992.0 -Imported From One Health,Misc,-99,8 Cm-Mfx-Eto-PAS-Cs-Z-AmxClv/12 Mfx-Eto-PAS-Cs-Z-AmxClv,1641,1.0,2726052.0 -Imported From One Health,Misc,-99,12 Z-Km-Lfx-Pto-Cs-PAS / 12 Z-Lfx-Pto-Cs-PAS,1642,1.0,2798880.0 -Imported From One Health,Misc,-99,8 ?m-Lfx-?s-Pto-Z-PAS / 16 Lfx-?s-Pto-Z-PAS,1643,1.0,2843862.0 -Imported From One Health,Misc,-99,11Cm-Lfx-Pto-Cs-Z-PAS/13Lfx-Pto-Cs-Z-PAS,1644,1.0,3107328.0 -Imported From One Health,Misc,-99,12 Z-Cm-Lfx-Pto-Cs-PAS / 12 Z-Lfx-Pto-Cs-PAS,1645,1.0,3195150.0 -Imported From One Health,Misc,-99,12 Z-Cm-Pto-Cs-PAS-Lfx/12 Z-Pto-Cs-PAS-Lfx,1646,1.0,3195150.0 -Imported From One Health,Misc,-99,"Protionamid (PTH), 2g",1647,1.0,91584.78 -Imported From One Health,Misc,-99,"Vitamine B6, 15 mg",1648,1.0,4.2126 -Imported From One Health,Misc,-99,TB Patient support - Incentive or enabler,1649,1.0,0.0 -Imported From One Health,Misc,-99,TB Patient support - Food voucher,1650,1.0,0.0 -Imported From One Health,Misc,-99,TB Patient support - Transport voucher,1651,1.0,0.0 -Imported From One Health,Misc,-99,TB Patient support - Mobile phone air-time,1652,1.0,0.0 -Imported From One Health,Misc,-99,Palliative care for TB patients,1653,1.0,0.0 -Imported From One Health,Misc,-99,Total bilirubin,1654,1.0,258.468 -Imported From One Health,Misc,-99,"Electrosurgical unit (monopolar pen, pad)",1655,1.0,2413.32 -Imported From One Health,Misc,-99,"Skin preparatory solution, 500 ml vial",1656,1.0,7.14 -Imported From One Health,Misc,-99,"Cefazolin, 1g",1657,1.0,307.02 -Imported From One Health,Misc,-99,Paclitaxel,1658,1.0,7332.78 -Imported From One Health,Misc,-99,"Formalin, 1 liter",1659,1.0,521.22 -Imported From One Health,Misc,-99,H and E staining,1660,1.0,357.0 -Imported From One Health,Misc,-99,Hormone receptor testing (immunoanalyzer),1661,1.0,17778.6 -Imported From One Health,Misc,-99,Electrolytes test,1662,1.0,3191.58 -Imported From One Health,Misc,-99,BUN test,1663,1.0,1861.398 -Imported From One Health,Misc,-99,Serum creatinine,1664,1.0,1535.1 -Imported From One Health,Misc,-99,Ultrasound gel,1665,1.0,147.798 -Imported From One Health,Misc,-99,Ultrasound probe cover,1666,1.0,5090.82 -Imported From One Health,Misc,-99,Filgastrim,1667,1.0,94.01238 -Imported From One Health,Misc,-99,Ondansetron (4mg tablets),1668,1.0,379.2054 -Imported From One Health,Misc,-99,"Alendronate, 10 mg tab",1669,1.0,43.2684 -Imported From One Health,Misc,-99,"Ibuprofen, 400 mg tab",1670,1.0,7.854 -Imported From One Health,Misc,-99,Morphine injection (5mL),1671,1.0,2170.56 -Imported From One Health,Misc,-99,Morphine oral liquid (10mg/mL),1672,1.0,107.1 -Imported From One Health,Misc,-99,Morphine slow release tablet (10mg),1673,1.0,578.34 -Imported From One Health,Misc,-99,Dexamethasone (4mg tablets),1674,1.0,42.84 -Imported From One Health,Misc,-99,Docusate (100mg tablet),1675,1.0,114.24 -Imported From One Health,Misc,-99,"Senna, 7.5 mg tab",1676,1.0,7.9968 -Imported From One Health,Misc,-99,Metoclopramide (10mg tablet),1677,1.0,4.4982 -Imported From One Health,Misc,-99,Amitriptyline(25 mg tab),1678,1.0,5.1408 -Imported From One Health,Misc,-99,"Haloperidol (oral liquid, 2mg) ",1679,1.0,22.2054 -Imported From One Health,Misc,-99,HER2 amplification (immunoanalyzer),1680,1.0,53978.4 -Imported From One Health,Misc,-99,"Trastuzamab, 1 mg",1681,1.0,3048.78 -Imported From One Health,Misc,-99,Mammography film,1682,1.0,456.96 -Imported From One Health,Misc,-99,Mammography film chemistry,1683,1.0,45.696 -Imported From One Health,Misc,-99,Wire localization needle,1684,1.0,54935.16 -Imported From One Health,Misc,-99,Soft tissue marker/fiduciary clip,1685,1.0,0.0 -Imported From One Health,Misc,-99,"Pipette, repeater",1686,1.0,28.56 -Imported From One Health,Misc,-99,Pipette tips,1687,1.0,28.56 -Imported From One Health,Misc,-99,Repeater tips,1688,1.0,28.56 -Imported From One Health,Misc,-99,CareHPV Test Kit,1689,1.0,6725.88 -Imported From One Health,Misc,-99,IEC materials,1690,1.0,714.0 -Imported From One Health,Misc,-99,Data collection forms,1691,1.0,142.8 -Imported From One Health,Misc,-99,"Azithromycin, 500 mg",1692,1.0,228.48 -Imported From One Health,Misc,-99,"Cefrriaxone, powder for infection, 250 ml vial",1693,1.0,171.36 -Imported From One Health,Misc,-99,"Acetic acid, 5% dilute, 5 ml",1694,1.0,228.48 -Imported From One Health,Misc,-99,KY jelly packet,1695,1.0,134.232 -Imported From One Health,Misc,-99,"70 isopropyl alcohol, 10 ml",1696,1.0,592.62 -Imported From One Health,Misc,-99,"Soap or hand sanitizer, 1L",1697,1.0,7854.0 -Imported From One Health,Misc,-99,Cervical cytology brush/scraper,1698,1.0,541.0692 -Imported From One Health,Misc,-99,"Monsel's solution, 1 ml",1699,1.0,92.82 -Imported From One Health,Misc,-99,"Lugol's solution, 1 ml",1700,1.0,594.048 -Imported From One Health,Misc,-99,"Compressed gas, 25 kg cylinder",1701,1.0,49980.0 -Imported From One Health,Misc,-99,"Cryotherapy unit with cryotips, use for one patient",1702,1.0,42.84 -Imported From One Health,Misc,-99,Gas cylinder adapter,1703,1.0,7140.0 -Imported From One Health,Misc,-99,"Syringe, 5 cc with needle",1704,1.0,397.6266 -Imported From One Health,Misc,-99,Cauterizer,1705,1.0,5069.4 -Imported From One Health,Misc,-99,IV contrast,1706,1.0,178.5 -Imported From One Health,Misc,-99,Vaginal estrogen,1707,1.0,14280.0 -Imported From One Health,Misc,-99,"Gauze pad, 10X4 cm",1708,1.0,107.1 -Imported From One Health,Misc,-99,"Cidex 2-4% glutaraldehyde (cl), 100ml",1709,1.0,199.92 -Imported From One Health,Misc,-99,"Needle, spinal, 22g (disposable)",1710,1.0,642.6 -Imported From One Health,Misc,-99,Electrosurgical pen,1711,1.0,2413.32 -Imported From One Health,Misc,-99,Perthodine (cl),1712,1.0,21.42 -Imported From One Health,Misc,-99,Definitive radiotherapy (50Gy in 25 fractions),1713,1.0,53907.0 -Imported From One Health,Misc,-99,Cisplatin (50 mg tab),1714,1.0,4783.8 -Imported From One Health,Misc,-99,"Forceps, punch biopsy",1715,1.0,28167.3 -Imported From One Health,Misc,-99,"Forceps, sponge holder",1716,1.0,9032.1 -Imported From One Health,Misc,-99,FIT test set,1717,1.0,1949.22 -Imported From One Health,Misc,-99,FOBT test set,1718,1.0,4069.8 -Imported From One Health,Misc,-99,Phosphate enema,1719,1.0,1128.12 -Imported From One Health,Misc,-99,"Midazolam, 1 mg",1720,1.0,208.6308 -Imported From One Health,Misc,-99,"GoLytely (PEG 3350 + electrolytes), 4 L",1721,1.0,99.96 -Imported From One Health,Misc,-99,Diagnosis of colorectal cancer ,1722,1.0,18421.2 -Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 1,1723,1.0,72828.0 -Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 2,1724,1.0,351288.0 -Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 3,1725,1.0,1118838.0 -Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 4,1726,1.0,334866.0 -Imported From One Health,Misc,-99,Rectal cancer treatment: Stage 1,1727,1.0,73756.2 -Imported From One Health,Misc,-99,Rectal cancer treatment: stage 2,1728,1.0,808947.72 -Imported From One Health,Misc,-99,Rectal cancer treatment: stage 3,1729,1.0,1925715.12 -Imported From One Health,Misc,-99,Rectal cancer treatment: stage 4,1730,1.0,263894.4 -Imported From One Health,Misc,-99,CEA test,1731,1.0,8518.02 -Imported From One Health,Misc,-99,Distance chart per 200 patients,1732,1.0,1606.5 -Imported From One Health,Misc,-99,Vision chart per 200 patients,1733,1.0,499.8 -Imported From One Health,Misc,-99,Illuminated chart per 200 patients,1734,1.0,17850.0 -Imported From One Health,Misc,-99,"Praziquantel, 600 mg (donated)",1735,1.0,0.0 -Imported From One Health,Misc,-99,"Mebendazole, 500 mg tab",1736,1.0,74.97 -Imported From One Health,Misc,-99,"Albendazole, tablet, 400 mg (donated)",1737,1.0,0.0 -Imported From One Health,Misc,-99,"Mebendazole, 500 mg tab (donated)",1738,1.0,0.0 -Imported From One Health,Misc,-99,"Ivermectin, 3 mg",1739,1.0,36.414 -Imported From One Health,Misc,-99,"Ivermectin, 3 mg (donated)",1740,1.0,0.0 -Imported From One Health,Misc,-99,"Diethylcarbamazine citrate, 100 mg tab",1741,1.0,3.927 -Imported From One Health,Misc,-99,"Diethylcarbamazine citrate, 100 mg tab (donated)",1742,1.0,0.0 -Imported From One Health,Misc,-99,"Azithromycin, 250 mg tab",1743,1.0,83.538 -Imported From One Health,Misc,-99,"Rifampicin, 300 mg tab",1744,1.0,85.1088 -Imported From One Health,Misc,-99,"Clarithromycin, 1 ml",1745,1.0,23.205 -Imported From One Health,Misc,-99,"Sodium Stibogluconate (100 mg/ml), 30 ml vial",1746,1.0,7389.9 -Imported From One Health,Misc,-99,"Meglumine antimonate (81 mg/ml), 5 ml ampoule",1747,1.0,0.0 -Imported From One Health,Misc,-99,"Pentamidine, 200 mg",1748,1.0,8246.7 -Imported From One Health,Misc,-99,rK39 rapid diagnostic test,1749,1.0,1213.8 -Imported From One Health,Misc,-99,"liposomal amphotericin B (Ambisome), 50 mg vial",1750,1.0,11602.5 -Imported From One Health,Misc,-99,"Miltefosine (Impavido), capsule, 50 mg",1751,1.0,0.0 -Imported From One Health,Misc,-99,Paromomycin (750 mg/2 ml),1752,1.0,0.0 -Imported From One Health,Misc,-99,"Kit NECT (Nifurtimox, 120 mg + Eflornithine (200 mg/ml), 100 ml ampoule)",1753,1.0,32744.04 -Imported From One Health,Misc,-99,Card Agglutination Trypanosomiasis Test (CATT),1754,1.0,371.28 -Imported From One Health,Misc,-99,MAECT,1755,1.0,2363.34 -Imported From One Health,Misc,-99,"Suramine, powder for injection, 1 g",1756,1.0,4319.7 -Imported From One Health,Misc,-99,"Melarsoprol (36 mg/ml), 5 ml vial",1757,1.0,5997.6 -Imported From One Health,Misc,-99,Lumbar puncture,1758,1.0,6704.46 -Imported From One Health,Misc,-99,"Dapsone, 100 mg tab",1759,1.0,178.5 -Imported From One Health,Misc,-99,"Benznidazole, 100 mg",1760,1.0,428.4 -Imported From One Health,Misc,-99,"Lidocaine HCL 2%, 20 ml ampule",1761,1.0,314.16 -Imported From One Health,Misc,-99,"Needle (disposable), 21g",1762,1.0,142.8 -Imported From One Health,Misc,-99,Yaws point of care test,1763,1.0,1428.0 -Imported From One Health,Misc,-99,"Actellic, 1 g",1764,1.0,7.14 -Imported From One Health,Misc,-99,"Deltamethrine, 100 ml",1765,1.0,2142.0 -Imported From One Health,Misc,-99,Beta-cypermethrine,1766,1.0,0.0 -Imported From One Health,Misc,-99,"Rabies vaccine, 1 ml (canine)",1767,1.0,178.5 -Imported From One Health,Misc,-99,"Rabies post exposure prophylaxis, 1 vial, .5 ml",1768,1.0,11159.82 -Imported From One Health,Misc,-99,"Rifampicin, 600 mg tab",1769,1.0,60.69 -Imported From One Health,Misc,-99,Thioridazine 50mg_1000_CMST,1770,1.0,64438.75704 -Imported From One Health,Misc,-99,Thioridazine 25mg_1000_CMST,1771,1.0,50500.28466 -Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (12+12s)_100_CMST,1772,1.0,39527.94678 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x24_720_CMST",1773,1.0,32988.20658 -Imported From One Health,Misc,-99,Lorazepam 1mg_100_CMST,1774,1.0,23890.46142 -Imported From One Health,Misc,-99,"Vitamin A 200,000 IU_1000_CMST",1775,1.0,23002.99512 -Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (6+6s)_100_CMST,1776,1.0,21417.8937 -Imported From One Health,Misc,-99,"Vitamin A 100,000 IU_1000_CMST",1777,1.0,17621.2344 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x12_360_CMST",1778,1.0,17436.14418 -Imported From One Health,Misc,-99,Mebendazole 500mg_1000_CMST,1779,1.0,15485.61756 -Imported From One Health,Misc,-99,Doxycycline 100mg_1000_CMST,1780,1.0,12960.83502 -Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (3+3s)_100_CMST,1781,1.0,12396.08244 -Imported From One Health,Misc,-99,Azithromycin 250mg_100_CMST,1782,1.0,12210.99936 -Imported From One Health,Misc,-99,Morphine sulphate 10mg (slow release)_60_CMST,1783,1.0,11233.362 -Imported From One Health,Misc,-99,Norethisterone 5mg_100_CMST,1784,1.0,10194.02076 -Imported From One Health,Misc,-99,Penicillin V 250mg_1000_CMST,1785,1.0,9415.71078 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x6_180_CMST",1786,1.0,8718.07566 -Imported From One Health,Misc,-99,Nicotinamide 50mg_1000_CMST,1787,1.0,7626.53388 -Imported From One Health,Misc,-99,Imipramine Hcl 10mg_1000_CMST,1788,1.0,5082.77322 -Imported From One Health,Misc,-99,Hydrocortisone acetate 20mg_100_CMST,1789,1.0,5054.2989 -Imported From One Health,Misc,-99,Atenolol 50mg_1000_CMST,1790,1.0,4143.09924 -Imported From One Health,Misc,-99,Dexamethasone 0.5mg_1000_CMST,1791,1.0,3991.23858 -Imported From One Health,Misc,-99,Acyclovir 400mg_100_CMST,1792,1.0,3796.6593 -Imported From One Health,Misc,-99,Nitrofurantoin 50mg_250_CMST,1793,1.0,3611.56908 -Imported From One Health,Misc,-99,Fluconazole 200mg_100_CMST,1794,1.0,3597.33192 -Imported From One Health,Misc,-99,Cephalexin 250mg_100_CMST,1795,1.0,3549.87234 -Imported From One Health,Misc,-99,Bisacodyl 5mg_1000_CMST,1796,1.0,3241.39578 -Imported From One Health,Misc,-99,Ibuprofen 200mg_1000_CMST,1797,1.0,3184.44714 -Imported From One Health,Misc,-99,Spironolactone 25mg_100_CMST,1798,1.0,2747.829 -Imported From One Health,Misc,-99,Pyridoxine (Vitamin B6) 20mg_1000_CMST,1799,1.0,2700.36942 -Imported From One Health,Misc,-99,Phenobarbitone 30mg_1000_CMST,1800,1.0,2671.8951 -Imported From One Health,Misc,-99,Acyclovir 200mg_100_CMST,1801,1.0,2501.04918 -Imported From One Health,Misc,-99,Aminophylline 100mg_1000_CMST,1802,1.0,2353.92948 -Imported From One Health,Misc,-99,Propranolol hydrochloride 40mg_1000_CMST,1803,1.0,2339.69232 -Imported From One Health,Misc,-99,Allopurinol 100mg_100_CMST,1804,1.0,2197.31358 -Imported From One Health,Misc,-99,Chlorpromazine 25mg_100_CMST,1805,1.0,2140.36494 -Imported From One Health,Misc,-99,Metformin hydrochloride 850mg_100_CMST,1806,1.0,2140.36494 -Imported From One Health,Misc,-99,Phenytoin sodium 25mg_1000_CMST,1807,1.0,2140.36494 -Imported From One Health,Misc,-99,Ferrous sulphate 200mg / folic acid 250 micrograms_1000_CMST,1808,1.0,2007.4824 -Imported From One Health,Misc,-99,Acetazolamide 250mg_100_CMST,1809,1.0,1969.51188 -Imported From One Health,Misc,-99,Loperamide HCl 2mg_1000_CMST,1810,1.0,1950.53376 -Imported From One Health,Misc,-99,Zinc sulphate 20mg _100_CMST,1811,1.0,1941.0447 -Imported From One Health,Misc,-99,Ketoconazole 200mg_100_CMST,1812,1.0,1912.56324 -Imported From One Health,Misc,-99,Indomethacin 25mg_1000_CMST,1813,1.0,1570.86426 -Imported From One Health,Misc,-99,Captopril 12.5mg_100_CMST,1814,1.0,1314.59538 -Imported From One Health,Misc,-99,Haloperidol 2mg_100_CMST,1815,1.0,1305.09918 -Imported From One Health,Misc,-99,Griseofulvin 125mg_100_CMST,1816,1.0,1286.12106 -Imported From One Health,Misc,-99,Benzhexol 5mg_100_CMST,1817,1.0,1034.586 -Imported From One Health,Misc,-99,Cimetidine 400mg_100_CMST,1818,1.0,783.05808 -Imported From One Health,Misc,-99,Atenolol 100mg_100_CMST,1819,1.0,522.0411 -Imported From One Health,Misc,-99,Hydrochlorothiazide 25mg_100_CMST,1820,1.0,436.61814 -Imported From One Health,Misc,-99,Atenolol 50mg_100_CMST,1821,1.0,412.88478 -Imported From One Health,Misc,-99,Dexamethasone 0.5mg_100_CMST,1822,1.0,393.89952 -Imported From One Health,Misc,-99,"Aminophylline 25mg/ml, 10ml_each_CMST",1823,1.0,327.46182 -Imported From One Health,Misc,-99,"Cefotaxime 500mg, PFR_each_CMST",1824,1.0,137.63064 -Imported From One Health,Misc,-99,"Ceftriaxone 250mg, PFR_each_CMST",1825,1.0,208.131 -Imported From One Health,Misc,-99,"Chlorpromazine hydrochloride 25mg/ml, 2ml_each_CMST",1826,1.0,1290.86202 -Imported From One Health,Misc,-99,"Dexamethasone 5mg/ml, 5ml_each_CMST",1827,1.0,199.32738 -Imported From One Health,Misc,-99,"Dextrose (glucose) 5%, 500ml_each_CMST",1828,1.0,408.14382 -Imported From One Health,Misc,-99,"Dextrose 50%, 50ml_each_CMST",1829,1.0,384.41046 -Imported From One Health,Misc,-99,"Ergometrine maleate 500mcg/ml + Oxytocin 10IU/ml, 1ml_each_CMST",1830,1.0,151.8678 -Imported From One Health,Misc,-99,"Flucloxacillin 250mg, vial, PFR_each_CMST",1831,1.0,341.69898 -Imported From One Health,Misc,-99,"Frusemide 10mg/ml, 2ml_each_CMST",1832,1.0,71.1858 -Imported From One Health,Misc,-99,"Gentamicin Sulphate 10mg/ml, 2ml_each_CMST",1833,1.0,99.66012 -Imported From One Health,Misc,-99,"Haloperidol 5mg/ml, 2ml_each_CMST",1834,1.0,578.98974 -Imported From One Health,Misc,-99,"Hydralazine hydrochloride 20mg/ml, 1ml_each_CMST",1835,1.0,991.87452 -Imported From One Health,Misc,-99,"Hydrocortisone sodium succinate iv 50mg/ml, 2ml_each_CMST",1836,1.0,341.69898 -Imported From One Health,Misc,-99,"Lignocaine hydrochloride 1%, 25ml_each_CMST",1837,1.0,151.8678 -Imported From One Health,Misc,-99,"Magnesium sulphate 50%, 2ml ampoule_each_CMST",1838,1.0,50.10852 -Imported From One Health,Misc,-99,"Medroxyprogesterone acetate injection 150mg/mL, 1mL vial with 2ml syringe with 22g 0.7 X 25mm needle_each_CMST",1839,1.0,783.05808 -Imported From One Health,Misc,-99,"Morphine sulphate 15mg/ml, 1ml_each_CMST",1840,1.0,180.34212 -Imported From One Health,Misc,-99,"Paraldehyde, 10ml_each_CMST",1841,1.0,28403.7411 -Imported From One Health,Misc,-99,"Phenobarbitone sodium 200mg/ml, 1ml_each_CMST",1842,1.0,422.38098 -Imported From One Health,Misc,-99,"Phytomenadione 2mg/ml, 1ml (Vitamin K)_each_CMST",1843,1.0,370.1733 -Imported From One Health,Misc,-99,"Promethazine hydrochloride 25mg/ml, 2ml_each_CMST",1844,1.0,455.59626 -Imported From One Health,Misc,-99,"Sodium chloride 0.9%, 500ml_each_CMST",1845,1.0,336.95088 -Imported From One Health,Misc,-99,"Sodium lactate + glucose (darrows half-strength in dextrose 5%), 1000ml_each_CMST",1846,1.0,479.32962 -Imported From One Health,Misc,-99,"Suxamethonium chloride 50mg/ml, 2ml_each_CMST",1847,1.0,541.02636 -Imported From One Health,Misc,-99,"Thiopentone sodium 500mg, PFR_each_CMST",1848,1.0,541.02636 -Imported From One Health,Misc,-99,Vincristine sulphate 1mg PFR_each_CMST,1849,1.0,1414.2555 -Imported From One Health,Misc,-99,"Water for injections, 10ml_each_CMST",1850,1.0,42.71148 -Imported From One Health,Misc,-99,"Hepatitis B vaccine, 20mcg/ml, 1ml vial_each_CMST",1851,1.0,1162.72758 -Imported From One Health,Misc,-99,"Rabies vaccine course, (1x 5, 0.5ml/dose PFR &_x000B_ diluent x 5 vials)_each_CMST",1852,1.0,40377.4497 -Imported From One Health,Misc,-99,Tetanus antitoxin 1500 IU_each_CMST,1853,1.0,1680.02058 -Imported From One Health,Misc,-99,Acetone_5_CMST,1854,1.0,5956.00236 -Imported From One Health,Misc,-99,Benzoic acid_500_CMST,1855,1.0,1665.78342 -Imported From One Health,Misc,-99,Calamine_25Kg_CMST,1856,1.0,103672.46442 -Imported From One Health,Misc,-99,Emulsifying wax _25kg_CMST,1857,1.0,77261.96856 -Imported From One Health,Misc,-99,Formaldehyde liquid 40%_5L_CMST,1858,1.0,25916.92908 -Imported From One Health,Misc,-99,Halothane _0.333333333333333_CMST,1859,1.0,30415.96446 -Imported From One Health,Misc,-99,Iodine_1kg_CMST,1860,1.0,78818.59566 -Imported From One Health,Misc,-99,Potassium iodide_1kg_CMST,1861,1.0,32138.70366 -Imported From One Health,Misc,-99,Salicylic acid_25_CMST,1862,1.0,267042.61164 -Imported From One Health,Misc,-99,Sodium citrate_500g_CMST,1863,1.0,6568.21452 -Imported From One Health,Misc,-99,Sodium nitrate_100g_CMST,1864,1.0,8903.15874 -Imported From One Health,Misc,-99,Sodium thiosulphate_500g_CMST,1865,1.0,2572.23498 -Imported From One Health,Misc,-99,Zinc oxide_25_CMST,1866,1.0,124406.95302 -Imported From One Health,Misc,-99,Acyclovir eye ointment 3%_5_CMST,1867,1.0,1219.67622 -Imported From One Health,Misc,-99,Atropine sulphate eye ointment 1%_3.5g_CMST,1868,1.0,341.69898 -Imported From One Health,Misc,-99,Calamine lotion + sulphur 2%_1_CMST,1869,1.0,1034.586 -Imported From One Health,Misc,-99,Calamine lotion aqueous_1_CMST,1870,1.0,930.17778 -Imported From One Health,Misc,-99,Cetrimide 15% + chlorhexidine 1.5% solution.for dilution _5_CMST,1871,1.0,15243.5787 -Imported From One Health,Misc,-99,Chloramphenicol 1% eye ointment_3.5_CMST,1872,1.0,194.57928 -Imported From One Health,Misc,-99,Chloramphenicol 125mg/5ml suspension_1_CMST,1873,1.0,569.50068 -Imported From One Health,Misc,-99,Chloramphenicol ear drops 5%_5ml_CMST,1874,1.0,227.8017 -Imported From One Health,Misc,-99,Chloramphenicol eye drops 0.5%_1_CMST,1875,1.0,256.27602 -Imported From One Health,Misc,-99,Chlorpheniramine 2mg/5ml suspension_100_CMST,1876,1.0,223.0536 -Imported From One Health,Misc,-99,Cotrimoxazole 240mg/5ml_100_CMST,1877,1.0,469.83342 -Imported From One Health,Misc,-99,Dextrose monohydrate (glucose)_500g_CMST,1878,1.0,2353.92948 -Imported From One Health,Misc,-99,Emulsifying ointment_500g_CMST,1879,1.0,2690.88036 -Imported From One Health,Misc,-99,Gentamicin 0.3% eye drops_5ml_CMST,1880,1.0,251.52792 -Imported From One Health,Misc,-99,Glycerine_0.5_CMST,1881,1.0,1504.42656 -Imported From One Health,Misc,-99,Hydrocortisone eye ointment 1%_3.5g_CMST,1882,1.0,355.93614 -Imported From One Health,Misc,-99,Hydrocortisone skin ointment 1%_1_CMST,1883,1.0,393.89952 -Imported From One Health,Misc,-99,Ketoconazole suspension 100mg/5ml_100ml_CMST,1884,1.0,892.2144 -Imported From One Health,Misc,-99,"Lignocaine gel 2%, 30g_1_CMST",1885,1.0,987.13356 -Imported From One Health,Misc,-99,Metronidazole oral suspension 200mg /5ml_100 ml_CMST,1886,1.0,375.79962 -Imported From One Health,Misc,-99,"Nystatin oral suspension 100,000 IU/ml_20_CMST",1887,1.0,550.51542 -Imported From One Health,Misc,-99,Povidone iodine 10% in alcoholic solution_500ml_CMST,1888,1.0,2733.59184 -Imported From One Health,Misc,-99,Salbutamol solution for nebulising 5mg/ml_30ml_CMST,1889,1.0,726.10944 -Imported From One Health,Misc,-99,"Salbutamol sulphate aerosol inhalation, 100mcg/dose, 200 doses _each_CMST",1890,1.0,1219.67622 -Imported From One Health,Misc,-99,Salicylic acid 5% + sulphur 5% ointment (in EO base)_500g_CMST,1891,1.0,3208.17336 -Imported From One Health,Misc,-99,Silver nitrate stick pencil (toughened)_each_CMST,1892,1.0,522.0411 -Imported From One Health,Misc,-99,Silver sulphadiazine cream 1% 50G_1_CMST,1893,1.0,479.32962 -Imported From One Health,Misc,-99,Tetracycline eye ointment 1%_3.5_CMST,1894,1.0,408.14382 -Imported From One Health,Misc,-99,"Vitamin, multiple syrup_100ml_CMST",1895,1.0,441.3591 -Imported From One Health,Misc,-99,Zinc oxide & salicylic acid paste BP (Lassar's)_500g_CMST,1896,1.0,3369.53022 -Imported From One Health,Misc,-99,Zinc oxide 15% ointment (in EO base)_5_CMST,1897,1.0,3250.88484 -Imported From One Health,Misc,-99,Zinc oxide 15% ointment +sulphur 5%_5_CMST,1898,1.0,2168.83926 -Imported From One Health,Misc,-99,"Bandage, crepe 10cm 1.4m long (4m when stretched)_each_CMST",1899,1.0,322.71372 -Imported From One Health,Misc,-99,"Bandage, plaster of paris 10cm_12_CMST",1900,1.0,5495.658 -Imported From One Health,Misc,-99,"Bandage, WOW 10cm x 4m _10_CMST",1901,1.0,612.21216 -Imported From One Health,Misc,-99,"Dressing, paraffin gauze 9.5cm x 9.5cm (square)_pack_x000B_of 36_CMST",1902,1.0,1034.586 -Imported From One Health,Misc,-99,"Gauze, absorbent 90cm X 100m_each_CMST",1903,1.0,12002.18292 -Imported From One Health,Misc,-99,Plaster of Paris (POP) 7.5cm x 7.5cm slab_12_CMST,1904,1.0,4712.59992 -Imported From One Health,Misc,-99,Plaster of Paris (POP) 12.5cm x 7.5cm slab_12_CMST,1905,1.0,7066.5294 -Imported From One Health,Misc,-99,"Plaster, extension 7.5cm x 5m_each_CMST",1906,1.0,707.12418 -Imported From One Health,Misc,-99,"Plaster, zinc oxide 5cm x 5m_each_CMST",1907,1.0,522.0411 -Imported From One Health,Misc,-99,"Plaster, zinc oxide 7.5cm x 5m_each_CMST",1908,1.0,863.74008 -Imported From One Health,Misc,-99,Braided synthetic sterile polyglyctin 3/0 round bodied needle cc 1/2 circle 20mm_12_CMST,1909,1.0,27402.37038 -Imported From One Health,Misc,-99,Polyglycolic Acid (0) round bodied needle cc ½ circle 20mm _12_CMST,1910,1.0,6753.30474 -Imported From One Health,Misc,-99,Catgut chromic 2/0 needle round bodied ½ circle 35mm_12_CMST,1911,1.0,24754.2015 -Imported From One Health,Misc,-99,Catgut chromic 3/0 needle round bodied ½ circle 25mm_12_CMST,1912,1.0,21099.92094 -Imported From One Health,Misc,-99,"Silk (3/0), 2.0 gauge on 1/2 circle round bodied needle 75cm on 36mm _12_CMST",1913,1.0,55255.59606 -Imported From One Health,Misc,-99,Black braided non absorbable sterile silk 2/0 on needle cc 40mm_12_CMST,1914,1.0,8461.79964 -Imported From One Health,Misc,-99,Black braided non absorbable sterile silk 4/0 on needle cc 25mm_12_CMST,1915,1.0,76047.04044 -Imported From One Health,Misc,-99,Airway disposable PVC/Silicon size 2_each_CMST,1916,1.0,484.07058 -Imported From One Health,Misc,-99,"Bags urine drainage 2,000ml with outlet_each_CMST",1917,1.0,157.40844 -Imported From One Health,Misc,-99,Cannula iv (winged with injection pot) 22_each_CMST,1918,1.0,199.32738 -Imported From One Health,Misc,-99,Cannula iv (winged with injection pot) 24_each_CMST,1919,1.0,199.32738 -Imported From One Health,Misc,-99,Catheter disposable female FG 14_each_CMST,1920,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter disposable female FG 16_each_CMST,1921,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 12g_each_CMST,1922,1.0,550.51542 -Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 16g_each_CMST,1923,1.0,550.51542 -Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 18g_each_CMST,1924,1.0,550.51542 -Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 16_each_CMST,1925,1.0,450.8553 -Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 24, 3 way_each_CMST",1926,1.0,341.69898 -Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 26, 3 way_each_CMST",1927,1.0,436.61814 -Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30c FG 28, 3 way_each_CMST",1928,1.0,256.27602 -Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 20, 3 way_each_CMST",1929,1.0,944.42208 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 16_each_CMST,1930,1.0,336.95088 -Imported From One Health,Misc,-99,"Clips, umbilical cord, polythene_each_CMST",1931,1.0,66.4377 -Imported From One Health,Misc,-99,Giving set paed iv administration + needle 60 drops/ml_each_CMST,1932,1.0,213.56454 -Imported From One Health,Misc,-99,Glove disposable powdered latex medium_100_CMST,1933,1.0,2221.04694 -Imported From One Health,Misc,-99,Glove gynaecological elbow length medium_each_CMST,1934,1.0,1570.86426 -Imported From One Health,Misc,-99,Glove gynaecological elbow length large_each_CMST,1935,1.0,1570.86426 -Imported From One Health,Misc,-99,Glove surgeon's size 7½ sterile_2_CMST,1936,1.0,242.03886 -Imported From One Health,Misc,-99,Introducer for catheters_each_CMST,1937,1.0,944.42208 -Imported From One Health,Misc,-99,Needle disposable Luer 23g x 2.5cm_100_CMST,1938,1.0,1490.1894 -Imported From One Health,Misc,-99,Plug catheter (spigot) medium_each_CMST,1939,1.0,156.6159 -Imported From One Health,Misc,-99,"Probe, silver 15cm_each_CMST",1940,1.0,783.05808 -Imported From One Health,Misc,-99,Scalp vein set disposable Luer 21g_each_CMST,1941,1.0,42.71148 -Imported From One Health,Misc,-99,Scalp vein set disposable Luer 23g_each_CMST,1942,1.0,42.71148 -Imported From One Health,Misc,-99,Scalp vein set disposable Luer 25g_each_CMST,1943,1.0,42.71148 -Imported From One Health,Misc,-99,Scalpel blade size 11 (individually wrapped)_100_CMST,1944,1.0,2050.19388 -Imported From One Health,Misc,-99,Scalpel blade size 15 (individually wrapped)_100_CMST,1945,1.0,2515.28634 -Imported From One Health,Misc,-99,Scalpel blade size 20 (individually wrapped)_100_CMST,1946,1.0,2515.28634 -Imported From One Health,Misc,-99,Scalpel blade size 21 (individually wrapped)_100_CMST,1947,1.0,2515.28634 -Imported From One Health,Misc,-99,Scalpel blade size 23 (individually wrapped)_100_CMST,1948,1.0,2515.28634 -Imported From One Health,Misc,-99,Scalpel blade size 24 (individually wrapped)_100_CMST,1949,1.0,2515.28634 -Imported From One Health,Misc,-99,Sharps disposal receptor_each_CMST,1950,1.0,450.8553 -Imported From One Health,Misc,-99,Stethoscope foetal (plastic)_each_CMST,1951,1.0,3924.79374 -Imported From One Health,Misc,-99,Syringe ear metal_each_CMST,1952,1.0,5505.1542 -Imported From One Health,Misc,-99,Syringe insulin 100 IU with 30g needle _each_CMST,1953,1.0,284.75034 -Imported From One Health,Misc,-99,"Syringe, 2ml, disposable, hypoluer with 23g needle_each_CMST",1954,1.0,85.42296 -Imported From One Health,Misc,-99,"Syringe, 2ml, disposable, hypoluer with 25g needle_each_CMST",1955,1.0,71.1858 -Imported From One Health,Misc,-99,"Syringe, autodestruct, 10ml, disposable with 21g needle_each_CMST",1956,1.0,113.89728 -Imported From One Health,Misc,-99,"Syringe, autodestruct, 20ml, disposable with 21g needle_each_CMST",1957,1.0,85.42296 -Imported From One Health,Misc,-99,"Syringe, autodestruct, 2ml, disposable, hypoluer with 23g needle_each_CMST",1958,1.0,66.4377 -Imported From One Health,Misc,-99,"Syringe, autodestruct, 2ml, disposable, hypoluer with 25g needle_each_CMST",1959,1.0,52.20054 -Imported From One Health,Misc,-99,"Syringe, autodestruct, 5ml, disposable, hypoluer with 21g needle_each_CMST",1960,1.0,80.682 -Imported From One Health,Misc,-99,"Syringe,10ml, disposable, hypoluer with 21g needle_each_CMST",1961,1.0,156.6159 -Imported From One Health,Misc,-99,"Tape, umbilical cotton, 3mm x 20m, non-sterile_Reel_CMST",1962,1.0,166.10496 -Imported From One Health,Misc,-99,"Tube, endotracheal 15mm size 7_each_CMST",1963,1.0,783.05808 -Imported From One Health,Misc,-99,"Tube, endotracheal, PVC cuffed, size 7mm_each_CMST",1964,1.0,370.1733 -Imported From One Health,Misc,-99,"Tube, endotracheal, PVC cuffed, size 7.5mm_each_CMST",1965,1.0,227.8017 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 8_each_CMST",1966,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 10_each_CMST",1967,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 12_each_CMST",1968,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 14_each_CMST",1969,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 16_each_CMST",1970,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 18_each_CMST",1971,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 24_each_CMST",1972,1.0,284.75034 -Imported From One Health,Misc,-99,"Tube, tracheostomy, cuffed size 7 with introducer and 15mm connector_each_CMST",1973,1.0,1727.48016 -Imported From One Health,Misc,-99,"Tube, tracheostomy, cuffed size 7.5 with introducer and 15mm connector_each_CMST",1974,1.0,1727.48016 -Imported From One Health,Misc,-99,"Tube, tracheostomy, non cuffed size 4_each_CMST",1975,1.0,1727.48016 -Imported From One Health,Misc,-99,"Bag tablet dispensing, polythene, disposable 9 x 10cm_50_CMST",1976,1.0,441.3591 -Imported From One Health,Misc,-99,"Bottle dropper, amber 10ml_each_CMST",1977,1.0,123.39348 -Imported From One Health,Misc,-99,"Apron, surgeon's polythene, foot length_each_CMST",1978,1.0,1471.20414 -Imported From One Health,Misc,-99,"Cup, feeding_each_CMST",1979,1.0,1570.86426 -Imported From One Health,Misc,-99,"Urinal, female stainless steel_each_CMST",1980,1.0,10208.26506 -Imported From One Health,Misc,-99,"Urinal, male stainless steel_each_CMST",1981,1.0,9187.90908 -Imported From One Health,Misc,-99,ABX Minoclair_ 500ml _CMST,1982,1.0,25855.23234 -Imported From One Health,Misc,-99,ABX Minoton_ 20L _CMST,1983,1.0,102723.30138 -Imported From One Health,Misc,-99,Acetone _2.5_CMST,1984,1.0,5011.58742 -Imported From One Health,Misc,-99,Act 5 diff Hgb_kit_CMST,1985,1.0,44762.5878 -Imported From One Health,Misc,-99,Act 5 diff WBC Lyse_kit_CMST,1986,1.0,79658.60952 -Imported From One Health,Misc,-99,Bilirubin in urine (Iactotest)_100_CMST,1987,1.0,26282.35428 -Imported From One Health,Misc,-99,Blood grouping serum Anti-A 10ml_each_CMST,1988,1.0,5970.23952 -Imported From One Health,Misc,-99,Blood in urine (Haemastix)_100_CMST,1989,1.0,21484.3314 -Imported From One Health,Misc,-99,"Bottle, blood collecting plain plastic vacuated, 5ml plus vacutainer needle 21G_1000_CMST",1990,1.0,39271.67076 -Imported From One Health,Misc,-99,"Bottle, blood collecting plain glass vacuated, 7ml _1000_CMST",1991,1.0,170.84592 -Imported From One Health,Misc,-99,"Bottle, blood collecting plastic vacuated with fluoride oxalate, 5ml _x000B_screw cap plus vacutainer needle 21G_1000_CMST",1992,1.0,43808.67666 -Imported From One Health,Misc,-99,"Bottle, blood collecting vacuated, 4.5 ml with EDTA K3 tubes plus vacutainer needle 21G_1000_CMST",1993,1.0,44501.56368 -Imported From One Health,Misc,-99,"Bottle, plastic plain with screw cap 12ml_1000_CMST",1994,1.0,73512.76884 -Imported From One Health,Misc,-99,"Bottle, wide mouth stainless steel screw cap 30ml_each_CMST",1995,1.0,1300.35822 -Imported From One Health,Misc,-99,Creatinine kinase test kit-Human 50ml_Kit_CMST,1996,1.0,66095.0514 -Imported From One Health,Misc,-99,"Culture swabs, sterile with hard plastic container with cap_1000_CMST",1997,1.0,3763.43688 -Imported From One Health,Misc,-99,"Dextrose, citrate blood bag with needle 16g, 250ml_each_CMST",1998,1.0,1347.81066 -Imported From One Health,Misc,-99,"Dextrose, citrate blood bag with needle 16g, 450ml_each_CMST",1999,1.0,1248.15054 -Imported From One Health,Misc,-99,Disposable Pipettes_1000g_CMST,2000,1.0,188333.16516 -Imported From One Health,Misc,-99,Fluorescent microscope square bulbs 100W_each_CMST,2001,1.0,10559.4531 -Imported From One Health,Misc,-99,Glucose in blood (Dextrostix)_25_CMST,2002,1.0,40609.99236 -Imported From One Health,Misc,-99,Glucose in urine (Clinistix)_100_CMST,2003,1.0,4299.71514 -Imported From One Health,Misc,-99,Glucose (GOD) test kit HUMAN_4 x 100ML_CMST,2004,1.0,73726.33338 -Imported From One Health,Misc,-99,Gram's A fluid_500ml_CMST,2005,1.0,3853.60794 -Imported From One Health,Misc,-99,HaemaCue Hb 201+ Machine_each_CMST,2006,1.0,509312.02938 -Imported From One Health,Misc,-99,Haemacue Hb 201+ - cuvettes _50_CMST,2007,1.0,23738.59362 -Imported From One Health,Misc,-99,Hepatitis B test kit-Dertemine_100 tests_CMST,2008,1.0,949.16304 -Imported From One Health,Misc,-99,Microscope slide frosted end 75mm x 25mm_50_CMST,2009,1.0,1808.15502 -Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 10cm_100_CMST,2010,1.0,4442.08674 -Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 15cm_100_CMST,2011,1.0,7555.34808 -Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 24cm_100_CMST,2012,1.0,31578.69204 -Imported From One Health,Misc,-99,FACSCOUNT Paper thermal _100_CMST,2013,1.0,61145.16072 -Imported From One Health,Misc,-99,Partec CD4 % easy count Kit (100 tests)_Kit_CMST,2014,1.0,497784.43512 -Imported From One Health,Misc,-99,Partec CD4 easy count Kit (100 tests)_Kit_CMST,2015,1.0,212944.99506 -Imported From One Health,Misc,-99,pH/protein/glucose/ketones/blood in urine (Labstix)_50_CMST,2016,1.0,14731.02666 -Imported From One Health,Misc,-99,"Pipette, pasteur plastic disposable 3ml_1000_CMST",2017,1.0,19604.99058 -Imported From One Health,Misc,-99,"Pipette, plastic_1000_CMST",2018,1.0,19604.99058 -Imported From One Health,Misc,-99,Pregnancy slide test kit_100_CMST,2019,1.0,21982.64628 -Imported From One Health,Misc,-99,"SGOT (Aspartate Aminotransferase) test kit, 15mll-Human_Kit_CMST",2020,1.0,64068.58374 -Imported From One Health,Misc,-99,"SGPT (Alanine Aminotransferase ) test kit, 15ml-Human_Kit_CMST",2021,1.0,27872.2038 -Imported From One Health,Misc,-99,keylab cholesterol _5x40 ml_CMST,2022,1.0,11423.19318 -Imported From One Health,Misc,-99,keylab Glucose_5x40 ml_CMST,2023,1.0,9282.82824 -Imported From One Health,Misc,-99,"Barium enema administration kit (tubing, Air insufflator _x000B_and one shot inflator) _each_CMST",2024,1.0,20369.0634 -Imported From One Health,Misc,-99,"Barium sulphate disposable enema (Tubing, one shot inflator and air insufflator) _KIT_CMST",2025,1.0,22125.01788 -Imported From One Health,Misc,-99,Lead rubber x-ray protective aprons up to 150kVp 0.50mm_each_CMST,2026,1.0,470135.27778 -Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate inj (Urografin/Urovideo) 10%+ 66% 20ml_5_CMST,2027,1.0,27872.2038 -Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate inj (Urografin/Urovideo) 60% 20ml_5_CMST,2028,1.0,19614.47964 -Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate solution 10% + 66%. (Gastrografin) oral/rectal 100ml bottle_each_CMST,2029,1.0,7488.90324 -Imported From One Health,Misc,-99,Utransist 300mg/ml (20ml)_each_CMST,2030,1.0,13829.3232 -Imported From One Health,Misc,-99,Dental Technician lab kit_case_CMST,2031,1.0,1812.90312 -Imported From One Health,Misc,-99,Mepivacaine hydrochloride 3% plain 1.8ml cartridge_50_CMST,2032,1.0,10236.73938 -Imported From One Health,Misc,-99,"Oil spray for handpiece, universal_each_CMST",2033,1.0,13824.5751 -Imported From One Health,Misc,-99,"Plastic Bib, adult _each_CMST",2034,1.0,2254.26222 -Imported From One Health,Misc,-99,"Plastic Bib, children _each_CMST",2035,1.0,2254.26222 -Imported From One Health,Misc,-99,"Rolls, cotton dental_750_CMST",2036,1.0,2790.54048 -Imported From One Health,Misc,-99,"Syringes for dental cartridge, 2ml_each_CMST",2037,1.0,11717.43258 -Imported From One Health,Misc,-99,"Blanket cellular, adult, blue, 100% cotton, marked MOH 200 cm x 250 cm._each_CMST",2038,1.0,42033.73692 -Imported From One Health,Misc,-99,"Blanket cellular, adult, gold, 100% cotton, marked MOH 200 cm x 250 cm._each_CMST",2039,1.0,42033.73692 -Imported From One Health,Misc,-99,"Draw sheets, blue , 100% cotton marked MOH – 150cm x _x000B_120 cm, machine wash at high temperature_each_CMST",2040,1.0,12016.42008 -Imported From One Health,Misc,-99,Pillows foam_each_CMST,2041,1.0,3184.44714 -Imported From One Health,Misc,-99,Bromocriptine 2.5mg_100_CMST,2042,1.0,39428.27952 -Imported From One Health,Misc,-99,Carbimazole 5mg_100_CMST,2043,1.0,10516.74162 -Imported From One Health,Misc,-99,Cyclophosphamide 50mg_100_CMST,2044,1.0,5889.56466 -Imported From One Health,Misc,-99,Folic acid 5mg_1000_CMST,2045,1.0,3269.8701 -Imported From One Health,Misc,-99,Isosorbide dinitrate 10mg_1000_CMST,2046,1.0,14379.83862 -Imported From One Health,Misc,-99,Methotrexate 2.5mg_100_CMST,2047,1.0,9472.65942 -Imported From One Health,Misc,-99,Methotrexate 10mg_100_CMST,2048,1.0,20463.98256 -Imported From One Health,Misc,-99,Misoprostol 200 mcg _100_CMST,2049,1.0,4954.63878 -Imported From One Health,Misc,-99,Thioridazine HCL 100 mg_1000_CMST,2050,1.0,77285.69478 -Imported From One Health,Misc,-99,Ciprofloxacin 500mg_100_CMST,2051,1.0,2548.50876 -Imported From One Health,Misc,-99,Magnesium Slow_100_CMST,2052,1.0,28209.16182 -Imported From One Health,Misc,-99,Nifedipine 20mg (slow release)_100_CMST,2053,1.0,1570.86426 -Imported From One Health,Misc,-99,Norfloxacin 400mg _100_CMST,2054,1.0,1442.72982 -Imported From One Health,Misc,-99,Omeprazole 20mg_100_CMST,2055,1.0,3848.85984 -Imported From One Health,Misc,-99,Pericyazine 4 mg_100_CMST,2056,1.0,1376.28498 -Imported From One Health,Misc,-99,Procyclidine 5mg_1000_CMST,2057,1.0,86392.929 -Imported From One Health,Misc,-99,Proguanil hydrochloride 100mg_100_CMST,2058,1.0,10943.86356 -Imported From One Health,Misc,-99,Ranitidine 150mg_100_CMST,2059,1.0,1157.97948 -Imported From One Health,Misc,-99,"Actinomycin D 500 mcg PFR, (with mannitol)_each_CMST",2060,1.0,21204.32916 -Imported From One Health,Misc,-99,"Bupivacaine spinal hyperbaric 0.5%, 4ml ampoule_each_CMST",2061,1.0,816.2805 -Imported From One Health,Misc,-99,"Bupivacaine spinal isobaric 0.5%, 4ml ampoule_each_CMST",2062,1.0,669.1608 -Imported From One Health,Misc,-99,"Cyclophosphamide 200mg, PFR_each_CMST",2063,1.0,1305.09918 -Imported From One Health,Misc,-99,Dianeal + Dextrose 1.5% intraperitoneal dialysis soln. with minicap_2L_CMST,2064,1.0,9330.28068 -Imported From One Health,Misc,-99,Dianeal + Dextrose 2.5% intraperitoneal dialysis soln. with minicap_2L_CMST,2065,1.0,9330.28068 -Imported From One Health,Misc,-99,"Digoxin 250 micrograms/ml, 2ml_each_CMST",2066,1.0,393.89952 -Imported From One Health,Misc,-99,Dopamine 40mg/ml 5ml ampoule_each_CMST,2067,1.0,2557.99782 -Imported From One Health,Misc,-99,"Ephedrine sulphate 30mg/ml, 1ml_each_CMST",2068,1.0,3341.0559 -Imported From One Health,Misc,-99,"Haloperidol decanoate oily 50mg/ml, 1ml ampoule _each_CMST",2069,1.0,1072.55652 -Imported From One Health,Misc,-99,"Heparin sodium 5,000 IU/ml, 5ml_each_CMST",2070,1.0,1205.43906 -Imported From One Health,Misc,-99,"Lignocaine hydrochloride 2%, 25ml_each_CMST",2071,1.0,370.78734 -Imported From One Health,Misc,-99,"Metoclopramide hydrochloride 5mg/ml, 2ml_each_CMST",2072,1.0,3241.39578 -Imported From One Health,Misc,-99,"Neostigmine 2.5mg/ml, inj, 1ml ampoule_each_CMST",2073,1.0,313.22466 -Imported From One Health,Misc,-99,"Procyclidine HCl 5mg/ml, 2ml ampoule_each_CMST",2074,1.0,284.75034 -Imported From One Health,Misc,-99,Erythropoetin 2000 IU vial_each_CMST,2075,1.0,22613.83656 -Imported From One Health,Misc,-99,"Yellow fever vaccine 10-dose (5ml) vial, _x000B_PFR + diluent ampoule_each_CMST",2076,1.0,37843.1781 -Imported From One Health,Misc,-99,Anise oil_100ml_CMST,2077,1.0,4612.9398 -Imported From One Health,Misc,-99,Chloramine_1_CMST,2078,1.0,6126.85542 -Imported From One Health,Misc,-99,Citric acid_500g_CMST,2079,1.0,3535.63518 -Imported From One Health,Misc,-99,Halothane _2_CMST,2080,1.0,30415.96446 -Imported From One Health,Misc,-99,Nitric acid_2.5L_CMST,2081,1.0,6905.17254 -Imported From One Health,Misc,-99,Paraffin hard_25kg_CMST,2082,1.0,243474.86394 -Imported From One Health,Misc,-99,Betamethasone ointment 0.1%_1_CMST,2083,1.0,365.4252 -Imported From One Health,Misc,-99,Betamethasone sodium eardrops 0.1%_10ml_CMST,2084,1.0,1286.12106 -Imported From One Health,Misc,-99,"Lignocaine spray, 10% 20ml (for gastroscopy)_each_CMST",2085,1.0,6895.67634 -Imported From One Health,Misc,-99,"Lignocaine spray, 2% (for gastroscopy)_each_CMST",2086,1.0,6895.67634 -Imported From One Health,Misc,-99,Miconazole ear drop 1%_10ml_CMST,2087,1.0,28816.62588 -Imported From One Health,Misc,-99,Miconazole eye drops 1%_10ml_CMST,2088,1.0,24445.72494 -Imported From One Health,Misc,-99,Neomycin + Bacitracin skin ointment_1_CMST,2089,1.0,522.0411 -Imported From One Health,Misc,-99,"Salicylic acid 20%, ointment_0.625_CMST",2090,1.0,2572.23498 -Imported From One Health,Misc,-99,Sodium hypochlorite concentrated solution_5L_CMST,2091,1.0,3535.63518 -Imported From One Health,Misc,-99,"Bandage, plaster of paris 5cm_12_CMST",2092,1.0,4086.1506 -Imported From One Health,Misc,-99,"Bandage, plaster of paris 7.5cm_12_CMST",2093,1.0,4318.7004 -Imported From One Health,Misc,-99,"Bandage, stockinette 10cm_10m_CMST",2094,1.0,9031.30032 -Imported From One Health,Misc,-99,Lint_500g_CMST,2095,1.0,3753.94068 -Imported From One Health,Misc,-99,Catgut chromic 4/0 needle round bodied ½ circle 20mm_12_CMST,2096,1.0,13853.04942 -Imported From One Health,Misc,-99,Black blaided silk nonabsorbable sterile surgical ligature 2/0 150cm_12_CMST,2097,1.0,20198.21748 -Imported From One Health,Misc,-99,Monofilament polyamide nylon 10/0 round bodied needle_12_CMST,2098,1.0,47538.89112 -Imported From One Health,Misc,-99,Virgin silk twisted blue gauge 0.2 (10/0) 30cm on 6.5mm spatula curved (3/8 circle). Advanced micropoint double needle._12_CMST,2099,1.0,398231.34372 -Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 14_each_CMST,2100,1.0,313.22466 -Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 18_each_CMST,2101,1.0,308.47656 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 14_each_CMST,2102,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 18_each_CMST,2103,1.0,242.03886 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 20_each_CMST,2104,1.0,280.00224 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 22_each_CMST,2105,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 24_each_CMST,2106,1.0,578.98974 -Imported From One Health,Misc,-99,Condom Catheter _each_CMST,2107,1.0,408.14382 -Imported From One Health,Misc,-99,"Currette, short blunt small_each_CMST",2108,1.0,783.05808 -Imported From One Health,Misc,-99,"Currette, short blunt large_each_CMST",2109,1.0,783.05808 -Imported From One Health,Misc,-99,ECG paper for printing_Roll_CMST,2110,1.0,564.75258 -Imported From One Health,Misc,-99,Forceps mosquito straight_2_CMST,2111,1.0,1162.72758 -Imported From One Health,Misc,-99,Forceps needle holder (Mayo's) straight_2_CMST,2112,1.0,1570.86426 -Imported From One Health,Misc,-99,Forceps needle holder 18cm (Mayo's)_2_CMST,2113,1.0,1570.86426 -Imported From One Health,Misc,-99,Forceps sinus (Lister's)_2_CMST,2114,1.0,2254.26222 -Imported From One Health,Misc,-99,Forceps tissue 12.5cm (Alli's)_2_CMST,2115,1.0,1176.96474 -Imported From One Health,Misc,-99,Giving sets iv (paediatric) with calibrated burrette_each_CMST,2116,1.0,650.17554 -Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,infant(90mm) _each_CMST",2117,1.0,17735.13168 -Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,child(114mm)_each_CMST",2118,1.0,17735.13168 -Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,adult (130mm)_each_CMST",2119,1.0,17735.13168 -Imported From One Health,Misc,-99,"Laryngoscope Macintosh, spare bulb_each_CMST",2120,1.0,355.93614 -Imported From One Health,Misc,-99,Needle lumbar puncture Luer 19g x 5cm_each_CMST,2121,1.0,450.8553 -Imported From One Health,Misc,-99,Needle lumbar puncture Luer 20g x 10cm_each_CMST,2122,1.0,450.8553 -Imported From One Health,Misc,-99,Needle spinal disposable Luer 23g x 10cm cutting bevel/pencil point_each_CMST,2123,1.0,450.8553 -Imported From One Health,Misc,-99,Shears plaster (Lorenz) 48cm_pair_CMST,2124,1.0,8091.62634 -Imported From One Health,Misc,-99,"Tube, chest drainage, size 22 with introducer_each_CMST",2125,1.0,85.42296 -Imported From One Health,Misc,-99,"Mortar & pestle, glass, 10cm_set_CMST",2126,1.0,7854.33558 -Imported From One Health,Misc,-99,"Sterilizer, instrument, 27.5 x 14 x 10cm, electrical_each_CMST",2127,1.0,95035.07076 -Imported From One Health,Misc,-99,"Tray, stainless steel no lid 20 x 15 x 5cm_each_CMST",2128,1.0,7066.5294 -Imported From One Health,Misc,-99,"Tray, stainless steel no lid 25 x 20 x 5cm_each_CMST",2129,1.0,7303.82016 -Imported From One Health,Misc,-99,"Tray, stainless steel no lid 45 x 32.5 x 5cm_each_CMST",2130,1.0,20421.27108 -Imported From One Health,Misc,-99,"Tray, stainless steel with lid 20 x15 x 5cm_each_CMST",2131,1.0,10208.26506 -Imported From One Health,Misc,-99,"Tray, stainless steel with lid 30 x 25 x 5cm_each_CMST",2132,1.0,16491.72924 -Imported From One Health,Misc,-99,"Trolley, patient_each_CMST",2133,1.0,278816.99286 -Imported From One Health,Misc,-99,"Trolley, soiled linen kick-about_each_CMST",2134,1.0,51050.80008 -Imported From One Health,Misc,-99,"Trolley, theatre stretcher-type imported_each_CMST",2135,1.0,282741.7866 -Imported From One Health,Misc,-99,Acetone in urine (acetest)_50_CMST,2136,1.0,21071.44662 -Imported From One Health,Misc,-99,ACT 5 diff Rinse_1L_CMST,2137,1.0,33695.33076 -Imported From One Health,Misc,-99,ACT 5 diff diluent _20L_CMST,2138,1.0,89748.22206 -Imported From One Health,Misc,-99,Act 5 Diff fix_1L_CMST,2139,1.0,266117.17482 -Imported From One Health,Misc,-99,Act 5 Diff WBC lyse_1L_CMST,2140,1.0,221938.32486 -Imported From One Health,Misc,-99,"Agar, dextrose_500g_CMST",2141,1.0,37705.54746 -Imported From One Health,Misc,-99,"Agar, SIM_500g_CMST",2142,1.0,64609.6101 -Imported From One Health,Misc,-99,Alkaline phosphatase test kit -HUMAN_Kit_CMST,2143,1.0,42161.87136 -Imported From One Health,Misc,-99,Amoxycillin disc 35mcg_1 x 50 discs_CMST,2144,1.0,3511.90896 -Imported From One Health,Misc,-99,"Amylase test kit, 5ml-HUMAN_Kit_CMST",2145,1.0,48350.42352 -Imported From One Health,Misc,-99,Anti - streptolysin (ASOT) test kit_Kit_CMST,2146,1.0,26040.32256 -Imported From One Health,Misc,-99,"Bacitracin 0.04 units, discs_50_CMST",2147,1.0,3511.90896 -Imported From One Health,Misc,-99,"Bacitracin 0.1 units, discs_50_CMST",2148,1.0,6876.69822 -Imported From One Health,Misc,-99,"Bottle, Bijou, 5ml, with stainless steel screw cap_each_CMST",2149,1.0,298.9875 -Imported From One Health,Misc,-99,"Bottle, blood collecting plastic 5ml with sod-cit 3-8% solution plus vacutainer needle 21G_1000_CMST",2150,1.0,86392.929 -Imported From One Health,Misc,-99,"Bottle, blood culture, 100ml_each_CMST",2151,1.0,906.45156 -Imported From One Health,Misc,-99,Calcium test kit-HUMAN_ 50ml_CMST,2152,1.0,42916.46226 -Imported From One Health,Misc,-99,Chloramphenicol discs_50_CMST,2153,1.0,5490.91704 -Imported From One Health,Misc,-99,Cholesterol test kit-HUMAN_250ml_CMST,2154,1.0,27373.89606 -Imported From One Health,Misc,-99,Cleaning solution for Nova 5_100mls_CMST,2155,1.0,101318.53494 -Imported From One Health,Misc,-99,Cloxacillin discs 5mcg_50_CMST,2156,1.0,7023.81792 -Imported From One Health,Misc,-99,"C-Reactive protein test kit,100ml_Kit_CMST",2157,1.0,34549.57464 -Imported From One Health,Misc,-99,Eclyte calibration cal 12_330mls_CMST,2158,1.0,47282.6151 -Imported From One Health,Misc,-99,Glucose (GOD/PAP)HUMAN_1000ml_CMST,2159,1.0,41549.66634 -Imported From One Health,Misc,-99,"Hemostat control plasma N,1ml_6X1ml_CMST",2160,1.0,50709.1011 -Imported From One Health,Misc,-99,"Humatrol N,5ml_6X5ML_CMST",2161,1.0,39997.7802 -Imported From One Health,Misc,-99,Microtome blades _50_CMST,2162,1.0,58985.81052 -Imported From One Health,Misc,-99,Norfloxacin disc 5mg_100_CMST,2163,1.0,6217.02648 -Imported From One Health,Misc,-99,Nova 5 fluid pack_ pack _CMST,2164,1.0,722176.34958 -Imported From One Health,Misc,-99,Novobiocin 5mg discs_50_CMST,2165,1.0,3511.90896 -Imported From One Health,Misc,-99,Novobiocin disc 5mg_50_CMST,2166,1.0,2747.829 -Imported From One Health,Misc,-99,Penicillin disc_50_CMST,2167,1.0,5490.91704 -Imported From One Health,Misc,-99,Penicillin G 1 unit disc_50_CMST,2168,1.0,5490.91704 -Imported From One Health,Misc,-99,Phosphorus test kit-Human_ 100ml _CMST,2169,1.0,13449.6537 -Imported From One Health,Misc,-99,Protein remover_100ml_CMST,2170,1.0,276273.2322 -Imported From One Health,Misc,-99,"Prothrombin time test kits, 1ml_6 x 1mls_CMST",2171,1.0,36557.05704 -Imported From One Health,Misc,-99,Rack for Westergreen ESR to take 6 tubes_each_CMST,2172,1.0,29395.61562 -Imported From One Health,Misc,-99,Rheumatoid factor test kit_ 45ml _CMST,2173,1.0,41625.60024 -Imported From One Health,Misc,-99,Salmonella (H) factor 1_0.4_CMST,2174,1.0,64068.58374 -Imported From One Health,Misc,-99,"Salmonella (H) factor 1, 2_0.4_CMST",2175,1.0,64068.58374 -Imported From One Health,Misc,-99,Salmonella (H) factor d_0.4_CMST,2176,1.0,64068.58374 -Imported From One Health,Misc,-99,"Salmonella (H) factor g, m_0.4_CMST",2177,1.0,64068.58374 -Imported From One Health,Misc,-99,Salmonella (O) factor (vi)_2ml_CMST,2178,1.0,64068.58374 -Imported From One Health,Misc,-99,Salmonella (O) factor 4_0.4_CMST,2179,1.0,64068.58374 -Imported From One Health,Misc,-99,Salmonella (O) factor 9_0.4_CMST,2180,1.0,64068.58374 -Imported From One Health,Misc,-99,Sulphuric acid_ 2.5L _CMST,2181,1.0,10208.26506 -Imported From One Health,Misc,-99,Total Protein test kit-Human_1000ml_CMST,2182,1.0,15770.36076 -Imported From One Health,Misc,-99,Triglycerides test kit - Human_100mls_CMST,2183,1.0,94925.91444 -Imported From One Health,Misc,-99,Uric acid test kit-Humanl_100mls_CMST,2184,1.0,35427.55188 -Imported From One Health,Misc,-99,X factor discs_100_CMST,2185,1.0,11366.24454 -Imported From One Health,Misc,-99,XV factor discs_100_CMST,2186,1.0,17350.72122 -Imported From One Health,Misc,-99,ABX Alphalyse_each_CMST,2187,1.0,14152.03692 -Imported From One Health,Misc,-99,ABX Basolyse_each_CMST,2188,1.0,66844.88706 -Imported From One Health,Misc,-99,Cortimoxizole prophylaxis,2189,1.0,4533.92142 -Imported From One Health,Misc,-99,ABX Eosinofix_each_CMST,2190,1.0,48578.22522 -Imported From One Health,Misc,-99,AP/PA floating markers left and right_pair_CMST,2191,1.0,8637.39366 -Imported From One Health,Misc,-99,Lead rubber protective aprons 0.5 mm equivalent with hunger_each_CMST,2192,1.0,470135.27778 -Imported From One Health,Misc,-99,"Amalgam capsule no. 1, non-gamma _50_CMST",2193,1.0,19135.15002 -Imported From One Health,Misc,-99,"Trimmer, Mitchell's, osteo no. 4_each_CMST",2194,1.0,15381.20934 -Imported From One Health,Misc,-99,Unsafe injections replaced with AD syringes,2195,1.0,164.20572 -Imported From One Health,Misc,-99,Prazosin 1mg _100_CMST,2196,1.0,17355.46932 -Imported From One Health,Misc,-99,"Fluid, viscoelastic hydroxypropylmethylcellulose, 2% w/v, 3ml ampoule_each_CMST",2197,1.0,469.83342 -Imported From One Health,Misc,-99,Bags syringe sterilization 20cm_1000_CMST,2198,1.0,9425.19984 -Imported From One Health,Misc,-99,Cannula tracheotomy Fuller's FG 17_each_CMST,2199,1.0,783.05808 -Imported From One Health,Misc,-99,Cannula tracheotomy Fuller's FG 24_each_CMST,2200,1.0,1414.2555 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 8_each_CMST,2201,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 10_each_CMST,2202,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 12_each_CMST,2203,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 16_each_CMST,2204,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 18_each_CMST,2205,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 20_each_CMST,2206,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 22_each_CMST,2207,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 26_each_CMST,2208,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 28_each_CMST,2209,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 14_each_CMST,2210,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 16_each_CMST,2211,1.0,341.69898 -Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 18_each_CMST,2212,1.0,341.69898 -Imported From One Health,Misc,-99,Needle suture round bodied no. 4_6_CMST,2213,1.0,550.51542 -Imported From One Health,Misc,-99,Syringe bladder disposable 100ml_each_CMST,2214,1.0,1176.96474 -Imported From One Health,Misc,-99,Spectacles - 0.5_pair_CMST,2215,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 1.0_pair_CMST,2216,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 1.5_pair_CMST,2217,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 2.0_pair_CMST,2218,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 2.5_pair_CMST,2219,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 3.0_pair_CMST,2220,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 3.5_pair_CMST,2221,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 4.0_pair_CMST,2222,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles - 5.0_pair_CMST,2223,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles + 0.5_pair_CMST,2224,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles + 1.0_pair_CMST,2225,1.0,3141.73566 -Imported From One Health,Misc,-99,Spectacles + 1.5_pair_CMST,2226,1.0,3141.73566 -Imported From One Health,Misc,-99,"Brush, nail bristle, plastic back_each_CMST",2227,1.0,792.55428 -Imported From One Health,Misc,-99,"Can, douche, stainless steel 1.5L_each_CMST",2228,1.0,5505.1542 -Imported From One Health,Misc,-99,"Stove, primus no 5_each_CMST",2229,1.0,17279.53542 -Imported From One Health,Misc,-99,"Amylase test kit,15ml_7_CMST",2230,1.0,47016.85002 -Imported From One Health,Misc,-99,Autoclavable bags_100_CMST,2231,1.0,38218.0995 -Imported From One Health,Misc,-99,CLED medium_500g_CMST,2232,1.0,29618.66922 -Imported From One Health,Misc,-99,"Gama- Glutamyl transferase test kit,10ml_10_CMST",2233,1.0,2401.38192 -Imported From One Health,Misc,-99,Haemocytometer pipette rbc_each_CMST,2234,1.0,2353.92948 -Imported From One Health,Misc,-99,Haemocytometer pipette wbc_each_CMST,2235,1.0,5813.63076 -Imported From One Health,Misc,-99,"Clock, interval timing, 0 to 120 mins_each_CMST",2236,1.0,9031.30032 -Imported From One Health,Misc,-99,Dental unit complete system (Belmont)_each_CMST,2237,1.0,7348201.64316 -Imported From One Health,Misc,-99,Paper points assorted_50_CMST,2238,1.0,8945.87022 -Imported From One Health,Misc,-99,"Paper, articulating blue_pack_CMST",2239,1.0,8718.07566 -Imported From One Health,Misc,-99,Plastic instrument (Aesculap DE 6)_each_CMST,2240,1.0,11304.5478 -Imported From One Health,Misc,-99,Plastic instrument (black) (Aesculap DE 621)_each_CMST,2241,1.0,11304.5478 -Imported From One Health,Misc,-99,Plastic instrument (Frahm) ( Aesculap DF 50)_each_CMST,2242,1.0,17564.28576 -Imported From One Health,Misc,-99,Plastic instrument (Heidmann) (Aesculap DE 420)_each_CMST,2243,1.0,12566.9355 -Imported From One Health,Misc,-99,Plastic instrument (Hollenbach) (Aesculap DE 424)_each_CMST,2244,1.0,11546.58666 -Imported From One Health,Misc,-99,Plastic instrument (Hollenbach) (Aesculap DE 676)_each_CMST,2245,1.0,12566.9355 -Imported From One Health,Misc,-99,Posts assorted_pack_CMST,2246,1.0,157081.93494 -Imported From One Health,Misc,-99,Wax blue inlay (kerr)_pack_CMST,2247,1.0,9425.19984 -Imported From One Health,Misc,-99,Wax model cement (Dentisply)_pack_CMST,2248,1.0,9425.19984 -Imported From One Health,Misc,-99,Wax occlusal indicator (kerr)_pack_CMST,2249,1.0,35736.03558 -Imported From One Health,Misc,-99,Wax periphery sticks_pack_CMST,2250,1.0,7166.18952 -Imported From One Health,Misc,-99,Determine syphillis _100_CMST,2251,1.0,64794.69318 -Imported From One Health,Misc,-99,Glove surgeon's size 7½ sterile_pair_CMST,2252,1.0,156.6159 -Imported From One Health,Misc,-99,"Towels, paper_1000_CMST",2253,1.0,5842.10508 -Imported From One Health,Misc,-99,Morphine sulphate suspension 10mg/5ml_500ml_CMST,2254,1.0,1305.09918 -Imported From One Health,Misc,-99,"Nystatin pessaries 100,000 IU_each_CMST",2255,1.0,783.05808 -Imported From One Health,Misc,-99,Airway disposable (Portex) size 0_each_CMST,2256,1.0,484.07058 -Imported From One Health,Misc,-99,Airway disposable (Portex) size 00_each_CMST,2257,1.0,484.07058 -Imported From One Health,Misc,-99,Airway disposable (Portex) size 000_each_CMST,2258,1.0,484.07058 -Imported From One Health,Misc,-99,Airway disposable (Portex) size 1_each_CMST,2259,1.0,484.07058 -Imported From One Health,Misc,-99,Connection polythene straight assorted_36_CMST,2260,1.0,1570.86426 -Imported From One Health,Misc,-99,Glove postmortem size 7_pair_CMST,2261,1.0,783.05808 -Imported From One Health,Misc,-99,Glove postmortem size 7½_pair_CMST,2262,1.0,783.05808 -Imported From One Health,Misc,-99,Glove postmortem size 8_pair_CMST,2263,1.0,783.05808 -Imported From One Health,Misc,-99,Glove postmortem size 8½_pair_CMST,2264,1.0,783.05808 -Imported From One Health,Misc,-99,Connecting tube corrugated 9cm_each_CMST,2265,1.0,2828.511 -Imported From One Health,Misc,-99,"Cord, extension_each_CMST",2266,1.0,3924.79374 -Imported From One Health,Misc,-99,Blood grouping tilles-flat_each_CMST,2267,1.0,1699.00584 -Imported From One Health,Misc,-99,"Bottle, plastic plain with screw 1litre_each_CMST",2268,1.0,9372.9993 -Imported From One Health,Misc,-99,"Leischman's buffer ampoules,10ml_10_CMST",2269,1.0,12695.06994 -Imported From One Health,Misc,-99,Leischman's stain GRG_100g_CMST,2270,1.0,19704.6507 -Imported From One Health,Misc,-99,Composite sureful (Dentisply)_pack_CMST,2271,1.0,125664.59976 -Imported From One Health,Misc,-99,Ketac silver mamixcap (Espe)_pack_CMST,2272,1.0,376993.79214 -Imported From One Health,Misc,-99,"aciclovir 200 mg, dispersible_500_IDA",2273,1.0,8338.40616 -Imported From One Health,Misc,-99,"aciclovir 200 mg, dispersible, blister_50x10_IDA",2274,1.0,11760.14406 -Imported From One Health,Misc,-99,aciclovir 3% eye ointment 4.5g_10_IDA,2275,1.0,4484.79822 -Imported From One Health,Misc,-99,adhesive tape 1.25 cm x 5 m_10_IDA,2276,1.0,1300.35822 -Imported From One Health,Misc,-99,adhesive tape 10.0 cm x 5 m_2_IDA,2277,1.0,1736.96922 -Imported From One Health,Misc,-99,adhesive tape 2.5 cm x 5 m_8_IDA,2278,1.0,1490.1894 -Imported From One Health,Misc,-99,adhesive tape 5.0 cm x 5 m_4_IDA,2279,1.0,1736.96922 -Imported From One Health,Misc,-99,adhesive woundplaster 6.0 cm x 5 m_1_IDA,2280,1.0,1784.4288 -Imported From One Health,Misc,-99,"albendazole 200 mg/ 5 ml oral suspension, 10 ml_30_IDA",2281,1.0,4921.41636 -Imported From One Health,Misc,-99,amlodipine 5 mg_100_IDA,2282,1.0,2121.37968 -Imported From One Health,Misc,-99,"amoxicillin 125 mg/5 ml, pwd for suspension, 100ml_40_IDA",2283,1.0,528.36 -Imported From One Health,Misc,-99,"amoxicillin 1g + clavulanic acid 200mg, pwd f inj._10_IDA",2284,1.0,14844.93108 -Imported From One Health,Misc,-99,amoxicillin 500 mg_1000_IDA,2285,1.0,18456.50016 -Imported From One Health,Misc,-99,amoxicillin 500 mg_1000_IDA,2286,1.0,21156.86958 -Imported From One Health,Misc,-99,"amoxicillin 500 mg + clavulanic acid 125 mg, bl._10x5_IDA",2287,1.0,5832.61602 -Imported From One Health,Misc,-99,"amoxicillin 500 mg, blister_100x10_IDA",2288,1.0,20962.2903 -Imported From One Health,Misc,-99,anti-haemorrhoid suppositories (*a)_100_IDA,2289,1.0,10939.11546 -Imported From One Health,Misc,-99,"applicator stick, wood, with cotton tip, 15.0 cm_100_IDA",2290,1.0,336.95088 -Imported From One Health,Misc,-99,"apron utility, 120 cm, opaque, plastic, reusable_1_IDA",2291,1.0,1447.47792 -Imported From One Health,Misc,-99,"apron with neckband, opaque, plastic, disposable_1000_IDA",2292,1.0,75093.1293 -Imported From One Health,Misc,-99,"artemether 80 mg/ml, 1 ml, for injection_50_IDA",2293,1.0,11617.77246 -Imported From One Health,Misc,-99,"artesunate 100 mg + SP 525 mg, co-blister, adults_6+3_IDA",2294,1.0,768.82092 -Imported From One Health,Misc,-99,artesunate 100mg + amodiaquine 270mg tab_25X6 _IDA,2295,1.0,17787.33936 -Imported From One Health,Misc,-99,artesunate 100mg + amodiaquine 270mg tab_25X3 _IDA,2296,1.0,27089.14572 -Imported From One Health,Misc,-99,"bandage, hydrophilic 7.5 cm x 10 m, w.o.w._10_IDA",2297,1.0,1105.77894 -Imported From One Health,Misc,-99,Dacarabazine 200mg injection,2298,1.0,6819.36402 -Imported From One Health,Misc,-99,"barium sulphate BP/EP, for x-ray diagnosis_25_IDA",2299,1.0,41255.4198 -Imported From One Health,Misc,-99,"beclometasone or. Inh., 50 mcg/d, 200 dos (UN1950)_1_IDA",2300,1.0,1684.76868 -Imported From One Health,Misc,-99,"benzathine penicillin 1.2 miu, powder for inj._50_IDA",2301,1.0,7427.21364 -Imported From One Health,Misc,-99,blade for surgical knives size 10_100_IDA,2302,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 11_100_IDA,2303,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 12_100_IDA,2304,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 15_100_IDA,2305,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 20_100_IDA,2306,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 21_100_IDA,2307,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 23_100_IDA,2308,1.0,4147.84734 -Imported From One Health,Misc,-99,blade for surgical knives size 24_100_IDA,2309,1.0,4147.84734 -Imported From One Health,Misc,-99,"blanket, survival, disposable, 210 x 160 cm_1_IDA",2310,1.0,1589.84952 -Imported From One Health,Misc,-99,"bloodgroup anti A 200 tests, monoclonal, 10 ml(**)_10_IDA",2311,1.0,20193.46938 -Imported From One Health,Misc,-99,"bloodgroup anti A/B 200 tests, monoclonal,10ml(**)_10_IDA",2312,1.0,27131.8572 -Imported From One Health,Misc,-99,"bottle, plastic, 1000ml, wide neck, no screwcap_1_IDA",2313,1.0,915.94062 -Imported From One Health,Misc,-99,"bottle, plastic, 100ml (without screwcap, 872741)_1_IDA",2314,1.0,142.3716 -Imported From One Health,Misc,-99,bowl s.s. 300ml_1_IDA,2315,1.0,1400.01834 -Imported From One Health,Misc,-99,"bromhexine 0.8 mg/ml oral solution, 125 ml_25_IDA",2316,1.0,27426.0966 -Imported From One Health,Misc,-99,bromhexine HCl 8 mg_1000_IDA,2317,1.0,11086.23516 -Imported From One Health,Misc,-99,"bupivacaine HCl 0.5%, 20 ml, for injection_10_IDA",2318,1.0,11565.56478 -Imported From One Health,Misc,-99,"calamine lotion, 500 ml_1_IDA",2319,1.0,1589.84952 -Imported From One Health,Misc,-99,calcium lactate 300 mg_1000_IDA,2320,1.0,11617.77246 -Imported From One Health,Misc,-99,carbol fuchsin (Ziehl-n) dry powder UN2811_25_IDA,2321,1.0,45787.68474 -Imported From One Health,Misc,-99,catheter Foley ch.26 balloon 5-15ml sterile_10_IDA,2322,1.0,3379.02642 -Imported From One Health,Misc,-99,"catheter Foley, 3-way, balloon 30-50ml, disp.,Ch22_10_IDA",2323,1.0,14892.38352 -Imported From One Health,Misc,-99,"catheter Foley, 3-way, balloon 30-50ml,disp.,Ch 20_10_IDA",2324,1.0,14892.38352 -Imported From One Health,Misc,-99,"catheter Foley, balloon 3-5ml,sterile,disp., Ch 08_10_IDA",2325,1.0,12002.18292 -Imported From One Health,Misc,-99,"catheter Foley, balloon 3-5ml,sterile,disp., Ch 10_10_IDA",2326,1.0,12002.18292 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 12,sterile,disp._10_IDA",2327,1.0,3084.78702 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 14,sterile,disp._10_IDA",2328,1.0,3084.78702 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 16,sterile,disp._10_IDA",2329,1.0,3084.78702 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 18,sterile,disp._10_IDA",2330,1.0,3184.44714 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 20,sterile,disp._10_IDA",2331,1.0,3184.44714 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 22,sterile,disp._10_IDA",2332,1.0,3184.44714 -Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 24,sterile,disp._10_IDA",2333,1.0,3184.44714 -Imported From One Health,Misc,-99,"catheter nelaton ch.10 disp. plastic, sterile_100_IDA",2334,1.0,11038.78272 -Imported From One Health,Misc,-99,"catheter nelaton ch.12 disp. plastic, sterile_100_IDA",2335,1.0,11038.78272 -Imported From One Health,Misc,-99,"catheter nelaton ch.14 disp. plastic, sterile_100_IDA",2336,1.0,11475.39372 -Imported From One Health,Misc,-99,"cefixime 200 mg, blister_10x10_IDA",2337,1.0,9591.3048 -Imported From One Health,Misc,-99,"ceftriaxon 500 mg, powder for injection_10_IDA",2338,1.0,3568.8576 -Imported From One Health,Misc,-99,"centrifuge tube plastic 110x16mm, 10ml, conical_1_IDA",2339,1.0,52.20054 -Imported From One Health,Misc,-99,"chlorhexidine gluconate 20%, solution, 5 L(UN3082)_1_IDA",2340,1.0,32053.27356 -Imported From One Health,Misc,-99,"chlorhexidine gluconate 5% solution, 1 L_1_IDA",2341,1.0,3032.57934 -Imported From One Health,Misc,-99,"chloroq. phosphate 10 mg base/ml, oral sol., 60 ml_195_IDA",2342,1.0,80916.24912 -Imported From One Health,Misc,-99,"chloroxylenol 5% (4.5-5.5%) solution, 1 L_1_IDA",2343,1.0,8869.94346 -Imported From One Health,Misc,-99,"chlorphenamine maleate 10 mg/ml, 1 ml, injection_100_IDA",2344,1.0,4484.79822 -Imported From One Health,Misc,-99,"chlorpromazine HCl 50 mg/2 ml, for injection_100_IDA",2345,1.0,4964.12784 -Imported From One Health,Misc,-99,cimetidine 200 mg_500_IDA,2346,1.0,3132.23946 -Imported From One Health,Misc,-99,"cimetidine 200 mg/2 ml, for injection_10_IDA",2347,1.0,2648.16888 -Imported From One Health,Misc,-99,"ciprofloxacin 2 mg/ml, 100 ml infusion_10_IDA",2348,1.0,54799.9998 -Imported From One Health,Misc,-99,"container specimen glass wide neck + cap, 100ml_1_IDA",2349,1.0,484.07058 -Imported From One Health,Misc,-99,co-trimoxazole 100 mg + 20 mg_1000_IDA,2350,1.0,3032.57934 -Imported From One Health,Misc,-99,co-trimoxazole 400 mg + 80 mg_1000_IDA,2351,1.0,7953.9957 -Imported From One Health,Misc,-99,co-trimoxazole 800 mg + 160 mg_500_IDA,2352,1.0,8006.20338 -Imported From One Health,Misc,-99,"co-trimoxazole 800 mg + 160 mg, blister_5x10_IDA",2353,1.0,8817.73578 -Imported From One Health,Misc,-99,CPD-a bag 35 ml for 250 ml blood + taking set_10_IDA,2354,1.0,7327.54638 -Imported From One Health,Misc,-99,CPD-a bag 63 ml for 450 ml blood + taking set_10_IDA,2355,1.0,7617.04482 -Imported From One Health,Misc,-99,dapsone 100mg tab_28_IDA,2356,1.0,242.03886 -Imported From One Health,Misc,-99,dapsone 50 mg_1000_IDA,2357,1.0,5974.98762 -Imported From One Health,Misc,-99,"Determine chasebuffer, 2.5ml, for 100 tests_1_IDA",2358,1.0,6696.3561 -Imported From One Health,Misc,-99,"dexamethasone sodium phosphate 5 mg/ml, 1 ml, inj._100_IDA",2359,1.0,5732.94876 -Imported From One Health,Misc,-99,"dextrose 10% in water, 500 ml_20_IDA",2360,1.0,13928.98332 -Imported From One Health,Misc,-99,"dextrose 2.5% in sodium chloride 0.45%, 1000 ml_12_IDA",2361,1.0,10554.705 -Imported From One Health,Misc,-99,"dextrose 2.5% in sodium chloride 0.45%, 500 ml_20_IDA",2362,1.0,12965.58312 -Imported From One Health,Misc,-99,"dextrose 5% in water, 250 ml_30_IDA",2363,1.0,17208.34962 -Imported From One Health,Misc,-99,"dextrose 50%, 50 ml, for injection_20_IDA",2364,1.0,12528.96498 -Imported From One Health,Misc,-99,"diazepam 10 mg/2 ml, for injection (pt)_100_IDA",2365,1.0,127.2705 -Imported From One Health,Misc,-99,"digoxin 0.25 mg, blister_7x4_IDA",2366,1.0,1879.34796 -Imported From One Health,Misc,-99,"digoxin 0.5 mg/2 ml, for injection_100_IDA",2367,1.0,5927.52804 -Imported From One Health,Misc,-99,"dopamine HCl 200 mg/5 ml, for injection_100_IDA",2368,1.0,43476.46674 -Imported From One Health,Misc,-99,"drum for cotton wool&gauze, 15cm diam., 15cm high_1_IDA",2369,1.0,9159.43476 -Imported From One Health,Misc,-99,E.t. cuffed tube oral 3.5mm disposable_10_IDA,2370,1.0,24820.64634 -Imported From One Health,Misc,-99,E.t. cuffed tube oral 7.5mm disposable_10_IDA,2371,1.0,23235.53778 -Imported From One Health,Misc,-99,ear syringe 60ml rubber_1_IDA,2372,1.0,1105.77894 -Imported From One Health,Misc,-99,elastic bandage 10.0 cm x 2.5m (5.0 m stretched)_10_IDA,2373,1.0,3806.14836 -Imported From One Health,Misc,-99,"enalapril maleate 5 mg, blister_10x10_IDA",2374,1.0,526.7892 -Imported From One Health,Misc,-99,ergotamine 1 mg + caffeine 100 mg_30_IDA,2375,1.0,9496.38564 -Imported From One Health,Misc,-99,erythromycin 250mg/5ml pwd for susp 100ml_1_IDA,2376,1.0,1784.4288 -Imported From One Health,Misc,-99,"ethinylestradiol/levonorgestrel 0.03/0.15 mg, 28tb_200_IDA",2377,1.0,56200.011 -Imported From One Health,Misc,-99,"examination gloves, plastic, pre-powdered _100_IDA",2378,1.0,436.61814 -Imported From One Health,Misc,-99,"feeding tube, Ch 10, sterile, disp., 40 cm, luer _100_IDA",2379,1.0,6890.93538 -Imported From One Health,Misc,-99,"ferrous fumarate 100 mg/5 ml oral susp., 50 ml_25_IDA",2380,1.0,13444.91274 -Imported From One Health,Misc,-99,"ferrous fumarate 100 mg/5 ml oral suspension, 5 L_1_IDA",2381,1.0,20535.16836 -Imported From One Health,Misc,-99,ferrous sulphate 200 mg + folic acid 0.25 mg_1000_IDA,2382,1.0,1879.34796 -Imported From One Health,Misc,-99,ferrous sulphate 200 mg + folic acid 0.4 mg_1000_IDA,2383,1.0,1926.8004 -Imported From One Health,Misc,-99,"ferrous sulphate 200 mg, coated (65 mg iron)_1000_IDA",2384,1.0,1784.4288 -Imported From One Health,Misc,-99,field stain A_25_IDA,2385,1.0,9159.43476 -Imported From One Health,Misc,-99,field stain A_250_IDA,2386,1.0,10844.20344 -Imported From One Health,Misc,-99,filter set 515KS-LFS for DeVilbiss oxygen concentr_1_IDA,2387,1.0,34606.53042 -Imported From One Health,Misc,-99,fluconazole 100 mg_100_IDA,2388,1.0,4869.21582 -Imported From One Health,Misc,-99,"fluconazole 100 mg, blister_10x10_IDA",2389,1.0,5590.57716 -Imported From One Health,Misc,-99,fluconazole 150 mg_100_IDA,2390,1.0,5448.20556 -Imported From One Health,Misc,-99,fluconazole 50 mg_100_IDA,2391,1.0,3663.77676 -Imported From One Health,Misc,-99,"furosemide 20 mg/2 ml, for injection_100_IDA",2392,1.0,4726.83708 -Imported From One Health,Misc,-99,"ganciclovir 500 mg, powder for injection_1_IDA",2393,1.0,26989.4856 -Imported From One Health,Misc,-99,"gentamicin 20 mg/2 ml, for injection_100_IDA",2394,1.0,5538.37662 -Imported From One Health,Misc,-99,"giemsa solution, 500 ml, plastic bottle (UN1992)_2_IDA",2395,1.0,19277.52162 -Imported From One Health,Misc,-99,Glucose Control solution_1_IDA,2396,1.0,6311.94564 -Imported From One Health,Misc,-99,gram staining set 5 x 500 ml (UN1993)_1_IDA,2397,1.0,88680.41364 -Imported From One Health,Misc,-99,griseofulvin 500 mg_1000_IDA,2398,1.0,38749.62966 -Imported From One Health,Misc,-99,"griseofulvin 500 mg, blister_1000_IDA",2399,1.0,42024.24786 -Imported From One Health,Misc,-99,Guedel airway size 2_1_IDA,2400,1.0,2415.61908 -Imported From One Health,Misc,-99,"haloperidol 10 mg/ 5 ml, oral solution, 100 ml_1_IDA",2401,1.0,10165.54644 -Imported From One Health,Misc,-99,"haloperidol 5 mg/ml, 1 ml, for injection_100_IDA",2402,1.0,26462.6964 -Imported From One Health,Misc,-99,halothane 250 ml (in case of air shipment:UN2810)_6_IDA,2403,1.0,105836.55558 -Imported From One Health,Misc,-99,HIV 1 New Lav Blot I (Bio-Rad Laboratories) (**)_18_IDA,2404,1.0,346183.92102 -Imported From One Health,Misc,-99,HIV 1+2 Determine (*a)_100_IDA,2405,1.0,76825.35042 -Imported From One Health,Misc,-99,HIV 1+2+O Antibodies Elisa (Abbott) (*)_96_IDA,2406,1.0,130367.70348 -Imported From One Health,Misc,-99,HIV 2 New Lav Blot II (Bio-Rad Laboratories) (**)_18_IDA,2407,1.0,346183.92102 -Imported From One Health,Misc,-99,hydrochlorothiazide 50 mg_1000_IDA,2408,1.0,3084.78702 -Imported From One Health,Misc,-99,"hydrocortisone 100 mg (as sodium suc.), pwd f inj._50_IDA",2409,1.0,10939.11546 -Imported From One Health,Misc,-99,"hydrocortisone acetate 1% cream, 15 g_10_IDA",2410,1.0,3184.44714 -Imported From One Health,Misc,-99,"hyoscine butylbromide 20 mg/ml, 1 ml, for inj._100_IDA",2411,1.0,8196.03456 -Imported From One Health,Misc,-99,"ibuprofen 100mg/5ml oral suspension, 100ml_1_IDA",2412,1.0,963.4002 -Imported From One Health,Misc,-99,IEHK Antimalarials for Basic Unit (1.000 persons)_1_IDA,2413,1.0,759412.06362 -Imported From One Health,Misc,-99,IEHK Basic Unit without Antimalarials (1.000 pers)_1_IDA,2414,1.0,367924.52844 -Imported From One Health,Misc,-99,IEHK Suppl. Unit w/o PEP & Malaria (10.000 pers)_1_IDA,2415,1.0,3278223.40734 -Imported From One Health,Misc,-99,infusion giving set with air inlet and needle_4x100_IDA,2416,1.0,55426.44198 -Imported From One Health,Misc,-99,isoflurane 250 ml (in case of air shipment:UN2810)_6_IDA,2417,1.0,176060.46906 -Imported From One Health,Misc,-99,isoniazid 100mg tab_1000_IDA,2418,1.0,3326.81874 -Imported From One Health,Misc,-99,"IV placement unit 16G, sterile, disposable_50_IDA",2419,1.0,5927.52804 -Imported From One Health,Misc,-99,"IV placement unit 16G, w.inj.port&wings,ster,disp_50_IDA",2420,1.0,6169.5669 -Imported From One Health,Misc,-99,"IV placement unit 18G, sterile, disposable_50_IDA",2421,1.0,5927.52804 -Imported From One Health,Misc,-99,"IV placement unit 18G, w.inj.port&wings,ster,disp_50_IDA",2422,1.0,5538.37662 -Imported From One Health,Misc,-99,"IV placement unit 20G, sterile, disposable_50_IDA",2423,1.0,5305.82682 -Imported From One Health,Misc,-99,"IV placement unit 20G, w.inj.port&wings,ster,disp_50_IDA",2424,1.0,6169.5669 -Imported From One Health,Misc,-99,"IV placement unit 22G, sterile, disposable_50_IDA",2425,1.0,5927.52804 -Imported From One Health,Misc,-99,"IV placement unit 22G, w.inj.port&wings,ster,disp_50_IDA",2426,1.0,6169.5669 -Imported From One Health,Misc,-99,"IV placement unit 24G, sterile, disposable_50_IDA",2427,1.0,5732.94876 -Imported From One Health,Misc,-99,"IV placement unit 24G, w.inj.port&wings,ster,disp_50_IDA",2428,1.0,6653.64462 -Imported From One Health,Misc,-99,laryngoscope + 4 Blades (1 str. neonate) + spare bulb_1_IDA,2429,1.0,76777.89798 -Imported From One Health,Misc,-99,laryngoscope handle standard hook-on fitting_1_IDA,2430,1.0,14408.31294 -Imported From One Health,Misc,-99,"levodopa 250 mg + carbidopa 25 mg, blister_10x10_IDA",2431,1.0,5690.23728 -Imported From One Health,Misc,-99,"levothyroxine sodium 0.1 mg, blister_7x4_IDA",2432,1.0,1400.01834 -Imported From One Health,Misc,-99,"lidocaine HCl 2% + epinephrine dental, 1.8 ml_100_IDA",2433,1.0,25394.88798 -Imported From One Health,Misc,-99,"lidocaine HCl 2% 20 ml, for injection_10_IDA",2434,1.0,6117.36636 -Imported From One Health,Misc,-99,"Lugol's iodine for staining (1:2:100 aqueous), 1 L_1_IDA",2435,1.0,11665.23204 -Imported From One Health,Misc,-99,lysine acetylsalicylate 900mg injection_100_IDA,2436,1.0,39713.02986 -Imported From One Health,Misc,-99,"magnesium sulphate 50%, 20 ml, for injection_10_IDA",2437,1.0,6269.22702 -Imported From One Health,Misc,-99,"malaria P. falciparum + P. pan RDT, Parascreen_25_IDA",2438,1.0,21014.49798 -Imported From One Health,Misc,-99,"malaria P.falciparum+P.vivax+P.pan RDT, Paramax_25_IDA",2439,1.0,29158.32486 -Imported From One Health,Misc,-99,"mebendazole 100 mg, blister_60x10_IDA",2440,1.0,4000.72764 -Imported From One Health,Misc,-99,"mebendazole 100 mg/5 ml oral suspension, 100 ml_1_IDA",2441,1.0,526.7892 -Imported From One Health,Misc,-99,"mebendazole 100 mg/5 ml oral suspension, 30 ml_1_IDA",2442,1.0,270.51318 -Imported From One Health,Misc,-99,"metoclopramide HCl 10 mg/2 ml, for injection_100_IDA",2443,1.0,4627.17696 -Imported From One Health,Misc,-99,"metronidazole 200 mg/5 ml, pwd for susp., 100 ml_250_IDA",2444,1.0,166274.59212 -Imported From One Health,Misc,-99,metronidazole 250 mg_1000_IDA,2445,1.0,4242.7665 -Imported From One Health,Misc,-99,"metronidazole 250 mg, blister_100x10_IDA",2446,1.0,5395.99788 -Imported From One Health,Misc,-99,"metronidazole 500 mg, vaginal_1000_IDA",2447,1.0,33643.12308 -Imported From One Health,Misc,-99,"microscope slides 76x26mm, trop.pack., frosted end_5000_IDA",2448,1.0,176971.66872 -Imported From One Health,Misc,-99,"mosquito net 130 x 180 x 150 cm, LLIN, polyester_1_IDA",2449,1.0,4100.38776 -Imported From One Health,Misc,-99,"mosquito net 160 x 180 x 150 cm, LLIN, polyester_1_IDA",2450,1.0,4532.2578 -Imported From One Health,Misc,-99,"mosquito net 190 x 180 x 150 cm, LLIN, polyester_1_IDA",2451,1.0,4726.83708 -Imported From One Health,Misc,-99,"naloxone 0.4 mg/ml, 1 ml, for injection_10_IDA",2452,1.0,11038.78272 -Imported From One Health,Misc,-99,naproxen 250 mg_1000_IDA,2453,1.0,17450.38134 -Imported From One Health,Misc,-99,nifedipine retard 20 mg_100_IDA,2454,1.0,2311.218 -Imported From One Health,Misc,-99,nitrofurantoin 100 mg_1000_IDA,2455,1.0,6074.65488 -Imported From One Health,Misc,-99,nitroglycerine 0.5 mg (glyceryl trinitrate)_100_IDA,2456,1.0,5495.658 -Imported From One Health,Misc,-99,norethisterone 5 mg_30_IDA,2457,1.0,1926.8004 -Imported From One Health,Misc,-99,nystatin 500.000 iu oral coated_100_IDA,2458,1.0,6074.65488 -Imported From One Health,Misc,-99,oxygen tube ch.10 40cm disp._100_IDA,2459,1.0,15523.58094 -Imported From One Health,Misc,-99,"pancuronium bromide 4 mg/2 ml, for injection (**)_100_IDA",2460,1.0,62122.79808 -Imported From One Health,Misc,-99,paracetamol 120 mg suppositories (*a)_100_IDA,2461,1.0,6553.97736 -Imported From One Health,Misc,-99,"pentazocine 30 mg/ml, 1 ml, for injection (pt)_100_IDA",2462,1.0,9690.96492 -Imported From One Health,Misc,-99,phenobarbital 50 mg (pt)_1000_IDA,2463,1.0,3763.43688 -Imported From One Health,Misc,-99,phenoxymethylpenicillin 250 mg_1000_IDA,2464,1.0,13881.52374 -Imported From One Health,Misc,-99,phenytoin 250 mg/5 ml for injection_5_IDA,2465,1.0,7711.95684 -Imported From One Health,Misc,-99,"pipette, RBC, with tubing and mouthpiece_1_IDA",2466,1.0,2168.83926 -Imported From One Health,Misc,-99,"pipette, WBC, with tubing and mouthpiece_1_IDA",2467,1.0,2168.83926 -Imported From One Health,Misc,-99,plaster of Paris bandage 20.0 cm x 2.7 m_12_IDA,2468,1.0,5538.37662 -Imported From One Health,Misc,-99,podophyllotoxin 0.5% solution_3_IDA,2469,1.0,21882.97902 -Imported From One Health,Misc,-99,"procaine penici.3miu / benzylpenici.1miu, pwd inj._50_IDA",2470,1.0,14023.90248 -Imported From One Health,Misc,-99,procaine penicillin 3 MIU powder for inj_50_IDA,2471,1.0,13686.9516 -Imported From One Health,Misc,-99,"promethazine HCl 50 mg/2 ml, for injection_100_IDA",2472,1.0,30510.88362 -Imported From One Health,Misc,-99,"protamine sulphate 50 mg/5 ml, for injection_10_IDA",2473,1.0,18750.73956 -Imported From One Health,Misc,-99,"pvp iodine 7.5% surgical scrub (betadine), 500 ml_1_IDA",2474,1.0,11859.80418 -Imported From One Health,Misc,-99,pyrantel 250mg_1000_IDA,2475,1.0,26847.10686 -Imported From One Health,Misc,-99,"quinine sulphate 200 mg, film coated_1000_IDA",2476,1.0,26510.15598 -Imported From One Health,Misc,-99,"rabies vacc.(vero cells), pwd inj+solv. 0.5ml(***)_1_IDA",2477,1.0,18651.07944 -Imported From One Health,Misc,-99,"rack, for slides, expendable, for staining_1_IDA",2478,1.0,9059.77464 -Imported From One Health,Misc,-99,"rifampicin 300 mg + isoniazid 150 mg, coated_1000_IDA",2479,1.0,36680.45052 -Imported From One Health,Misc,-99,"Ringer's lactate (Hartmann's solution), 250 ml_30_IDA",2480,1.0,16871.3916 -Imported From One Health,Misc,-99,"Ringer's lactate (Hartmann's solution), 500 ml_20_IDA",2481,1.0,12723.54426 -Imported From One Health,Misc,-99,"ringer's lactate (Hartmann's solution), 500 ml_20_IDA",2482,1.0,8480.7849 -Imported From One Health,Misc,-99,salbutamol 2 mg_1000_IDA,2483,1.0,1300.35822 -Imported From One Health,Misc,-99,"salbutamol 2 mg/5 ml, oral solution, 100 ml_25_IDA",2484,1.0,16719.53094 -Imported From One Health,Misc,-99,"salbutamol respirator solution 5 mg/ml, 30 ml_1_IDA",2485,1.0,3421.7379 -Imported From One Health,Misc,-99,screwcap for plastic bottle 1000 ml _1_IDA,2486,1.0,185.09022 -Imported From One Health,Misc,-99,screwcap with inlay for plastic bottle 100 ml _1_IDA,2487,1.0,142.3716 -Imported From One Health,Misc,-99,sheeting plastic clear 90cm x 180cm Uni0361020_1_IDA,2488,1.0,1490.1894 -Imported From One Health,Misc,-99,"slidebox for 100 slides, 75 x 26mm, plastic_1_IDA",2489,1.0,12244.22178 -Imported From One Health,Misc,-99,sodium valproate 200mg enteric coated_100_IDA,2490,1.0,4000.72764 -Imported From One Health,Misc,-99,sodium valproate 500mg enteric coated_100_IDA,2491,1.0,8775.0243 -Imported From One Health,Misc,-99,spare wick for spirit lamp 150 ml_1_IDA,2492,1.0,963.4002 -Imported From One Health,Misc,-99,sphygmomanometer anaeroid for children_1_IDA,2493,1.0,4000.72764 -Imported From One Health,Misc,-99,"spirit lamp s.s., 150 ml, alcohol burner_1_IDA",2494,1.0,13107.96186 -Imported From One Health,Misc,-99,"spoon 5ml, plastic (graduated)_50_IDA",2495,1.0,3663.77676 -Imported From One Health,Misc,-99,"stethoscope, nurse type, lightweight, single cup_1_IDA",2496,1.0,1542.38994 -Imported From One Health,Misc,-99,"stethoscope,Littman type,lightwght,dble cup,spares_1_IDA",2497,1.0,1542.38994 -Imported From One Health,Misc,-99,"stomach tube, Ch 10, sterile, disp.,125cm(06SGx03)_25_IDA",2498,1.0,3853.60794 -Imported From One Health,Misc,-99,"stomach tube, Ch 12, sterile, disp.,125cm(06SGx03)_25_IDA",2499,1.0,3853.60794 -Imported From One Health,Misc,-99,"stomach tube, Ch 12, sterile, disposable, 80 cm_100_IDA",2500,1.0,14460.52062 -Imported From One Health,Misc,-99,"stomach tube, Ch 14, sterile, disposable, 80 cm_100_IDA",2501,1.0,14460.52062 -Imported From One Health,Misc,-99,"stomach tube, Ch 16, sterile, disposable, 80 cm_100_IDA",2502,1.0,14460.52062 -Imported From One Health,Misc,-99,"streptomycin 1 g, powder for injection_50_IDA",2503,1.0,8480.7849 -Imported From One Health,Misc,-99,"suction tube no. 08, sterile, disposable_100_IDA",2504,1.0,11518.1052 -Imported From One Health,Misc,-99,"suction tube no. 10, sterile, disposable_100_IDA",2505,1.0,11518.1052 -Imported From One Health,Misc,-99,"suction tube no. 14, sterile, disposable_100_IDA",2506,1.0,11518.1052 -Imported From One Health,Misc,-99,"suction tube no. 16, sterile, disposable_100_IDA",2507,1.0,11518.1052 -Imported From One Health,Misc,-99,sulfadiazine 500mg tab_56_IDA,2508,1.0,1400.01834 -Imported From One Health,Misc,-99,supplementary reagents kit for Enzygnost TMB (***)_1152_IDA,2509,1.0,135431.49858 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile pwd-free, size 6_8X50_IDA",2510,1.0,91428.24264 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pre-pwd, size 6.0_8x50_IDA",2511,1.0,72051.05376 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pre-pwd, size 6.5_8x50_IDA",2512,1.0,72051.05376 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 6.5_8x50_IDA",2513,1.0,88049.22336 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 7.0_8x50_IDA",2514,1.0,91428.24264 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 7.5_8x50_IDA",2515,1.0,88049.22336 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 8.0_8x50_IDA",2516,1.0,88049.22336 -Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 8.5_8x50_IDA",2517,1.0,88049.22336 -Imported From One Health,Misc,-99,"surgical scrub brush, sterilisable, plastic_1_IDA",2518,1.0,1015.60788 -Imported From One Health,Misc,-99,"suture catgut chromic (0) 1 x 150 cm, S114H_36_IDA",2519,1.0,12775.75194 -Imported From One Health,Misc,-99,suture catgut chromic (1) 1 x 150 cm_36_IDA,2520,1.0,13829.3232 -Imported From One Health,Misc,-99,suture catgut chromic (2) 1 x 150 cm_36_IDA,2521,1.0,14602.89222 -Imported From One Health,Misc,-99,"suture catgut chromic (2/0) 1 x 150 cm, S113H_36_IDA",2522,1.0,12723.54426 -Imported From One Health,Misc,-99,"suture catgut chromic (3/0) 1 x 150 cm, S112H_36_IDA",2523,1.0,12723.54426 -Imported From One Health,Misc,-99,"suture needles, assorted sizes, cutting_12_IDA",2524,1.0,526.7892 -Imported From One Health,Misc,-99,"suture needles, assorted sizes, round body_12_IDA",2525,1.0,578.98974 -Imported From One Health,Misc,-99,"suture polyester (0) 150 cm, non-abs., braided_36_IDA",2526,1.0,12438.80106 -Imported From One Health,Misc,-99,"suture polyester (2/0) 150 cm, non-abs., braided_36_IDA",2527,1.0,12196.7622 -Imported From One Health,Misc,-99,"suture polyester (3/0) 150 cm, non-abs., braided_36_IDA",2528,1.0,12196.7622 -Imported From One Health,Misc,-99,"suture silk (2/0) 45 cm + 3/8ct ndl 24.5 mm, 7633H_36_IDA",2529,1.0,13829.3232 -Imported From One Health,Misc,-99,"suture synth.abs.(1) 90cm+1/2ct ndl 36.5mm, V519H_36_IDA",2530,1.0,33880.42098 -Imported From One Health,Misc,-99,"suture synth.abs.(2/0) 70cm+3/8ct ndl 30mm, V586H_36_IDA",2531,1.0,30985.46514 -Imported From One Health,Misc,-99,"suture synthetic absorbable (1) 2 x 70 cm, V627H_36_IDA",2532,1.0,33401.09136 -Imported From One Health,Misc,-99,"suture Vicryl® (0) 70cm + 1/2 rb ndl 40mm, V352H_36_IDA",2533,1.0,116581.0989 -Imported From One Health,Misc,-99,"suture Vicryl® (1) 70cm + 1/2 rb ndl 48mm, V365H_36_IDA",2534,1.0,116581.0989 -Imported From One Health,Misc,-99,"suture Vicryl® (1) 90cm + 1/2 ct ndl 36.5mm, V519H_36_IDA",2535,1.0,149792.35194 -Imported From One Health,Misc,-99,"suture Vicryl® (2/0) 70cm + 3/8 ct ndl 30mm, V586H_36_IDA",2536,1.0,85785.46494 -Imported From One Health,Misc,-99,"suture Vicryl® (3/0) 45cm+3/8ct ndl 18.5mm, V393H_36_IDA",2537,1.0,85785.46494 -Imported From One Health,Misc,-99,"suture Vicryl® (3/0) 70cm+1/2rb ndl 17.5mm, V305H_36_IDA",2538,1.0,101351.75736 -Imported From One Health,Misc,-99,"suture Vicrylâ (0) 2 x 70 cm, V626H_24_IDA",2539,1.0,44582.24568 -Imported From One Health,Misc,-99,"suture Vicrylâ (1) 2 x 70 cm, V627H_36_IDA",2540,1.0,68292.36498 -Imported From One Health,Misc,-99,"suture Vicrylâ (2/0) 2 x 70 cm, V625H_24_IDA",2541,1.0,42940.18848 -Imported From One Health,Misc,-99,"suture Vicrylâ (3/0) 2 x 70 cm, V624H_24_IDA",2542,1.0,55957.97928 -Imported From One Health,Misc,-99,"suxamethonium chloride 100 mg/2 ml, inj.(**)_100_IDA",2543,1.0,36243.83238 -Imported From One Health,Misc,-99,"syringe 60 ml catheter tip+luer adapt, disp_100_IDA",2544,1.0,77641.63092 -Imported From One Health,Misc,-99,"syringe luer 1 ml sterile, disp., without needle_100_IDA",2545,1.0,5305.82682 -Imported From One Health,Misc,-99,"syringe luer 10 ml sterile, disp., without needle_100_IDA",2546,1.0,3953.26806 -Imported From One Health,Misc,-99,"syringe luer 10 ml, with bypacked needle 21Gx 1.5""_100_IDA",2547,1.0,5111.24754 -Imported From One Health,Misc,-99,"syringe luer 2 ml sterile, disp., without needle_100_IDA",2548,1.0,2069.17914 -Imported From One Health,Misc,-99,"syringe luer 2 ml, with bypacked ndle 23G x 1.1/4""_100_IDA",2549,1.0,3379.02642 -Imported From One Health,Misc,-99,"syringe luer 2ml, with bypacked needle, 21G x 1.5""_100_IDA",2550,1.0,3379.02642 -Imported From One Health,Misc,-99,"syringe luer 5 ml sterile, disp., without needle_100_IDA",2551,1.0,2747.829 -Imported From One Health,Misc,-99,"syringe luer 5 ml, with bypacked needle 21G x 1.5""_100_IDA",2552,1.0,3853.60794 -Imported From One Health,Misc,-99,"syringe luer 5 ml, with bypacked needle 22Gx1.1/4""_100_IDA",2553,1.0,3853.60794 -Imported From One Health,Misc,-99,syringes (double valve) +cannulas_1_IDA,2554,1.0,192537.96114 -Imported From One Health,Misc,-99,"tabletbags resealable, 80 x 100 mm, with pictogram_500_IDA",2555,1.0,1205.43906 -Imported From One Health,Misc,-99,tamoxifen 20mg_30_IDA,2556,1.0,1784.4288 -Imported From One Health,Misc,-99,"tetracycline HCl 3% skin ointment, 15 g_10_IDA",2557,1.0,2168.83926 -Imported From One Health,Misc,-99,"thiopental sodium 1 gram, powder for injection_50_IDA",2558,1.0,50841.98364 -Imported From One Health,Misc,-99,"thiopental sodium 500 mg, powder for injection_50_IDA",2559,1.0,36291.29196 -Imported From One Health,Misc,-99,timer 60 min. (with signal)_1_IDA,2560,1.0,7517.37756 -Imported From One Health,Misc,-99,tinidazole 500 mg_100_IDA,2561,1.0,1926.8004 -Imported From One Health,Misc,-99,"toilet soap in wrapper, 100 g_100_IDA",2562,1.0,17877.51042 -Imported From One Health,Misc,-99,"tourniquet (arm), cotton white, with buckle_1_IDA",2563,1.0,270.51318 -Imported From One Health,Misc,-99,"tramadol HCl 100 mg/2 ml, for injection_100_IDA",2564,1.0,6606.18504 -Imported From One Health,Misc,-99,"tuberculin (ppd) 10 iu/0.1 ml, 1.5 ml pwd inj.(**)_1_IDA",2565,1.0,21593.48772 -Imported From One Health,Misc,-99,"turk solution, acet. acid/gentianviolet, 100 ml_1_IDA",2566,1.0,7517.37756 -Imported From One Health,Misc,-99,"umbilical cord tie, 3 mm non-sterile, 100 m_1_IDA",2567,1.0,1589.84952 -Imported From One Health,Misc,-99,urine collecting bags pediatric 100ml_100_IDA,2568,1.0,9301.80636 -Imported From One Health,Misc,-99,"Vacutainer® blood coll.tube 4ml, Li-heparin, green_100_IDA",2569,1.0,10217.75412 -Imported From One Health,Misc,-99,"Vacutainer® blood coll.tube 4ml, plain silica, red_100_IDA",2570,1.0,9975.71526 -Imported From One Health,Misc,-99,"Vacutainer® tubes holder for 5, 10 & 20 ml, disp._1000_IDA",2571,1.0,24725.72718 -Imported From One Health,Misc,-99,valganciclovir 450 mg_60_IDA,2572,1.0,1439103.81384 -Imported From One Health,Misc,-99,"VDRL carbon antigen (vd24), 5 ml (**)_1_IDA",2573,1.0,18261.92088 -Imported From One Health,Misc,-99,"vecuronium bromide 4 mg, powder for injection_25_IDA",2574,1.0,36243.83238 -Imported From One Health,Misc,-99,vincristine sulphate 1mg/ml inj **_5_IDA,2575,1.0,35569.93062 -Imported From One Health,Misc,-99,"vitamin A (retinol) 50.000 iu, gelcapsules_1000_IDA",2576,1.0,13686.9516 -Imported From One Health,Misc,-99,"vitamin B compound, 2 ml, for injection_100_IDA",2577,1.0,19661.93922 -Imported From One Health,Misc,-99,"vitamin B12 (cyanocobalamine) 1 mg/ml, 1 ml, inj._100_IDA",2578,1.0,5253.62628 -Imported From One Health,Misc,-99,vitamin B-6 100mg/2ml inj (pyridoxine HCl)_100_IDA,2579,1.0,5348.5383 -Imported From One Health,Misc,-99,"vitamin K1 (phytomenadione) 1 mg/ml, 1 ml, inj._100_IDA",2580,1.0,18840.91062 -Imported From One Health,Misc,-99,"vitamin K1(phytomenadione) 10 mg/ml, 1ml, inj.(*a)_100_IDA",2581,1.0,24198.94512 -Imported From One Health,Misc,-99,"washbottle plastic 250 ml, complete squeeze type_1_IDA",2582,1.0,1300.35822 -Imported From One Health,Misc,-99,"waterbag foldable, 20 L, strong quality with tap_1_IDA",2583,1.0,3032.57934 -Imported From One Health,Misc,-99,x-ray fixer powder for 22.5 L ( for manual use)_3.3_IDA,2584,1.0,9638.76438 -Imported From One Health,Misc,-99,"zinc oxide ointment 10%, 100 g_10_IDA",2585,1.0,7132.9671 -Imported From One Health,Misc,-99,"zinc oxide ointment 10%, 800 g_1_IDA",2586,1.0,6553.97736 -Imported From One Health,Misc,-99,Ethambutol400mg/isoniazid 150mg (Fatol®)_1000_CMST,2587,1.0,14101.5 -Imported From One Health,Misc,-99,Rifampicin 150mg/isoniazid 100mg tablet (Rifinah®)_1000_CMST,2588,1.0,16022.16 -Imported From One Health,Misc,-99,Amikacin sulphate 1g inj_Each_CMST,2589,1.0,778.26 -Imported From One Health,Misc,-99,Microscope slides-frosted end(Tropical packaging)_50_CMST,2590,1.0,4241.16 -Imported From One Health,Misc,-99,Microscope slides-frosted end(Tropical packaging)_50_CMST,2591,1.0,12280.8 -Imported From One Health,Misc,-99,Isoniazid 100mg _1000_CMST,2592,1.0,5191.92954 -Imported From One Health,Misc,-99,Rifampicin 150mg/isoniazid 75mg _672_CMST,2593,1.0,17057.46 -Imported From One Health,Misc,-99,Rifampicin 60 mg/isoniazid 30mg _672_CMST,2594,1.0,6340.32 -Imported From One Health,Misc,-99,Streptomycin Suphate injection 1g_Each_CMST,2595,1.0,13830.18 -Imported From One Health,Misc,-99,"Water for injection, 5ml_Each_CMST",2596,1.0,28.56 -Imported From One Health,Misc,-99,"Syringe, disposable 2ml, hypoluer with 23g needle_each_CMST",2597,1.0,42.84 -Imported From One Health,Misc,-99,"Syringe, disposable 5ml, hypoluer with 21g needle_each_CMST",2598,1.0,49.98 -Imported From One Health,Misc,-99,Ethinylestradiol 0.03mg + levonorgestrel 0.15mg_3cycles_CMST,2599,1.0,364.14 -Imported From One Health,Misc,-99,Copper containing IUCD (Copper T®)_Each_CMST,2600,1.0,414.12 -Imported From One Health,Misc,-99,Male condoms with spermicide_Box of 100_CMST,2601,1.0,2049.18 -Imported From One Health,Misc,-99,"Medroxyprogesterone acetate injection 150mg/mL, 1mL vial (Depo Provera®) with 2ml autodestruct syringe 22G needle_each_CMST",2602,1.0,785.4 -Imported From One Health,Misc,-99,Metronidazole 250mg _1000_CMST,2603,1.0,5654.88 -Imported From One Health,Misc,-99,"Syringes, disposable, 10ml with 21G needle_Each_CMST",2604,1.0,42.84 -Imported From One Health,Misc,-99,"Syringes, disposable, autodestruct, 10ml with 21G needle_Each_CMST",2605,1.0,357.0 -Imported From One Health,Misc,-99,"Benzylpenicillin 1g (1MU), PFR_Each_CMST",2606,1.0,42.84 -Imported From One Health,Misc,-99,"Chloramphenicol succinate 1g, PFR_Each_CMST",2607,1.0,107.1 -Imported From One Health,Misc,-99,"Gentamicin 10mg/ml, 2ml_Each_CMST",2608,1.0,692.58 -Imported From One Health,Misc,-99,Water for injections 10ml_Each_CMST,2609,1.0,435.54 -Imported From One Health,Misc,-99,Amoxycillin 125mg/5ml suspension_100ml_CMST,2610,1.0,571.2 -Imported From One Health,Misc,-99,"Syringes, hypoluer, 5ml 21g, disposable_Each_CMST",2611,1.0,7.14 -Imported From One Health,Misc,-99,"Syringes, hypoluer, 2ml 23g, disposable_Each_CMST",2612,1.0,21.42 -Imported From One Health,Misc,-99,"Syringes, hypoluer, 2ml 25g, disposable_Each_CMST",2613,1.0,21.42 -Imported From One Health,Misc,-99,Albendazole 400mg_100.005320936485_CMST,2614,1.0,428.4 -Imported From One Health,Misc,-99,Co-trimoxazole 120mg_100_CMST,2615,1.0,549.78 -Imported From One Health,Misc,-99,Co-trimoxazole 480mg_120_CMST,2616,1.0,185.64 -Imported From One Health,Misc,-99,Co-trimoxazole 480mg_60_CMST,2617,1.0,556.92 -Imported From One Health,Misc,-99,Co-trimoxazole 480mg_1000_CMST,2618,1.0,1063.86 -Imported From One Health,Misc,-99,Lamivudine 150 mg (3TC) + Zidovudine 300mg AZT_60_CMST,2619,1.0,74.27028 -Imported From One Health,Misc,-99,Lamivudine 150mg + Stavudine 30mg (Dual comb.)_60_CMST,2620,1.0,27988.8 -Imported From One Health,Misc,-99,Lamivudine 150mg + Stavudine 30mg + Nevirapine 200mg _x000B_ (Triple Combination)_60_CMST,2621,1.0,27988.8 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg,30x6_180_CMST",2622,1.0,8717.94 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg,30x12_360_CMST",2623,1.0,17435.88 -Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",2624,1.0,26153.82 -Imported From One Health,Misc,-99,Nevirapine 200mg_60_CMST,2625,1.0,109820.34 -Imported From One Health,Misc,-99,Pyridoxine 25mg_1000_CMST,2626,1.0,9267.72 -Imported From One Health,Misc,-99,Zidovudine 300 mg_60_CMST,2627,1.0,5819.1 -Imported From One Health,Misc,-99,Zidovudine 300 mg + Lamivudine 150 (3TC) + Nevirapine 200mg _60_CMST,2628,1.0,8932.14 -Imported From One Health,Misc,-99,"Ceftriaxone 500mg, PFR_Each_CMST",2629,1.0,235.62 -Imported From One Health,Misc,-99,"Dextrose 50%, 20ml_Each_CMST",2630,1.0,903.58842 -Imported From One Health,Misc,-99,Nevirapine 10mg/ml oral solution_240ml_CMST,2631,1.0,29345.4 -Imported From One Health,Misc,-99,Zidovudine 10mg/ml oral solution_100ml_CMST,2632,1.0,1078.14 -Imported From One Health,Misc,-99,Bioline HIV 1/2 test kit _30_CMST,2633,1.0,8832.18 -Imported From One Health,Misc,-99,Determine HIV 1/2 test kit_100 tests_CMST,2634,1.0,49501.62 -Imported From One Health,Misc,-99,Unigold HIV test kit_20 tests_CMST,2635,1.0,50265.6 -Imported From One Health,Misc,-99,Apron laboratory sleeves_50_CMST,2636,1.0,66223.5 -Imported From One Health,Misc,-99,"Exacta-med oral dispensers 1ml,pack with blue seal caps_100_CMST",2637,1.0,24468.78 -Imported From One Health,Misc,-99,"Glove disposable latex, large_100_CMST",2638,1.0,1956.36 -Imported From One Health,Misc,-99,Haemacue glucose HB 301 machine_each_CMST,2639,1.0,375416.28054 -Imported From One Health,Misc,-99,Haemacue control HB 201 Machine_50_CMST,2640,1.0,509310.48 -Imported From One Health,Misc,-99,Haemacue HB 301_50_CMST,2641,1.0,48545.20986 -Imported From One Health,Misc,-99,Vacuette Blood Collection set (adult)_100_CMST,2642,1.0,14108.64 -Imported From One Health,Misc,-99,Vacuette Blood Collection set (pead)_100_CMST,2643,1.0,14108.64 -Imported From One Health,Misc,-99,Adult First line 1A d4T-based,2644,1.0,41927.24382 -Imported From One Health,Misc,-99,Adult First line 3A d4T-based,2645,1.0,54985.98252 -Imported From One Health,Misc,-99,Adult First line 2A AZT-based,2646,1.0,80255.87052 -Imported From One Health,Misc,-99,Adult First line 4A AZT-based,2647,1.0,90971.60394 -Imported From One Health,Misc,-99,Adult First line 5A TDF-based,2648,1.0,104310.25206 -Imported From One Health,Misc,-99,Adult First line 6A TDF-based,2649,1.0,69572.17428 -Imported From One Health,Misc,-99,Adult Second line 7A ,2650,1.0,263414.57058 -Imported From One Health,Misc,-99,Adult Second line 8A ,2651,1.0,275793.61698 -Imported From One Health,Misc,-99,Paediatric First line 1P d4T-based,2652,1.0,57456.99372 -Imported From One Health,Misc,-99,Paediatric First line 3P d4T-based,2653,1.0,124846.0416 -Imported From One Health,Misc,-99,Paediatric First line 2P AZT-based,2654,1.0,103146.71766 -Imported From One Health,Misc,-99,Paediatric First line 4P AZT-based,2655,1.0,150995.56332 -Imported From One Health,Misc,-99,Paediatric Second line 9P ,2656,1.0,635649.63126 -Imported From One Health,Misc,-99,Doxorubicin (Adreamycin) 50mg Injection,2657,1.0,9128.49 -Imported From One Health,Misc,-99,Cyclophosphamide 500mg Injection,2658,1.0,1612.79748 -Imported From One Health,Misc,-99,Paclitaxel 300mg Injection,2659,1.0,48051.29322 -Imported From One Health,Misc,-99,PackTeeth,2660,1.0,0.0 -Imported From One Health,Misc,-99,Average ART cost,2661,1.0,0.0 -Imported From One Health,Misc,-99,"AlerDeterm.HIV1/2Ag/AbCombo,Wbkit/100",2662,1.0,963.9 -Imported From One Health,Misc,-99,"Humasis Malaria P.f Antigen, kit/25",2663,1.0,378.42 -Imported From One Health,Misc,-99,"Proca,benz.peni.pdr/inj 1MIU vl/BOX-50",2664,1.0,12159.42 -Imported From One Health,Misc,-99,"Tube Feeding, CH08, L40cm, ster,disp, 50 per box",2665,1.0,142.8 -Imported From One Health,Misc,-99,"Syringe, feeeding, 50ml, catheter tips, ster 50 per box",2666,1.0,257.04 -Imported From One Health,Misc,-99,"Soap, Toilet, bar, 100-110g, wrapped (36 per box)",2667,1.0,128.52 -Imported From One Health,Misc,-99,"Plaster, elastic adhesive 7.5cm x 5m",2668,1.0,0.0 -Added by JC,Misc,-99,"Forceps, obstetric",2669,1.0,1.0 -Added by JC,Misc,-99,"Vacuum, obstetric",2670,1.0,1.0 -Added by TM,Misc,-99,First-line ART regimen: adult,2671,1.0,1.0 -Added by TM,Misc,-99,First line ART regimen: older child,2672,1.0,1.0 -Added by TM,Misc,-99,First line ART regimen: young child,2673,1.0,1.0 -Added by TM,Misc,-99,Pre-exposure prophlaxis for HIV,2674,1.0,1.0 -Added by SM (Recommended by TM),Isoniazid preventative therapy for HIV+ no TB,82,Isoniazid/Rifapentine,2678,1.0,1.0 -Added by SM (Recommended by EJ),Misc,-99,Cystoscope,285,1.0, -Added by SM (Recommended by EJ),Misc,-99,Endoscope,280,1.0, -Added by SM (Recommended by EJ),Misc,-99,Prostate specific antigen test,281,1.0, +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,"Prednisolone, tablet, 5 mg",341,54.6,59.99742 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Blood glucose level test,216,2,685.99692 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Cholesterol test,217,2,685.99692 +Non-communicable diseases,Treatment for those with cerebrovascular disease and post-stroke_ No Diabetes,163,Urine analysis,47,2,627.9987 +Imported From One Health,Misc,-99,"Artemether + Lumefantrine, tablets, 20 + 120 mg, 6 x 1 blister",1000,1,99.66012 +Imported From One Health,Misc,-99,Artemether 20 mg/ml injection/1 ml,1001,1,484.07058 +Imported From One Health,Misc,-99,"Artesunate + Amodiaquine, tablets, 50 mg + 153 mg, 3 + 3 blister",1002,1,218.3055 +Imported From One Health,Misc,-99,"Artesunate + SP, tablets, 50 mg + 500 mg + 25 mg, 3 + 1 blister",1003,1,393.89952 +Imported From One Health,Misc,-99,Bacteriuria test,1004,1,85.42296 +Imported From One Health,Misc,-99,"Betamethasone, 12 mg injection",1005,1,10279.45086 +Imported From One Health,Misc,-99,Blood culture,1006,1,0 +Imported From One Health,Misc,-99,"Calcium, tablet, 600 mg",1007,1,14.23716 +Imported From One Health,Misc,-99,"Ceftriaxone, powder for injection, 250 ml vial",1008,1,207.10998 +Imported From One Health,Misc,-99,"Chloramphenicol, powder/inj, 1 g vial",1009,1,930.17778 +Imported From One Health,Misc,-99,"Chloramphenicol, oral suspension 125 mg/5 ml, 60 ml bottle",1010,1,484.07058 +Imported From One Health,Misc,-99,"Ciprofloxacin, tablet, 250 mg",1011,1,16.20066 +Imported From One Health,Misc,-99,"Condom, female",1012,1,427.12194 +Imported From One Health,Misc,-99,Depot-Medroxyprogesterone Acetate 25 mg + estradiol cypionate 5 mg - 1 monthly,1013,1,0 +Imported From One Health,Misc,-99,"Desogestrel 0.15 mg + Ethinyl estradiol 30 mcg, cycle",1014,1,0 +Imported From One Health,Misc,-99,Dietary supplements (country-specific),1015,1,0 +Imported From One Health,Misc,-99,"Digoxin, tabcap, 250 mcg",1016,1,9.48906 +Imported From One Health,Misc,-99,DTP vaccine,1017,1,99.66012 +Imported From One Health,Misc,-99,Drug kit for C-section and complex deliveries,1018,1,1434505.118 +Imported From One Health,Misc,-99,"Ergometrine, tablet, 0.2 mg",1019,1,14.23716 +Imported From One Health,Misc,-99,"Ethambutol, tab-cap, 100 mg",1020,1,9.48906 +Imported From One Health,Misc,-99,"Ethambutol, tab-cap, 400 mg",1021,1,28.47432 +Imported From One Health,Misc,-99,"F-100 therapeutic diet, sachet, 456 g for 2.4 liters liquid diet",1022,1,455.59626 +Imported From One Health,Misc,-99,"F-100 therapeutic milk,sachet, 456 g",1023,1,1414.2555 +Imported From One Health,Misc,-99,"F-75 therapeutic diet, sachet, 410 g for 2.4 liters liquid diet",1024,1,346.44708 +Imported From One Health,Misc,-99,"Folic acid, tablet, 5 mg",1025,1,4.7481 +Imported From One Health,Misc,-99,"Furosemide, tablets, 40 mg",1026,1,4.7481 +Imported From One Health,Misc,-99,"Gauze pad, 10 x 10 cm, non-sterile",1027,1,23.72622 +Imported From One Health,Misc,-99,Gentamicin inj 10 mg/ml 2 ml amp,1028,1,90.17106 +Imported From One Health,Misc,-99,"Glucose inj 5 %, 500 ml with giving set",1029,1,688.14606 +Imported From One Health,Misc,-99,"Glucose inj 5 %, 500 ml with giving set",1030,1,683.39796 +Imported From One Health,Misc,-99,Hib vaccine,1031,1,0 +Imported From One Health,Misc,-99,"Injection supplies (cotton, tape, etc)",1032,1,37.96338 +Imported From One Health,Misc,-99,"IUD, Multiload 375 Standard/SL",1033,1,991.87452 +Imported From One Health,Misc,-99,"Levonorgestrel 0.03 mg, cycle of 28 pills",1034,1,199.32738 +Imported From One Health,Misc,-99,"Levonorgestrel 0.05/0.075/0.125 mg +Ethinyl estradiol 30/40/30 mcg, cycle",1035,1,151.8678 +Imported From One Health,Misc,-99,"Levonorgestrel 0.15/0.2 mg + Ethinyl estradiol 30/40 mcg, cycle",1036,1,0 +Imported From One Health,Misc,-99,"Lynestrenol 0.5 mg, cycle",1037,1,802.04334 +Imported From One Health,Misc,-99,"Mebendazole, chewable tablet, 100 mg",1038,1,901.70346 +Imported From One Health,Misc,-99,"Metformin, tablet, 500 mg",1039,1,4.7481 +Imported From One Health,Misc,-99,"Metronidazole, tablet, 200 mg",1040,1,4.7481 +Imported From One Health,Misc,-99,"Micronutrient, film-coated tablet",1041,1,9.48906 +Imported From One Health,Misc,-99,Microscopy,1042,1,0 +Imported From One Health,Misc,-99,Mucus extractor,1043,1,683.39796 +Imported From One Health,Misc,-99,"Multiple micronutrient powder, sachet",1044,1,14.23716 +Imported From One Health,Misc,-99,"Nasogastric tube, CH12, 125 cm, disposable",1045,1,294.2394 +Imported From One Health,Misc,-99,Nitrite test,1046,1,0 +Imported From One Health,Misc,-99,FBC,1047,1,1043.60382 +Imported From One Health,Misc,-99,Norethisterone enanthate 200 mg - 2 monthly,1048,1,830.51766 +Imported From One Health,Misc,-99,Norethisterone enanthate 200 mg + 5 mg estradiol valerate - 1 monthly,1049,1,607.46406 +Imported From One Health,Misc,-99,"Norgestrel 0.30 mcg + Ethinyl estradiol 30 mcg (Lofemenal), cycle",1050,1,175.59402 +Imported From One Health,Misc,-99,"Nutrition Kit for therapeutic feeding, clinic based",1051,1,13326.26736 +Imported From One Health,Misc,-99,Partograph,1052,1,0 +Imported From One Health,Misc,-99,"Pyrazinamide, tablets, 500 mg",1053,1,28.47432 +Imported From One Health,Misc,-99,"Quinine, injection, 300 mg/ml, 2 ml ampoule",1054,1,194.57928 +Imported From One Health,Misc,-99,"ReSoMal, 42 g sachet for 1 liter",1055,1,271.32 +Imported From One Health,Misc,-99,"Rifampicin + Isoniazid + Pyrazinamide, 150 mg + 75 mg + 400 mg, tablet",1056,1,33.22242 +Imported From One Health,Misc,-99,"Rifampicin + Isoniazid, 150 mg + 75 mg, tablet",1057,1,0 +Imported From One Health,Misc,-99,RPR test kit,1058,1,66.4377 +Imported From One Health,Misc,-99,"Salbutamol, oral inhaler, 0.1 mg/dose",1059,1,4.7481 +Imported From One Health,Misc,-99,Slide and stain for microscopy,1060,1,109.15632 +Imported From One Health,Misc,-99,"Soap, bar",1061,1,0 +Imported From One Health,Misc,-99,"Suture, absorbable, synthetic, 1/0, curved needle",1062,1,403.39572 +Imported From One Health,Misc,-99,"Suture, absorbable, synthetic, 3/0, curved needle",1063,1,341.69898 +Imported From One Health,Misc,-99,"Test, blood glucose",1064,1,0 +Imported From One Health,Misc,-99,"Test, blood group, anti A + B, 10 ml",1065,1,0 +Imported From One Health,Misc,-99,"Vaginal cream (Benzalkonium Chloride) with applicator, tube for 30 applications",1066,1,2277.99558 +Imported From One Health,Misc,-99,"Vaginal Foaming Tablet, Neo Sampoon, tube of 20 tablets",1067,1,1428.49266 +Imported From One Health,Misc,-99,"Vaginal Foaming Tablets (Benzalkonium Chloride), tube with 12 tablets",1068,1,650.17554 +Imported From One Health,Misc,-99,"Vitamin A, caplet, 50,000 IU",1069,1,23.72622 +Imported From One Health,Misc,-99,Slides/reagents required for TB detection,1070,1,147.1197 +Imported From One Health,Misc,-99,Sputum container,1071,1,37.96338 +Imported From One Health,Misc,-99,Cat. II Patient Kit B1,1072,1,0 +Imported From One Health,Misc,-99,Cat. II Patient Kit B2,1073,1,0 +Imported From One Health,Misc,-99,Pediatric patient kit,1074,1,2913.93396 +Imported From One Health,Misc,-99,"Ethambutol/Isoniazid, tablet, 400 mg + 150 mg",1075,1,18.98526 +Imported From One Health,Misc,-99,"Ethambutol/Isoniazid, tablet, 400 mg + 150 mg, on blister sheet",1076,1,18.98526 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 150 mg + 150 mg",1077,1,28.47432 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 150 mg + 150 mg, on blister sheet",1078,1,18.98526 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablets, 150 mg + 75 mg",1079,1,33.22242 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablets, 150 mg + 75 mg, on blister sheet",1080,1,14.23716 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Ethambutol, tablet, 150 mg + 75 mg + 275 mg",1081,1,23.72622 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Ethambutol, tablet, 150 mg + 75 mg + 275 mg, on blister sheet",1082,1,37.96338 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide/Ethambutol, tablet, 150 mg + 75 mg + 400 mg + 275 mg",1083,1,28.47432 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide/Ethambutol, tablet, 150 mg + 75 mg + 400 mg + 275 mg, on blister sheet",1084,1,33.22242 +Imported From One Health,Misc,-99,Rifampicin 150 mg / Isoniazid 75 mg / Pyrazinamide 400 mg / Ethambutol 275 mg - Box of 24 blister sheets,1085,1,52.20054 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 60 mg + 30 mg",1086,1,0 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid, tablet, 60 mg + 30 mg, in jar",1087,1,14.23716 +Imported From One Health,Misc,-99,"Rifampicin/Isoniazid/Pyrazinamide, tablet, 60 mg + 30 mg + 150 mg",1088,1,14.23716 +Imported From One Health,Misc,-99,"Amikacin, powder for injection, 500 mg vial",1089,1,0 +Imported From One Health,Misc,-99,"Amikacin, solution for injection, 500 mg/2 ml vial",1090,1,0 +Imported From One Health,Misc,-99,"Capreomycin, powder for injection, 1 g vial",1091,1,10611.65364 +Imported From One Health,Misc,-99,"Cycloserine, capsule, 250 mg, on strip",1092,1,0 +Imported From One Health,Misc,-99,"Ethionamide, tablet, 250 mg, in jar",1093,1,113.89728 +Imported From One Health,Misc,-99,"Ethionamide, tablet, 250 mg, on blister sheet",1094,1,0 +Imported From One Health,Misc,-99,"Kanamycin, solution for injection, 1 g/4 ml vial",1095,1,223.0536 +Imported From One Health,Misc,-99,"Levofloxacin, tablet, 250 mg, on blister sheet",1096,1,0 +Imported From One Health,Misc,-99,"Levofloxacin, tablet, 500 mg, on blister sheet",1097,1,403.39572 +Imported From One Health,Misc,-99,"Moxifloxacin, tablet, 400 mg, on blister sheet",1098,1,0 +Imported From One Health,Misc,-99,"Ofloxacin, tablet, 200 mg, on blister sheet",1099,1,232.54266 +Imported From One Health,Misc,-99,"Ofloxacin, tablet, 400 mg, on blister sheet",1100,1,156.6159 +Imported From One Health,Misc,-99,"PAS, acid sachet granules, 4 g",1101,1,0 +Imported From One Health,Misc,-99,"PAS sodium mini-granules (60% PAS), 100 g jar",1102,1,0 +Imported From One Health,Misc,-99,"Prothionamide, tablet, 250 mg, in jar",1103,1,0 +Imported From One Health,Misc,-99,"TB drugs, MDR, average cost per patient",1104,1,1642201.235 +Imported From One Health,Misc,-99,TB/HIV Care and support for 6 months,1105,1,0 +Imported From One Health,Misc,-99,"Abacavir (ABC), tablet, 300 mg",1106,1,422.38098 +Imported From One Health,Misc,-99,"Abacavir/Lamivudine (ABC+3TC), tablet, 600 + 150 mg",1107,1,0 +Imported From One Health,Misc,-99,AZT + 3TC + EFV (co-blister),1108,1,0 +Imported From One Health,Misc,-99,"Didanosine (ddl), unbuffered enteric coated capsule, 250 mg",1109,1,384.41046 +Imported From One Health,Misc,-99,"Didanosine (ddl), unbuffered enteric coated capsule, 400 mg",1110,1,550.51542 +Imported From One Health,Misc,-99,"Efavirenz (EFV), tablet, 600 mg ",1111,1,118.64538 +Imported From One Health,Misc,-99,"Emtricitabine (FTC), capsule 200 mg",1112,1,156.6159 +Imported From One Health,Misc,-99,"Lamiduvine/Zidovudine/Nevirapine (3TC + AZT + NVP), tablet, 150 + 300 + 200 mg",1113,1,80.682 +Imported From One Health,Misc,-99,"Lamivudine (3TC), tablet, 150 mg",1114,1,33.22242 +Imported From One Health,Misc,-99,"Lamivudine/Stavudine (3TC + d4T), tablet, 150 + 30 mg",1115,1,37.96338 +Imported From One Health,Misc,-99,"Lamivudine/Stavudine (3TC + d4T), tablet, 150 + 40 mg",1116,1,99.66012 +Imported From One Health,Misc,-99,"Lamivudine/Stavudine/Nevirapine (3TC + d4T + NVP), tablet, 150 + 30 + 200 mg",1117,1,227.8017 +Imported From One Health,Misc,-99,"Lamivudine/Stavudine/Nevirapine (3TC + d4T + NVP), tablet, 150 + 40 + 200 mg",1118,1,256.27602 +Imported From One Health,Misc,-99,"Lamivudine/Zidovudine, tablet (3TC+AZT), 150 + 300 mg",1119,1,223.0536 +Imported From One Health,Misc,-99,"Lamivudine/Zidovudine/Abacavir (3TC + AZT + ABC), tablet, 300 + 150 + 300 mg",1120,1,1072.55652 +Imported From One Health,Misc,-99,"Lopinavir/Ritonavir (LPV/r), capsule, 133.3 + 33.3 mg",1121,1,583.73784 +Imported From One Health,Misc,-99,"Nevirapine (NVP), tablet, 200 mg",1122,1,4.7481 +Imported From One Health,Misc,-99,"Stavudine (d4T), capsule, 40 mg",1123,1,23.72622 +Imported From One Health,Misc,-99,Fansidar (sulphadoxine / pyrimethamine tab),1124,1,327.46182 +Imported From One Health,Misc,-99,TDF + FTC + EFV (co-formulation),1125,1,0 +Imported From One Health,Misc,-99,"Tenofovir (TDF), tablet, 300 mg",1126,1,156.6159 +Imported From One Health,Misc,-99,"Test, HIV 1 + 2, Doublecheck, rapid test ",1127,1,934.92588 +Imported From One Health,Misc,-99,"Zidovudine (AZT), tablet/capsule, 250 mg ",1128,1,246.77982 +Imported From One Health,Misc,-99,"Zidovudine (AZT), tablet/capsule, 300 mg ",1129,1,94.91916 +Imported From One Health,Misc,-99,"Zidovudine (AZT), capsule, 100 mg",1130,1,56.94864 +Imported From One Health,Misc,-99,"Zidovudine (AZT), capsule, 250 mg",1131,1,322.71372 +Imported From One Health,Misc,-99,"Zidovudine (AZT), injection, 10 mg/ml in 20 ml vial",1132,1,15912.7395 +Imported From One Health,Misc,-99,"Zidovudine (AZT), oral solution, 10 mg/ml 100 mL, bottle ",1133,1,1314.59538 +Imported From One Health,Misc,-99,PEP Kit,1134,1,384131.5073 +Imported From One Health,Misc,-99,"Doxycycline, tablet, 500 mg",1135,1,17.16456 +Imported From One Health,Misc,-99,"Ferrous Salt + Folic Acid, tablet, 60 + 0.4 mg",1136,1,0 +Imported From One Health,Misc,-99,"Metronidazole, tablet, 500 mg",1137,1,5.26932 +Imported From One Health,Misc,-99,LAM drugs/supplies to service a client,1138,1,0 +Imported From One Health,Misc,-99,Other contraceptives drugs/supplies to service a client,1139,1,0 +Imported From One Health,Misc,-99,Other ANC components drugs/supplies to service a client,1140,1,0 +Imported From One Health,Misc,-99,Other complications drugs/supplies to service a client,1141,1,0 +Imported From One Health,Misc,-99,MgSO4 - Management of pre-eclampsia drugs/supplies to service a client,1142,1,0 +Imported From One Health,Misc,-99,Labor and delivery management drugs/supplies to service a client,1143,1,0 +Imported From One Health,Misc,-99,Pre-referal management of labor complications drugs/supplies to service a client,1144,1,0 +Imported From One Health,Misc,-99,KMC - Kangaroo mother care drugs/supplies to service a client,1145,1,0 +Imported From One Health,Misc,-99,Induction of labor (beyond 41 weeks) drugs/supplies to service a client,1146,1,0 +Imported From One Health,Misc,-99,Maternal Sepsis case management drugs/supplies to service a client,1147,1,0 +Imported From One Health,Misc,-99,Preventive postnatal care drugs/supplies to service a client,1148,1,0 +Imported From One Health,Misc,-99,Breast cancer screening drugs/supplies to service a client,1149,1,0 +Imported From One Health,Misc,-99,Identification and management of infertility drugs/supplies to service a client,1150,1,0 +Imported From One Health,Misc,-99,Treatment of severe diarrhea drugs/supplies to service a client,1151,1,0 +Imported From One Health,Misc,-99,Treatment of severe pneumonia drugs/supplies to service a client,1152,1,0 +Imported From One Health,Misc,-99,Treatment of severe malaria drugs/supplies to service a client,1153,1,0 +Imported From One Health,Misc,-99,Treatment of severe measles drugs/supplies to service a client,1154,1,0 +Imported From One Health,Misc,-99,Malaria case management drugs/supplies to service a client,1155,1,0 +Imported From One Health,Misc,-99,Mass media,1156,1,711.87228 +Imported From One Health,Misc,-99,Community mobilization,1157,1,5424.66498 +Imported From One Health,Misc,-99,Youth focused interventions - In-school drugs/supplies to service a client,1158,1,11588.20572 +Imported From One Health,Misc,-99,Workplace programs drugs/supplies to service a client,1159,1,5117.75208 +Imported From One Health,Misc,-99,Blood safety drugs/supplies to service a client,1160,1,64917.51546 +Imported From One Health,Misc,-99,Universal precautions drugs/supplies to service a client,1161,1,214131.4489 +Imported From One Health,Misc,-99,Additional ART for TB patients drugs/supplies to service a client,1162,1,0 +Imported From One Health,Misc,-99,Diagnostics/lab costs drugs/supplies to service a client,1163,1,0 +Imported From One Health,Misc,-99,Management of opportunistic infections drugs/supplies to service a client,1164,1,0 +Imported From One Health,Misc,-99,ART - Antiretroviral therapy for HIV positive children drugs/supplies to service a client,1165,1,0 +Imported From One Health,Misc,-99,VCT for TB cases drugs/supplies to service a client,1166,1,0 +Imported From One Health,Misc,-99,HIV prevention for TB patients drugs/supplies to service a client,1167,1,0 +Imported From One Health,Misc,-99,ART (+CPT) for TB HIV+ patients drugs/supplies to service a client,1168,1,0 +Imported From One Health,Misc,-99,Folic acid fortification drugs/supplies to service a client,1169,1,0 +Imported From One Health,Misc,-99,Breastfeeding promotion drugs/supplies to service a client,1170,1,0 +Imported From One Health,Misc,-99,Complementary feeding--education only drugs/supplies to service a client,1171,1,0 +Imported From One Health,Misc,-99,Improved water source - cost per HH,1172,1,0 +Imported From One Health,Misc,-99,Water connection in the home - cost per HH,1173,1,0 +Imported From One Health,Misc,-99,Improved sanitation - cost per HH,1174,1,0 +Imported From One Health,Misc,-99,ART (Second-Line Treatment) for adults drugs/supplies to service a client,1175,1,0 +Imported From One Health,Misc,-99,DST test for first-line drugs (liquid media),1176,1,57120.70686 +Imported From One Health,Misc,-99,DST test for first-line drugs,1177,1,57120.70686 +Imported From One Health,Misc,-99,DST test for second-line drugs,1178,1,57120.70686 +Imported From One Health,Misc,-99,First-line treatment – for new drug sensitive patients,1179,1,711.87228 +Imported From One Health,Misc,-99,First-line treatment – for re-retreatment patients,1180,1,711.87228 +Imported From One Health,Misc,-99,First-line treatment – children,1181,1,711.87228 +Imported From One Health,Misc,-99,HIV prevention education,1182,1,2641.80714 +Imported From One Health,Misc,-99,Cotrimoxazole preventive therapy for TB HIV+ patients,1183,1,711.87228 +Imported From One Health,Misc,-99,MSAM Drug Kit,1184,1,71400.87822 +Imported From One Health,Misc,-99,"Ferrous salt, tablets, 60 mg",1185,1,0 +Imported From One Health,Misc,-99,Infant formula,1186,1,71.1858 +Imported From One Health,Misc,-99,AZT + 3TC + NVP,1187,1,711.87228 +Imported From One Health,Misc,-99,"Cannula, IV, 18G, sterile, disposable ",1188,1,99.66012 +Imported From One Health,Misc,-99,"Lopinavir/ritonavir (LPV/r), tablet, 200/50 mg",1189,1,199.32738 +Imported From One Health,Misc,-99,"Didanosine(ddI), capsule, 400 or 250 mg ",1190,1,498.30774 +Imported From One Health,Misc,-99,"Tenofovir (TDF)/Emtricitabine (FTC), tablet, 300/200 mg",1191,1,251.52792 +Imported From One Health,Misc,-99,Meningococcal A vaccine,1192,1,1248.15054 +Imported From One Health,Misc,-99,Towel,1193,1,355.93614 +Imported From One Health,Misc,-99,AZT (60 mg) + 3TC (30 mg) + NVP (50 mg),1194,1,52.20054 +Imported From One Health,Misc,-99,AZT 10 mg/ml + 3TC 10 mg/ml + LPV/r (80 + 20 mg/ml),1195,1,227.8017 +Imported From One Health,Misc,-99,Hepatitis B vaccine,1196,1,151.8678 +Imported From One Health,Misc,-99,"Pentavalent vaccine (DPT, Hep B, Hib)",1197,1,248.09358 +Imported From One Health,Misc,-99,"Hydrochlorothiazide, tablet, 25 mg",1198,1,0 +Imported From One Health,Misc,-99,"Amlodipine, tablet, 10 mg",1199,1,137.63064 +Imported From One Health,Misc,-99,Insulin,1200,1,640.68648 +Imported From One Health,Misc,-99,"Beclometazone inhaler, 250 mcg/dose",1201,1,14.23716 +Imported From One Health,Misc,-99,IV line,1202,1,678.64986 +Imported From One Health,Misc,-99,"Doxycycline, capsule or tablet, 100 mg (hydrochloride)",1203,1,14.23716 +Imported From One Health,Misc,-99,"Tetracycline, capsule or tablet, 250 mg (hydrochloride)",1204,1,14.23716 +Imported From One Health,Misc,-99,"Nystatin 100,000 iu/ml",1205,1,18.98526 +Imported From One Health,Misc,-99,Cyclyphosphamide 1000mg injection,1206,1,2501.04918 +Imported From One Health,Misc,-99,"Metronidazole, oral solution 200 mg/5 ml",1207,1,308.47656 +Imported From One Health,Misc,-99,"Artusenate, 20 mg/ml, 1 ml ampoule",1208,1,1428.49266 +Imported From One Health,Misc,-99,"CareStartMal Pf (HRP2/pf-pLDH), kit/60 ",1209,1,455.59626 +Imported From One Health,Misc,-99,Gentamicine eye drops 0.3%/5ml,1210,1,379.6695 +Imported From One Health,Misc,-99,"Zinc oxide ointment, 10%",1211,1,721.36848 +Imported From One Health,Misc,-99,Miconazolenitrate cream 2%/TBE-30g ,1212,1,227.8017 +Imported From One Health,Misc,-99,Furosemide inj 10mg/ml 2ml amp,1213,1,33.22242 +Imported From One Health,Misc,-99,Paraffin compress,1214,1,104.40822 +Imported From One Health,Misc,-99,Cloxacillin,1215,1,128.13444 +Imported From One Health,Misc,-99,Erythromicine solution 125 mg/ml,1216,1,455.59626 +Imported From One Health,Misc,-99,Permetrine cream 5%,1217,1,3962.76426 +Imported From One Health,Misc,-99,"Permethrin shampoo/sol. 1%, 100ml bottle ",1218,1,1404.7593 +Imported From One Health,Misc,-99,Pyrantel 125 mg tablet,1219,1,14.23716 +Imported From One Health,Misc,-99,"F-75 therapeutic milk, 102.5 g",1220,1,3941.28 +Imported From One Health,Misc,-99,"Supplementary spread, sachet 92g/CAR-150",1221,1,218.3055 +Imported From One Health,Misc,-99,CSB,1222,1,13012.80708 +Imported From One Health,Misc,-99,"F-100 therapeutic diet, sach., 114g/CAR-90",1223,1,4533.9 +Imported From One Health,Misc,-99,"Iron syrup, 20 mg/ml",1224,1,4.7481 +Imported From One Health,Misc,-99,"Vitamin A caplet, 10,000 IU",1225,1,9.48906 +Imported From One Health,Misc,-99,"Iodized oil, 200 mg caplet",1226,1,166.10496 +Imported From One Health,Misc,-99,"Therapeutic spread, sachet 92g/CAR-150",1227,1,256.27602 +Imported From One Health,Misc,-99,"Ciprofloxacin, 250 mg / 5 ml",1228,1,2353.92948 +Imported From One Health,Misc,-99,Nasal prongs,1229,1,151.8678 +Imported From One Health,Misc,-99,Hartmann solution,1230,1,0 +Imported From One Health,Misc,-99,Diazotized reagent,1231,1,294.2394 +Imported From One Health,Misc,-99,Alkaline phosphatase reagents,1232,1,7825.86126 +Imported From One Health,Misc,-99,Pipettes,1233,1,28.47432 +Imported From One Health,Misc,-99,Buffer solution,1234,1,142.3716 +Imported From One Health,Misc,-99,Aspirating needle,1235,1,15993.41436 +Imported From One Health,Misc,-99,Aspirating syringe,1236,1,16007.65152 +Imported From One Health,Misc,-99,Specimen container,1237,1,47.45958 +Imported From One Health,Misc,-99,"Scalpel blade, disposable",1238,1,113.89728 +Imported From One Health,Misc,-99,Biopsy needle,1239,1,16002.91056 +Imported From One Health,Misc,-99,"Electrodes, electrocardiographic",1240,1,66.4377 +Imported From One Health,Misc,-99,"Paper, Recording ECG",1241,1,23.72622 +Imported From One Health,Misc,-99,"Butylscopolamine, one ampoule",1242,1,66.4377 +Imported From One Health,Misc,-99,Developer chemicals,1243,1,308.47656 +Imported From One Health,Misc,-99,Sponges,1244,1,28.47432 +Imported From One Health,Misc,-99,Sutures,1245,1,469.83342 +Imported From One Health,Misc,-99,Wound drainage kit,1246,1,18954.8079 +Imported From One Health,Misc,-99,"Doxorubicin, 10 mg vial",1247,1,4456.3239 +Imported From One Health,Misc,-99,"Cyclophosphamide, 500 mg",1248,1,6777.03096 +Imported From One Health,Misc,-99,"Dexamethasone, 4 mg, 1 ampoule",1249,1,109.15632 +Imported From One Health,Misc,-99,"Tamoxifen, 20 mg tablet",1250,1,94.91916 +Imported From One Health,Misc,-99,Cannulae,1251,1,1157.97948 +Imported From One Health,Misc,-99,Intravenous administration set,1252,1,1499.67846 +Imported From One Health,Misc,-99,"Fluoxetine, 20 mg tab",1253,1,14.23716 +Imported From One Health,Misc,-99,"Amitriptyline, 50 mg tab",1254,1,14.23716 +Imported From One Health,Misc,-99,"Haloperidol, 5 mg tab",1255,1,14.23716 +Imported From One Health,Misc,-99,"Chlorpromazine, 100 mg",1256,1,14.23716 +Imported From One Health,Misc,-99,"Fluphenazine decanoate, 25 mg/ml",1257,1,616.95312 +Imported From One Health,Misc,-99,EEG,1258,1,7137.7152 +Imported From One Health,Misc,-99,"Phenytoin, 100 mg",1259,1,3.84132 +Imported From One Health,Misc,-99,"Carbamazepine, 200 mg",1260,1,18.98526 +Imported From One Health,Misc,-99,"Valproate, 500 mg",1261,1,109.15632 +Imported From One Health,Misc,-99,Serum level test,1262,1,0 +Imported From One Health,Misc,-99,Thyroid function test,1263,1,0 +Imported From One Health,Misc,-99,"Diazepam, 5 mg",1264,1,0 +Imported From One Health,Misc,-99,"Methylphenidate, 10 mg",1265,1,56.94864 +Imported From One Health,Misc,-99,"Haloperidol, 5 mg",1266,1,14.23716 +Imported From One Health,Misc,-99,"Donepezil, 10 mg",1267,1,213.56454 +Imported From One Health,Misc,-99,"Acamprosate, 333 mg",1268,1,242.03886 +Imported From One Health,Misc,-99,"Naltrexone, 50 mg",1269,1,4760.0595 +Imported From One Health,Misc,-99,"Disulfiram, 250 mg",1270,1,555.26352 +Imported From One Health,Misc,-99,Diaphragm,1271,1,10711.3209 +Imported From One Health,Misc,-99,"Microscope slides, lime-soda-glass, pack of 50",1272,1,2140.36494 +Imported From One Health,Misc,-99,"Sputum containers, pack 100",1273,1,7854.33558 +Imported From One Health,Misc,-99,"Immersion oil, 500ml",1274,1,29272.22214 +Imported From One Health,Misc,-99,"Lens tissue (paper), 50 pages/block, 10 blocks/pack",1275,1,26419.98492 +Imported From One Health,Misc,-99,"Liquid soap for hands, 1 liter",1276,1,7137.7152 +Imported From One Health,Misc,-99,"Paper towels, single-use, box. 150 towels/pack, 30 packs/ carton",1277,1,42123.90798 +Imported From One Health,Misc,-99,"Nitril gloves, powder free, if Auramine O is used for staining",1278,1,12851.68584 +Imported From One Health,Misc,-99,"Laboratory request forms, pack of 1000",1279,1,19277.52162 +Imported From One Health,Misc,-99,"Laboratory report forms, pack of 1000",1280,1,19277.52162 +Imported From One Health,Misc,-99,Laboratory register,1281,1,9994.70052 +Imported From One Health,Misc,-99,"Filter paper round, diameter 150, packs of 100",1282,1,7137.7152 +Imported From One Health,Misc,-99,"Desinfectant, phenol, bottle of 5 kg",1283,1,68543.8929 +Imported From One Health,Misc,-99,"Stable chlorine desinfectant, pack of 100 tablets",1284,1,19277.52162 +Imported From One Health,Misc,-99,Protective eye glasses,1285,1,3568.8576 +Imported From One Health,Misc,-99,"Methylated ethanol for spirit lamps, bottle of 2.5 L",1286,1,2140.36494 +Imported From One Health,Misc,-99,"Basic fuchsine, 100g (bottle)",1287,1,44980.8933 +Imported From One Health,Misc,-99,"Methylene blue, 100g (bottle)",1288,1,77826.72114 +Imported From One Health,Misc,-99,"Phenol crystals colourless, 5Kg ",1289,1,68543.8929 +Imported From One Health,Misc,-99,"Ethanol, 96%, 2.5L (bottle), for stain solutions",1290,1,4997.35026 +Imported From One Health,Misc,-99,"Ethanol, 96%, 2.5L (bottle), for decolourization",1291,1,4997.35026 +Imported From One Health,Misc,-99,"Hydrochloric acid, 2.5L (bottle)",1292,1,19277.52162 +Imported From One Health,Misc,-99,"Concentrated sulphuric acid, 2.5L (bottle)",1293,1,58549.19238 +Imported From One Health,Misc,-99,"Auramine O, 50g (bottle)",1294,1,23562.9996 +Imported From One Health,Misc,-99,"Potassium permanganate, 250g (bottle)",1295,1,68543.8929 +Imported From One Health,Misc,-99,"Tube for liquid cultures, growth detection based on fluorescence signal, per test - 1 tubes per test + 10% repeat + 10% contamination",1296,1,3749.19972 +Imported From One Health,Misc,-99,"Growth supplement for liquid cultures, growth detection based on fluorescence signal, per test. BACTEC MGIT 960 Supplement Kit (100 tests, PANTA and OADC combined) + 10% repeat + 10% contamination",1297,1,1072.55652 +Imported From One Health,Misc,-99,"Petri-dishes, disposables, sterile; 20 per bag, 15 bags per package",1298,1,77826.72114 +Imported From One Health,Misc,-99,"Immunochromatographic tests for the rapid identification of Mycobacterium tuberculosis, per test",1299,1,1428.49266 +Imported From One Health,Misc,-99,"Droppers, disposable, 1.5 ml, 20 per bag and 25 bags per package",1300,1,58549.19238 +Imported From One Health,Misc,-99,"Culture tubes, diameter 16 mm, pack of 100",1301,1,29272.22214 +Imported From One Health,Misc,-99,"PP-tubes for centrifuge, 50 ml; 500 pieces/pack",1302,1,117093.6438 +Imported From One Health,Misc,-99,"PP-tubes for centrifuge, 15 ml; 500 pieces/pack",1303,1,117093.6438 +Imported From One Health,Misc,-99,"Loop, disposable 10 m, 500 pieces/pack",1304,1,17849.0361 +Imported From One Health,Misc,-99,"Plastic Pasteur pipettes, 1.5 ml, 500 pieces/pack",1305,1,39271.67076 +Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 2 ml",1306,1,142085.1361 +Imported From One Health,Misc,-99,"Deep freeze storage box with lid for 2 ml cryovials , autoclavable PP",1307,1,7854.33558 +Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size S, 100/pack",1308,1,11423.19318 +Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size M, 100/pack",1309,1,11423.19318 +Imported From One Health,Misc,-99,"Gloves, vinyl or nitrile, powder free, disposable, size L, 100/pack",1310,1,11423.19318 +Imported From One Health,Misc,-99,"Plastic bags for waste bins, 1000 pieces per pack",1311,1,21417.8937 +Imported From One Health,Misc,-99,Stands for small plastic bags (2 litres),1312,1,7854.33558 +Imported From One Health,Misc,-99,"Autoclavable bags at 134°C, 410 x 620 mm, 100 pieces per pack",1313,1,39271.67076 +Imported From One Health,Misc,-99,"Filter paper round, diameter 185, packs of 100",1314,1,7854.33558 +Imported From One Health,Misc,-99,"Marker pen, water resistant",1315,1,4878.70488 +Imported From One Health,Misc,-99,"Adhesive labels, pack of 4800 labels",1316,1,44980.8933 +Imported From One Health,Misc,-99,"Cryo-tags sized to fit for use on cryo-tubes, rolls of 1000",1317,1,40970.6766 +Imported From One Health,Misc,-99,"Sterilindicator tape (rolls), 55 m long, for hot air sterilizer (green/brown)",1318,1,21417.8937 +Imported From One Health,Misc,-99,"Sterilindicator tape (rolls), 55 m long, for autoclave (beige/dark brown)",1319,1,12851.68584 +Imported From One Health,Misc,-99,"Parafilm, 100 mm width with dispenser",1320,1,22134.50694 +Imported From One Health,Misc,-99,"Plastic-foil rolls, 30 cm",1321,1,7854.33558 +Imported From One Health,Misc,-99,Tube brush 280 mm long,1322,1,2140.36494 +Imported From One Health,Misc,-99,"Laboratory coat, size L",1323,1,34274.3205 +Imported From One Health,Misc,-99,"Laboratory coat, size M",1324,1,34274.3205 +Imported From One Health,Misc,-99,"Laboratory coat, size S",1325,1,34274.3205 +Imported From One Health,Misc,-99,"FFP2 or FFP3 respirators, individually packed, packs of 10",1326,1,21417.8937 +Imported From One Health,Misc,-99,"Disinfectant for floors, container 10 litres ",1327,1,51406.73622 +Imported From One Health,Misc,-99,"Disinfectant, ethanol-based, container 5 litres",1328,1,45697.51368 +Imported From One Health,Misc,-99,Spray hand for bottle with disinfectant of 1 litre,1329,1,4997.35026 +Imported From One Health,Misc,-99,"Disinfectant for hands, alcohol-based, 1 litre bottle",1330,1,7854.33558 +Imported From One Health,Misc,-99,"Cotton wool, 1 kg",1331,1,2140.36494 +Imported From One Health,Misc,-99,"Tissue pulp, absorbent sheets, approx. 550 x 350 mm",1332,1,4997.35026 +Imported From One Health,Misc,-99,"Ready-to-use mix, 500g",1333,1,95675.7501 +Imported From One Health,Misc,-99,"Glycerol >99% purity, 1 litre",1334,1,27131.8572 +Imported From One Health,Misc,-99,"di-Sodium hydrogen phosphate anhydrous, Na2HPO4, MW: 141.96, 1 kg ",1335,1,64258.41492 +Imported From One Health,Misc,-99,"Potassium dihydrogen phosphate, KH2PO4, MW: 136,09, 1 kg ",1336,1,24991.49226 +Imported From One Health,Misc,-99,"N-acetyl-L-cysteine (NALC), C5H9NO3S, MW: 163.19,puriss. ? 99%, 250g",1337,1,146370.614 +Imported From One Health,Misc,-99,"tri-Sodium citrate dihydrate, C6H5Na3O7 · 2H2O, MW: 294.10, 1 kg",1338,1,39983.54304 +Imported From One Health,Misc,-99,"Sodium hydroxide, NaOH, MW 40.00, purum ? 98%, pellets, 1kg",1339,1,11423.19318 +Imported From One Health,Misc,-99,"BACTEC™ MGIT™ 960 SIRE kit, One kit is sufficient for 40 test + 10% repeat",1340,1,1300.35822 +Imported From One Health,Misc,-99,"Tube and growth supplement for liquid cultures, growth detection based on fluorescence signal, per test - 5 tubes per test + 10% repeat",1341,1,3749.19972 +Imported From One Health,Misc,-99,"Syringe filters, 100 pieces per pack",1342,1,292741.2281 +Imported From One Health,Misc,-99,"Silica gel for desiccator, 0.5 kg",1343,1,29272.22214 +Imported From One Health,Misc,-99,"DNAse-/RNAse-free TIPS, for pipettes 0.1 - 10 µl, 10 boxes at 960 per pack",1344,1,89249.91432 +Imported From One Health,Misc,-99,"Sterile, DNA-/RNAse-free TIPS 100 - 1000 µl",1345,1,89249.91432 +Imported From One Health,Misc,-99,Dispenser-tips Universal 10ml sterile ,1346,1,89249.91432 +Imported From One Health,Misc,-99,"Isoniazid, 5 g",1347,1,16420.54344 +Imported From One Health,Misc,-99,"Rifampicin, 1 g",1348,1,58549.19238 +Imported From One Health,Misc,-99,"Ethambutol, 25 g",1349,1,68543.8929 +Imported From One Health,Misc,-99,"Dihydro-streptomycin, 5 g",1350,1,17849.0361 +Imported From One Health,Misc,-99,"Ofloxacin/Ciprofloxacin, 2 g",1351,1,21417.8937 +Imported From One Health,Misc,-99,"Protionamid, 2 g",1352,1,17849.0361 +Imported From One Health,Misc,-99,"Kanamycin, 2 g",1353,1,29988.84252 +Imported From One Health,Misc,-99,"capreomycin, 2 g",1354,1,112812.9139 +Imported From One Health,Misc,-99,"Dimethyl sulfoxide, 99,8%, p. a., 500 ml",1355,1,19277.52162 +Imported From One Health,Misc,-99,"Xpert Cartridge, one cartridge",1356,1,7125.70572 +Imported From One Health,Misc,-99,"Standard reaction tubes with O-ring, 1.5 ml, 1000 per pack",1357,1,126822.5792 +Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 2 ml, with outer winding; pack of 1000",1358,1,175595.3837 +Imported From One Health,Misc,-99,"PCR tubes, 0.2 ml with attached caps, sterile, DNAse- RNAse-free, 1000 per pack",1359,1,82923.73152 +Imported From One Health,Misc,-99,"DNAse-/RNAse-free TIPS, for pipettes 20 - 200 µl, 10 boxes at 960per pack",1360,1,89249.91432 +Imported From One Health,Misc,-99,"Pasteur-pipettes, plastic, sterile, 1.5ml, 500 per pack",1361,1,39020.14284 +Imported From One Health,Misc,-99,"Combitips for Multipette 10 ml, 100 pieces/pack ",1362,1,78040.28568 +Imported From One Health,Misc,-99,"Plastic bags, disposable PP, 100 pieces per pack",1363,1,9752.66166 +Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size M, 100 per pack",1364,1,11707.94352 +Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size S, 100 per pack",1365,1,11707.94352 +Imported From One Health,Misc,-99,"Gloves, vinyl, powder free, disposable, size L, 100 per pack",1366,1,11707.94352 +Imported From One Health,Misc,-99,Forceps plastic,1367,1,10730.29902 +Imported From One Health,Misc,-99,"Bottles, plastic",1368,1,21460.60518 +Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 6-7, 100 per pack",1369,1,13658.47014 +Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 7-8, 100 per pack",1370,1,14631.36654 +Imported From One Health,Misc,-99,"Gloves, nitril, powder free, disposable, size 8-9, 100 per pack",1371,1,15609.0039 +Imported From One Health,Misc,-99,"Strips for the rapid detection of resistance to isoniazid and rifampicin, per strip ",1372,1,44876.48508 +Imported From One Health,Misc,-99,Kit 4(RHZE 150/75/400/275) / 2(EH 400/75),1373,1,22082.3064 +Imported From One Health,Misc,-99,Kit 2(RHZE 150/75/400/275) / 4(RH 150/150)3,1374,1,11546.58666 +Imported From One Health,Misc,-99,Kit 2 (RHZE 150/75/400/275) / 4(RH 150/75),1375,1,15884.26518 +Imported From One Health,Misc,-99,"RHZE 150/75/400/275 in blister sheets, 1 box",1376,1,34449.91452 +Imported From One Health,Misc,-99,"RH 150/150 in blister sheet, 1 box",1377,1,16458.50682 +Imported From One Health,Misc,-99,"RH 150/75, in blister sheet, 1 box",1378,1,16600.87842 +Imported From One Health,Misc,-99,"RHE 150/75/275 in blister sheet, 1 box",1379,1,22405.02012 +Imported From One Health,Misc,-99,"E 400 in blister sheet, 1 box",1380,1,18328.35858 +Imported From One Health,Misc,-99,S 1 g (100 vials),1381,1,48549.7509 +Imported From One Health,Misc,-99,Kit 2S(RHZE) / 1(RHZE) / 5(RH)E + AD,1382,1,70613.07204 +Imported From One Health,Misc,-99,Kit 2S(RHZE) / 1(RHZE) / 5(RHE) + AD,1383,1,69545.26362 +Imported From One Health,Misc,-99,Kit 2S(RHZE) / 3(RHZE) / (5(RH 150/150)E)3 + AD,1384,1,64509.94998 +Imported From One Health,Misc,-99,2RHZ/4RH ,1385,1,17222.58678 +Imported From One Health,Misc,-99,2RHZE/4RH ,1386,1,20426.01204 +Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z/ 15 Lfx Eto Cs,1387,1,1332493.689 +Imported From One Health,Misc,-99,6 Km Lfx Pto Cs Z E/ 18 Lfx Pto Cs Z E,1388,1,1485498.963 +Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z (PAS) / 18 Lfx Eto Cs Z (PAS),1389,1,1518833.609 +Imported From One Health,Misc,-99,6 Km Lfx Eto Cs Z E/ 18 Lfx Eto Cs Z E,1390,1,1645072.451 +Imported From One Health,Misc,-99,10 Km (Cm)-Lfx-Pto-CS-(+/-E/Z) / 18 Lfx-Pto-CS-(+/-E/Z),1391,1,1692824.906 +Imported From One Health,Misc,-99,10 Km(Cm) Z Lfx Pto Cs (PAS) / 12-18 Z Lfx Pto Cs (PAS),1392,1,3916844.828 +Imported From One Health,Misc,-99,6 Cm-Lfx-Et-Cs-Z / 18 Lfx-Et-Cs,1393,1,2188796.438 +Imported From One Health,Misc,-99,8 Km (Cm) Lfx(Mfx) Eto Cs (PAS) E/ 12-16 Lfx(Mfx) Eto Cs (PAS) E,1394,1,3148197.396 +Imported From One Health,Misc,-99,6 Km (Cm) Lfx Eto Cs (PAS)  E Z / 18Lfx Eto Cs E Z,1395,1,2834389.469 +Imported From One Health,Misc,-99,6 Amk-Z-Lfx-Cs-Eto-PAS/ 18 Z-Lfx-Cs-Eto-PAS,1396,1,3339363.82 +Imported From One Health,Misc,-99,8 Km  (Cm) Z Ofx Eto Cs PAS/ 16 Z Ofx Eto Cs PAS,1397,1,3051994.856 +Imported From One Health,Misc,-99,6 Cm Lfx (Ofx) Eto Cs PASER/ 18 Lfx (Ofx) Eto Cs PASER,1398,1,3944351.607 +Imported From One Health,Misc,-99,9-12 Cm Lfx (Ofx) -Pto - PAS - Cs / 14 Lfx (Ofx) -Pto - PAS - Cs,1399,1,3060674.962 +Imported From One Health,Misc,-99,6 Cm Lfx(Ofx) Cs Eto PASER Z E / 18 Lfx(Ofx) Cs Eto PASER Z E,1400,1,3192181.666 +Imported From One Health,Misc,-99,8 Cm- Pto- Ofx- Cs- Z (PAS) / 12 Cs- Pto- Z- Ofx (PAS),1401,1,3471615.62 +Imported From One Health,Misc,-99,12 Km(Cm) Z Lfx(Ofx) Pto Cs (PAS) / 12 Z Lfx(Ofx) Pto Cs (PAS),1402,1,1905964.481 +Imported From One Health,Misc,-99,6 Cm (Km) Z Lfx Eto Cs (E) / 18  Z Lfx Eto Cs (E) ,1403,1,3051994.856 +Imported From One Health,Misc,-99,8 Cm Cs Eto PAS Mfx /12 Eto PAS Mfx,1404,1,3695158.031 +Imported From One Health,Misc,-99,8km Cs Lfx(HD) Eto Z/12 Cs Lfx(HD) Eto,1405,1,1505113.442 +Imported From One Health,Misc,-99,12 Cm-Mfx-PASER- Cs-Amox/Clv – Z / 12 Mfx- PASER- CS- Amox/Clv,1406,1,5427828.85 +Imported From One Health,Misc,-99,"Isoniazid, 300 mg tab",1407,1,14.3514 +Imported From One Health,Misc,-99,Surgical mask,1408,1,28.56 +Imported From One Health,Misc,-99,"Surgical cap, disposable",1409,1,235.62 +Imported From One Health,Misc,-99,Surgical scrub Betadine,1410,1,14.28 +Imported From One Health,Misc,-99,"Gauze pad, inadine",1411,1,121.38 +Imported From One Health,Misc,-99,Elastoplast/Dermaplast 25 mm/9mm,1412,1,121.38 +Imported From One Health,Misc,-99,Micropore,1413,1,121.38 +Imported From One Health,Misc,-99,Bandage,1414,1,42.84 +Imported From One Health,Misc,-99,"Lignocaine, 2%, injection 20 ml",1415,1,85.68 +Imported From One Health,Misc,-99,2(RH)3Z3E3,1416,1,42440.16 +Imported From One Health,Misc,-99,2(RH)ZE,1417,1,8736.38262 +Imported From One Health,Misc,-99,2(RHZE),1418,1,2011.695 +Imported From One Health,Misc,-99,"2HRZ, 21-30 kg weight band",1419,1,8017.02762 +Imported From One Health,Misc,-99,"2HRZ, 5-20 kg weight band",1420,1,4924.22238 +Imported From One Health,Misc,-99,"2RHZE, 21-30 kg weight band",1421,1,10122.735 +Imported From One Health,Misc,-99,"2RHZE, 5-20 kg weight band",1422,1,16639.6272 +Imported From One Health,Misc,-99,2S(RH)ZE/1(RH)ZE,1423,1,38694.3375 +Imported From One Health,Misc,-99,2S(RHZE)/1(RHZE),1424,1,36489.8625 +Imported From One Health,Misc,-99,2S3(RH)3Z3E3/1(RH)3Z3E3,1425,1,19165.15944 +Imported From One Health,Misc,-99,4(RH),1426,1,7022.19 +Imported From One Health,Misc,-99,4(RH)3,1427,1,3584.78694 +Imported From One Health,Misc,-99,"4RH, 21-30 kg weight band",1428,1,12734.19 +Imported From One Health,Misc,-99,"4RH, 5-20 kg weight band",1429,1,10081.68 +Imported From One Health,Misc,-99,5(RH)3E3,1430,1,9634.5375 +Imported From One Health,Misc,-99,5(RH)3Z3E3,1431,1,13663.53954 +Imported From One Health,Misc,-99,5(RH)E,1432,1,14790.21012 +Imported From One Health,Misc,-99,5(RH)ZE,1433,1,21840.96012 +Imported From One Health,Misc,-99,5(RHE),1434,1,14819.9625 +Imported From One Health,Misc,-99,5(RHZE),1435,1,18166.8375 +Imported From One Health,Misc,-99,6(EH),1436,1,14651.994 +Imported From One Health,Misc,-99,Albuterol,1437,1,0 +Imported From One Health,Misc,-99,Amikacin 500 mg,1438,1,574.77 +Imported From One Health,Misc,-99,"Amikacin (AMI), 5g",1439,1,228961.95 +Imported From One Health,Misc,-99,Amitriptyline 25 mg tablets,1440,1,5.1408 +Imported From One Health,Misc,-99,Amoxicillin 500 mg Clavulanic acid 125 mg,1441,1,106.4574 +Imported From One Health,Misc,-99,"BACTEC MGIT 960 Supplement Kit (100 tests, PANTA and OADC combined)",1442,1,505.512 +Imported From One Health,Misc,-99,BACTEC™ MGIT™ PZA Kit,1443,1,1293.768 +Imported From One Health,Misc,-99,BACTEC™ MGIT™ PZA Tubes - 25,1444,1,1529.388 +Imported From One Health,Misc,-99,BBL MGIT Tubes for use in Bactec MGIT 960 (7ml) - 100 tubes/pkg,1445,1,1392.3 +Imported From One Health,Misc,-99,Brain Heart Infusion agar,1446,1,119752.08 +Imported From One Health,Misc,-99,"Calamine lotion, 500 ml",1447,1,4.4982 +Imported From One Health,Misc,-99,Capreomycin 1000 mg,1448,1,3355.8 +Imported From One Health,Misc,-99,"Centrifuge tubes if specimens are further culture processed, pack 1000",1449,1,105.8148 +Imported From One Health,Misc,-99,Cilastatin 500 mg,1450,1,3648.54 +Imported From One Health,Misc,-99,Cimetidine,1451,1,0 +Imported From One Health,Misc,-99,Ciotrimazole,1452,1,0 +Imported From One Health,Misc,-99,Cladryl lotion,1453,1,0 +Imported From One Health,Misc,-99,Clarithromycin 500 mg,1454,1,102.00204 +Imported From One Health,Misc,-99,Clavunate 125 mg,1455,1,250.3998 +Imported From One Health,Misc,-99,Clofazimine 100 mg,1456,1,904.7808 +Imported From One Health,Misc,-99,Codeine 30 mg,1457,1,50.8368 +Imported From One Health,Misc,-99,Cryo-tags,1458,1,18.78534 +Imported From One Health,Misc,-99,"Cryo-vial, sterile with cap, 1.5 ml",1459,1,179.89944 +Imported From One Health,Misc,-99,Culture tubes with screw cap,1460,1,185.4972 +Imported From One Health,Misc,-99,"Cutaneous reactions, itching",1461,1,125.9496 +Imported From One Health,Misc,-99,Cycloserin 250 mg,1462,1,235.62 +Imported From One Health,Misc,-99,"Dexamethasone 0.5 mg, tablet",1463,1,5.712 +Imported From One Health,Misc,-99,Dexamethasone 5 ml inj,1464,1,58.905 +Imported From One Health,Misc,-99,Diazepam 5mg/ml,1465,1,47.5524 +Imported From One Health,Misc,-99,Dihydro-streptomycin - for laboratory use (5g),1466,1,46845.54 +Imported From One Health,Misc,-99,"Dimenhydrinate 50 , tablet",1467,1,2427.6 +Imported From One Health,Misc,-99,"Dimenhydrinate 50 mg/ml, vial",1468,1,152.082 +Imported From One Health,Misc,-99,"Dimethyl sulfoxide, 99,8%",1469,1,11038.44 +Imported From One Health,Misc,-99,Disinfectant for BSCs surface,1470,1,27210.54 +Imported From One Health,Misc,-99,Disinfectant for cleaning instrument,1471,1,76483.68 +Imported From One Health,Misc,-99,Disinfectant for floors,1472,1,16314.9 +Imported From One Health,Misc,-99,Disinfectant for hands,1473,1,6490.26 +Imported From One Health,Misc,-99,di-Sodium hydrogen phosphate dodecahydrate,1474,1,29274 +Imported From One Health,Misc,-99,Dispenser for disinfectant/soap,1475,1,39334.26 +Imported From One Health,Misc,-99,"Disposable pasteur pipettes, graduated, non sterile, 155 mm, 3 ml",1476,1,13.33752 +Imported From One Health,Misc,-99,E100,1477,1,10627.7472 +Imported From One Health,Misc,-99,E400,1478,1,2404.98762 +Imported From One Health,Misc,-99,EH 400/150,1479,1,14651.994 +Imported From One Health,Misc,-99,Electrolyte wasting,1480,1,10363.8528 +Imported From One Health,Misc,-99,Ethambutol,1481,1,21.46998 +Imported From One Health,Misc,-99,Ethambutol - for laboratory use (25g),1482,1,4513.3368 +Imported From One Health,Misc,-99,"Ethionamid (ETH), 5g",1483,1,112594.23 +Imported From One Health,Misc,-99,Ethionamide 250 mg,1484,1,57.0486 +Imported From One Health,Misc,-99,Famotidine,1485,1,0 +Imported From One Health,Misc,-99,Filter paper - sheets,1486,1,845.376 +Imported From One Health,Misc,-99,Fluconazole 50 mg,1487,1,6837.264 +Imported From One Health,Misc,-99,"Forceps, individually wrap, sterile",1488,1,107.9568 +Imported From One Health,Misc,-99,Furosemide (RX) 20 mg,1489,1,1004.598 +Imported From One Health,Misc,-99,Gabapentin,1490,1,0 +Imported From One Health,Misc,-99,GenoType MTBDR plus V2 - 30496AM - Test kit only composed of: 30496A GenoType MTBDRplus Version 2.0 and 51610 GenoLyse,1491,1,7497 +Imported From One Health,Misc,-99,"Glass beads, massive glass, 3 mm diameter",1492,1,4419.66 +Imported From One Health,Misc,-99,"Glass beads, massive glass, 5 mm diameter",1493,1,4783.8 +Imported From One Health,Misc,-99,GT-Blot 48 reagent kits,1494,1,0 +Imported From One Health,Misc,-99,GT-Blot 48 Tray for 96 strips (black),1495,1,2070.6 +Imported From One Health,Misc,-99,H300,1496,1,6822.86976 +Imported From One Health,Misc,-99,Hair Cover,1497,1,7.9254 +Imported From One Health,Misc,-99,Haloperidol 2mg - tablets ,1498,1,3454.6176 +Imported From One Health,Misc,-99,"Haloperidol 5mg/ml, 2ml - injections",1499,1,206.8458 +Imported From One Health,Misc,-99,High-dose isoniazid,1500,1,40.61232 +Imported From One Health,Misc,-99,Hydrocortisone cream,1501,1,28.4886 +Imported From One Health,Misc,-99,Hyoscine Butylbromide 10 mg,1502,1,11407.4352 +Imported From One Health,Misc,-99,Ibuprofen 200 mg,1503,1,4.9266 +Imported From One Health,Misc,-99,Imipenem/Cilastin 500 mg,1504,1,7282.8 +Imported From One Health,Misc,-99,Ion exchanger cartridge,1505,1,440309.52 +Imported From One Health,Misc,-99,Ion exchanger resin for laboratory grade water,1506,1,12680.64 +Imported From One Health,Misc,-99,IPT for children under 20kg,1507,1,1786.428 +Imported From One Health,Misc,-99,Isoniazid 100 mg,1508,1,21.42 +Imported From One Health,Misc,-99,Isoniazid - for laboratory use (5g),1509,1,3791.34 +Imported From One Health,Misc,-99,Isoniazid 150 mg,1510,1,28.56 +Imported From One Health,Misc,-99,Isoniazid Preventive Therapy,1511,1,3251.556 +Imported From One Health,Misc,-99,Isopropanol,1512,1,2143.428 +Imported From One Health,Misc,-99,Kanamycin 1000 mg,1513,1,1228.9368 +Imported From One Health,Misc,-99,"Kanamycin (KAN), 1g",1514,1,9599.016 +Imported From One Health,Misc,-99,Lansoprazole,1515,1,0 +Imported From One Health,Misc,-99,L-Asparagine-momohydrate,1516,1,178500 +Imported From One Health,Misc,-99,"Latex gloves size L, 1000 per pack",1517,1,35.92848 +Imported From One Health,Misc,-99,"Latex gloves size M, 1000 per pack",1518,1,35.92848 +Imported From One Health,Misc,-99,"Latex gloves size S, 1000 per pack",1519,1,35.92848 +Imported From One Health,Misc,-99,Levofloxacin 250 mg,1520,1,39.27 +Imported From One Health,Misc,-99,Levothyroxine 50 mcg,1521,1,9.8532 +Imported From One Health,Misc,-99,Linezolid 600 mg,1522,1,3912.72 +Imported From One Health,Misc,-99,Long 1 ml tips with filter,1523,1,86.60106 +Imported From One Health,Misc,-99,Loperamide 2 mg,1524,1,7.14 +Imported From One Health,Misc,-99,"Lorazepam, 1 mg",1525,1,0 +Imported From One Health,Misc,-99,Magnesium sulfate-heptahydrate,1526,1,51408 +Imported From One Health,Misc,-99,Magnetic bars set of 12,1527,1,28060.2 +Imported From One Health,Misc,-99,Malachite green oxalate,1528,1,485520 +Imported From One Health,Misc,-99,Masks FFP2 (N95) - 3M 9320,1529,1,1432.284 +Imported From One Health,Misc,-99,Meclizine,1530,1,0 +Imported From One Health,Misc,-99,Metoclopramide HCL,1531,1,2087.1648 +Imported From One Health,Misc,-99,"Microscope slides with frosted end, pack of 50",1532,1,63.546 +Imported From One Health,Misc,-99,Molecular grade water,1533,1,8208.47958 +Imported From One Health,Misc,-99,Moxifloxacin 400 mg,1534,1,328.44 +Imported From One Health,Misc,-99,"Moxifloxacin (MOX), 2g",1535,1,7140 +Imported From One Health,Misc,-99,Mystatin,1536,1,0 +Imported From One Health,Misc,-99,odansetron 8 mg,1537,1,341791.2288 +Imported From One Health,Misc,-99,Ofloxacin 200 mg,1538,1,41.412 +Imported From One Health,Misc,-99,"Ofloxacin/Ciprofloxacin, 10 g",1539,1,225188.46 +Imported From One Health,Misc,-99,Oil 8cc for CX 21 / CX 22,1540,1,3277.26 +Imported From One Health,Misc,-99,Omeprazole 20 mg,1541,1,12.852 +Imported From One Health,Misc,-99,Other serotonin 5-THE receptor antagonist,1542,1,0 +Imported From One Health,Misc,-99,P-aminosalicylic acid 4000 mg,1543,1,951.99762 +Imported From One Health,Misc,-99,PCR tubes,1544,1,32.95824 +Imported From One Health,Misc,-99,Phenitoin,1545,1,0 +Imported From One Health,Misc,-99,Phenol,1546,1,49.73724 +Imported From One Health,Misc,-99,Plastic bags - 30L,1547,1,282.387 +Imported From One Health,Misc,-99,Plastic bags made from PP,1548,1,56.3346 +Imported From One Health,Misc,-99,Plastic-foil,1549,1,49194.6 +Imported From One Health,Misc,-99,PP-tubes for centrifuge non sterile 50 ml,1550,1,105.8148 +Imported From One Health,Misc,-99,"PP-tubes for centrifuge, non sterile, 15 ml",1551,1,121.86552 +Imported From One Health,Misc,-99,"PP-tubes for centrifuge, sterile, 50 ml",1552,1,105.8148 +Imported From One Health,Misc,-99,"Prednisone, 50 mg",1553,1,1673.3304 +Imported From One Health,Misc,-99,Prochlorperazine 5 mg,1554,1,14394.24 +Imported From One Health,Misc,-99,Promethazine,1555,1,510.00306 +Imported From One Health,Misc,-99,Protionamide 250 mg,1556,1,126.735 +Imported From One Health,Misc,-99,Pyrazinamide,1557,1,22.3482 +Imported From One Health,Misc,-99,"Rantidine, 150 mg tab",1558,1,0 +Imported From One Health,Misc,-99,Rapid test for Detection of MPT 64 Antigen,1559,1,999.6 +Imported From One Health,Misc,-99,"Ready mixed TB / LJ Base, 500g",1560,1,42840 +Imported From One Health,Misc,-99,Regimen 1: TDF+3TC+EFV,1561,1,43246.98 +Imported From One Health,Misc,-99,Regimen 2: TDF +FTC+EFV,1562,1,49570.164 +Imported From One Health,Misc,-99,Regimen 3: AZT + 3TC + EFV,1563,1,59646.132 +Imported From One Health,Misc,-99,Regimen 4: AZT+3TC+ NVP,1564,1,54672.408 +Imported From One Health,Misc,-99,Regimen 5: TDF+3TC+NVP,1565,1,65982.168 +Imported From One Health,Misc,-99,Regimen 6: TDF+FTC+NVP,1566,1,53091.612 +Imported From One Health,Misc,-99,RH 150/150,1567,1,24.89718 +Imported From One Health,Misc,-99,RH 150/75,1568,1,20.89878 +Imported From One Health,Misc,-99,RH 60/30,1569,1,13.00194 +Imported From One Health,Misc,-99,"RH 60/60, 5-20 kg weight band",1570,1,16.78614 +Imported From One Health,Misc,-99,"RH 60/60, 21-30 kg weight band",1571,1,25.49694 +Imported From One Health,Misc,-99,RHE 150/75/275,1572,1,35.28588 +Imported From One Health,Misc,-99,RHZ 60/30/150,1573,1,18.78534 +Imported From One Health,Misc,-99,RHZE,1574,1,43.25412 +Imported From One Health,Misc,-99,RHZE 150/75/400/275,1575,1,35.92134 +Imported From One Health,Misc,-99,Rifabutine 150 mg,1576,1,607.1142 +Imported From One Health,Misc,-99,Rifampicin,1577,1,60.69 +Imported From One Health,Misc,-99,Rifampicin - for laboratory use (1g),1578,1,108528 +Imported From One Health,Misc,-99,S1,1579,1,456.96 +Imported From One Health,Misc,-99,"Sertraline, 50 mg tab",1580,1,0 +Imported From One Health,Misc,-99,Shoe cover,1581,1,16.3149 +Imported From One Health,Misc,-99,Single use plastic Pasteur-pipettes sterile individually packed,1582,1,63.74592 +Imported From One Health,Misc,-99,"Single use syringes, sterile",1583,1,51.5508 +Imported From One Health,Misc,-99,Single-use paper towels,1584,1,10859.94 +Imported From One Health,Misc,-99,Spironolactone 25 mg,1585,1,30.8448 +Imported From One Health,Misc,-99,"Sterile, DNA-/RNAse-free TIPS, 10 - 100 µl",1586,1,54.10692 +Imported From One Health,Misc,-99,Streptomycin,1587,1,456.96 +Imported From One Health,Misc,-99,"Syringe filter for single use, sterile",1588,1,1726.0236 +Imported From One Health,Misc,-99,Terizidone 250 mg,1589,1,1189.524 +Imported From One Health,Misc,-99,Thioacetazone 150 mg,1590,1,0 +Imported From One Health,Misc,-99,Thorazine,1591,1,0 +Imported From One Health,Misc,-99,"TIPS, PP, 100-1000 ?l, sterile, autoclavable with Filter",1592,1,43.86102 +Imported From One Health,Misc,-99,Transparent polypropylene bag,1593,1,125.63544 +Imported From One Health,Misc,-99,tri-Magnesium di-citrate nonahydrate,1594,1,292740 +Imported From One Health,Misc,-99,"Valproic acid, 200 mg",1595,1,125.307 +Imported From One Health,Misc,-99,"Vitamine B6, 25 mg",1596,1,4.2126 +Imported From One Health,Misc,-99,Waste containers for sharps,1597,1,1150.254 +Imported From One Health,Misc,-99,Xpert MTB/RIF kit of 50 tests,1598,1,7125.72 +Imported From One Health,Misc,-99,Z400,1599,1,16.78614 +Imported From One Health,Misc,-99,"Nausea, vomiting, upset stomach",1600,1,343878.3936 +Imported From One Health,Misc,-99,"Heartburn, acid indigestion, sour stomach, ulcer",1601,1,2159.136 +Imported From One Health,Misc,-99,Oral candidiasis,1602,1,6837.264 +Imported From One Health,Misc,-99,Diarrhea,1603,1,5517.792 +Imported From One Health,Misc,-99,Depression,1604,1,8972.4096 +Imported From One Health,Misc,-99,Severe anxiety,1605,1,14490.2016 +Imported From One Health,Misc,-99,Insomnia,1606,1,2399.04 +Imported From One Health,Misc,-99,Psychosis,1607,1,3454.6176 +Imported From One Health,Misc,-99,Seizures,1608,1,11635.344 +Imported From One Health,Misc,-99,Prophylaxis of neurological complications of cycloserine and isoniazid,1609,1,22646.9376 +Imported From One Health,Misc,-99,Peripheral neuropathy,1610,1,4318.272 +Imported From One Health,Misc,-99,Vestibular symptoms,1611,1,14394.24 +Imported From One Health,Misc,-99,"Musculoskeletal pain, arthralgia, headaches",1612,1,0 +Imported From One Health,Misc,-99,Systemic hypersensitivity reactions,1613,1,1673.3304 +Imported From One Health,Misc,-99,Bronchospasm,1614,1,4948.02 +Imported From One Health,Misc,-99,Hypothyroidism,1615,1,3310.6752 +Imported From One Health,Misc,-99,Abdominal pain,1616,1,11407.4352 +Imported From One Health,Misc,-99,Tinnitus,1617,1,14394.24 +Imported From One Health,Misc,-99,Renal failure/nephrotoxicity,1618,1,1004.598 +Imported From One Health,Misc,-99,"Capreomycin (CM), 1g",1619,1,214285.68 +Imported From One Health,Misc,-99,Bedaquiline 100 mg,1620,1,11393.6193 +Imported From One Health,Misc,-99,6 Am-Lfx-Eto-Cs-Z/14 Lfx-Eto-Cs-Z,1621,1,632604 +Imported From One Health,Misc,-99,6 Km-Lfx-Pto-Cs-Z/12 Lfx-Pto-Cs-Z,1622,1,766836 +Imported From One Health,Misc,-99,6 Km-Lfx-Eto-Cs-Z-(E) / 12 Lfx-Eto-Cs-Z-(E),1623,1,774690 +Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs/12Z-Lfx-Eto-Cs,1624,1,882504 +Imported From One Health,Misc,-99,8 Km-Pto-Lfx-Cs-Z/12 Pto-Lfx-Cs-Z,1625,1,931056 +Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs / 16 Z-Lfx-Eto-Cs,1626,1,971040 +Imported From One Health,Misc,-99,8 Km-Lfx-Pto-Cs-Z-E/14 Lfx-Pto-Cs-Z-E,1627,1,1030302 +Imported From One Health,Misc,-99,6 Km-Lfx-Eto-Cs-Z-E/18 Lfx-Eto-Cs-E,1628,1,1042440 +Imported From One Health,Misc,-99,9 Z-Km-Lfx-Eto-Cs/15 Lfx-Eto-Cs-Z,1629,1,1140972 +Imported From One Health,Misc,-99,8 Z-Cm-Lfx-Pto-Cs / 12 Z-Lfx-Pto-Cs,1630,1,1189524 +Imported From One Health,Misc,-99,8 Cm-Pto-Lfx-Cs-Z/12 Pto-Lfx-Cs-Z,1631,1,1189524 +Imported From One Health,Misc,-99,8 Cm-Eto-Lfx-Cs-Z-E/16 Eto-Lfx-Cs-Z-E,1632,1,1276632 +Imported From One Health,Misc,-99,9 Km-Lfx-Eto-Cs-Z-E/18 Lfx-Eto-Cs-E,1633,1,1292340 +Imported From One Health,Misc,-99,8 Z-E-Cm-Lfx-Pto-Cs/14 E-Z-Lfx-Pto-Cs,1634,1,1295196 +Imported From One Health,Misc,-99,6 Am-Lfx-Eto-Cs-PAS-Z/14 Lfx-Eto-Cs-PAS-Z,1635,1,1929942 +Imported From One Health,Misc,-99,8 Z-Km-Lfx-Eto-Cs-PAS/12 Z-Lfx-Eto-PAS-Cs,1636,1,2179842 +Imported From One Health,Misc,-99,8 Am-Lfx-Eto-Cs-Z-PAS/16 Lfx-Eto-Cs-Z-PAS,1637,1,2341206 +Imported From One Health,Misc,-99,8 Cm-Lfx-Eto-PAS-Cs-Z/12 Lfx-Eto-PAS-Cs-Z,1638,1,2444022 +Imported From One Health,Misc,-99,12 Z-Ami-Lfx-Eto-Cs-PAS / 12 Z-Lfx-Eto-Cs-PAS,1639,1,2467584 +Imported From One Health,Misc,-99,12 Z-Am-Pto-Cs-PAS-Lfx/12 Z-Pto-Cs-PAS-Lfx,1640,1,2518992 +Imported From One Health,Misc,-99,8 Cm-Mfx-Eto-PAS-Cs-Z-AmxClv/12 Mfx-Eto-PAS-Cs-Z-AmxClv,1641,1,2726052 +Imported From One Health,Misc,-99,12 Z-Km-Lfx-Pto-Cs-PAS / 12 Z-Lfx-Pto-Cs-PAS,1642,1,2798880 +Imported From One Health,Misc,-99,8 ?m-Lfx-?s-Pto-Z-PAS / 16 Lfx-?s-Pto-Z-PAS,1643,1,2843862 +Imported From One Health,Misc,-99,11Cm-Lfx-Pto-Cs-Z-PAS/13Lfx-Pto-Cs-Z-PAS,1644,1,3107328 +Imported From One Health,Misc,-99,12 Z-Cm-Lfx-Pto-Cs-PAS / 12 Z-Lfx-Pto-Cs-PAS,1645,1,3195150 +Imported From One Health,Misc,-99,12 Z-Cm-Pto-Cs-PAS-Lfx/12 Z-Pto-Cs-PAS-Lfx,1646,1,3195150 +Imported From One Health,Misc,-99,"Protionamid (PTH), 2g",1647,1,91584.78 +Imported From One Health,Misc,-99,"Vitamine B6, 15 mg",1648,1,4.2126 +Imported From One Health,Misc,-99,TB Patient support - Incentive or enabler,1649,1,0 +Imported From One Health,Misc,-99,TB Patient support - Food voucher,1650,1,0 +Imported From One Health,Misc,-99,TB Patient support - Transport voucher,1651,1,0 +Imported From One Health,Misc,-99,TB Patient support - Mobile phone air-time,1652,1,0 +Imported From One Health,Misc,-99,Palliative care for TB patients,1653,1,0 +Imported From One Health,Misc,-99,Total bilirubin,1654,1,258.468 +Imported From One Health,Misc,-99,"Electrosurgical unit (monopolar pen, pad)",1655,1,2413.32 +Imported From One Health,Misc,-99,"Skin preparatory solution, 500 ml vial",1656,1,7.14 +Imported From One Health,Misc,-99,"Cefazolin, 1g",1657,1,307.02 +Imported From One Health,Misc,-99,Paclitaxel,1658,1,7332.78 +Imported From One Health,Misc,-99,"Formalin, 1 liter",1659,1,521.22 +Imported From One Health,Misc,-99,H and E staining,1660,1,357 +Imported From One Health,Misc,-99,Hormone receptor testing (immunoanalyzer),1661,1,17778.6 +Imported From One Health,Misc,-99,Electrolytes test,1662,1,3191.58 +Imported From One Health,Misc,-99,BUN test,1663,1,1861.398 +Imported From One Health,Misc,-99,Serum creatinine,1664,1,1535.1 +Imported From One Health,Misc,-99,Ultrasound gel,1665,1,147.798 +Imported From One Health,Misc,-99,Ultrasound probe cover,1666,1,5090.82 +Imported From One Health,Misc,-99,Filgastrim,1667,1,94.01238 +Imported From One Health,Misc,-99,Ondansetron (4mg tablets),1668,1,379.2054 +Imported From One Health,Misc,-99,"Alendronate, 10 mg tab",1669,1,43.2684 +Imported From One Health,Misc,-99,"Ibuprofen, 400 mg tab",1670,1,7.854 +Imported From One Health,Misc,-99,Morphine injection (5mL),1671,1,2170.56 +Imported From One Health,Misc,-99,Morphine oral liquid (10mg/mL),1672,1,107.1 +Imported From One Health,Misc,-99,Morphine slow release tablet (10mg),1673,1,578.34 +Imported From One Health,Misc,-99,Dexamethasone (4mg tablets),1674,1,42.84 +Imported From One Health,Misc,-99,Docusate (100mg tablet),1675,1,114.24 +Imported From One Health,Misc,-99,"Senna, 7.5 mg tab",1676,1,7.9968 +Imported From One Health,Misc,-99,Metoclopramide (10mg tablet),1677,1,4.4982 +Imported From One Health,Misc,-99,Amitriptyline(25 mg tab),1678,1,5.1408 +Imported From One Health,Misc,-99,"Haloperidol (oral liquid, 2mg) ",1679,1,22.2054 +Imported From One Health,Misc,-99,HER2 amplification (immunoanalyzer),1680,1,53978.4 +Imported From One Health,Misc,-99,"Trastuzamab, 1 mg",1681,1,3048.78 +Imported From One Health,Misc,-99,Mammography film,1682,1,456.96 +Imported From One Health,Misc,-99,Mammography film chemistry,1683,1,45.696 +Imported From One Health,Misc,-99,Wire localization needle,1684,1,54935.16 +Imported From One Health,Misc,-99,Soft tissue marker/fiduciary clip,1685,1,0 +Imported From One Health,Misc,-99,"Pipette, repeater",1686,1,28.56 +Imported From One Health,Misc,-99,Pipette tips,1687,1,28.56 +Imported From One Health,Misc,-99,Repeater tips,1688,1,28.56 +Imported From One Health,Misc,-99,CareHPV Test Kit,1689,1,6725.88 +Imported From One Health,Misc,-99,IEC materials,1690,1,714 +Imported From One Health,Misc,-99,Data collection forms,1691,1,142.8 +Imported From One Health,Misc,-99,"Azithromycin, 500 mg",1692,1,228.48 +Imported From One Health,Misc,-99,"Cefrriaxone, powder for infection, 250 ml vial",1693,1,171.36 +Imported From One Health,Misc,-99,"Acetic acid, 5% dilute, 5 ml",1694,1,228.48 +Imported From One Health,Misc,-99,KY jelly packet,1695,1,134.232 +Imported From One Health,Misc,-99,"70 isopropyl alcohol, 10 ml",1696,1,592.62 +Imported From One Health,Misc,-99,"Soap or hand sanitizer, 1L",1697,1,7854 +Imported From One Health,Misc,-99,Cervical cytology brush/scraper,1698,1,541.0692 +Imported From One Health,Misc,-99,"Monsel's solution, 1 ml",1699,1,92.82 +Imported From One Health,Misc,-99,"Lugol's solution, 1 ml",1700,1,594.048 +Imported From One Health,Misc,-99,"Compressed gas, 25 kg cylinder",1701,1,49980 +Imported From One Health,Misc,-99,"Cryotherapy unit with cryotips, use for one patient",1702,1,42.84 +Imported From One Health,Misc,-99,Gas cylinder adapter,1703,1,7140 +Imported From One Health,Misc,-99,"Syringe, 5 cc with needle",1704,1,397.6266 +Imported From One Health,Misc,-99,Cauterizer,1705,1,5069.4 +Imported From One Health,Misc,-99,IV contrast,1706,1,178.5 +Imported From One Health,Misc,-99,Vaginal estrogen,1707,1,14280 +Imported From One Health,Misc,-99,"Gauze pad, 10X4 cm",1708,1,107.1 +Imported From One Health,Misc,-99,"Cidex 2-4% glutaraldehyde (cl), 100ml",1709,1,199.92 +Imported From One Health,Misc,-99,"Needle, spinal, 22g (disposable)",1710,1,642.6 +Imported From One Health,Misc,-99,Electrosurgical pen,1711,1,2413.32 +Imported From One Health,Misc,-99,Perthodine (cl),1712,1,21.42 +Imported From One Health,Misc,-99,Definitive radiotherapy (50Gy in 25 fractions),1713,1,53907 +Imported From One Health,Misc,-99,Cisplatin (50 mg tab),1714,1,4783.8 +Imported From One Health,Misc,-99,"Forceps, punch biopsy",1715,1,28167.3 +Imported From One Health,Misc,-99,"Forceps, sponge holder",1716,1,9032.1 +Imported From One Health,Misc,-99,FIT test set,1717,1,1949.22 +Imported From One Health,Misc,-99,FOBT test set,1718,1,4069.8 +Imported From One Health,Misc,-99,Phosphate enema,1719,1,1128.12 +Imported From One Health,Misc,-99,"Midazolam, 1 mg",1720,1,208.6308 +Imported From One Health,Misc,-99,"GoLytely (PEG 3350 + electrolytes), 4 L",1721,1,99.96 +Imported From One Health,Misc,-99,Diagnosis of colorectal cancer ,1722,1,18421.2 +Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 1,1723,1,72828 +Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 2,1724,1,351288 +Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 3,1725,1,1118838 +Imported From One Health,Misc,-99,Colorectal cancer treatment: stage 4,1726,1,334866 +Imported From One Health,Misc,-99,Rectal cancer treatment: Stage 1,1727,1,73756.2 +Imported From One Health,Misc,-99,Rectal cancer treatment: stage 2,1728,1,808947.72 +Imported From One Health,Misc,-99,Rectal cancer treatment: stage 3,1729,1,1925715.12 +Imported From One Health,Misc,-99,Rectal cancer treatment: stage 4,1730,1,263894.4 +Imported From One Health,Misc,-99,CEA test,1731,1,8518.02 +Imported From One Health,Misc,-99,Distance chart per 200 patients,1732,1,1606.5 +Imported From One Health,Misc,-99,Vision chart per 200 patients,1733,1,499.8 +Imported From One Health,Misc,-99,Illuminated chart per 200 patients,1734,1,17850 +Imported From One Health,Misc,-99,"Praziquantel, 600 mg (donated)",1735,1,0 +Imported From One Health,Misc,-99,"Mebendazole, 500 mg tab",1736,1,74.97 +Imported From One Health,Misc,-99,"Albendazole, tablet, 400 mg (donated)",1737,1,0 +Imported From One Health,Misc,-99,"Mebendazole, 500 mg tab (donated)",1738,1,0 +Imported From One Health,Misc,-99,"Ivermectin, 3 mg",1739,1,36.414 +Imported From One Health,Misc,-99,"Ivermectin, 3 mg (donated)",1740,1,0 +Imported From One Health,Misc,-99,"Diethylcarbamazine citrate, 100 mg tab",1741,1,3.927 +Imported From One Health,Misc,-99,"Diethylcarbamazine citrate, 100 mg tab (donated)",1742,1,0 +Imported From One Health,Misc,-99,"Azithromycin, 250 mg tab",1743,1,83.538 +Imported From One Health,Misc,-99,"Rifampicin, 300 mg tab",1744,1,85.1088 +Imported From One Health,Misc,-99,"Clarithromycin, 1 ml",1745,1,23.205 +Imported From One Health,Misc,-99,"Sodium Stibogluconate (100 mg/ml), 30 ml vial",1746,1,7389.9 +Imported From One Health,Misc,-99,"Meglumine antimonate (81 mg/ml), 5 ml ampoule",1747,1,0 +Imported From One Health,Misc,-99,"Pentamidine, 200 mg",1748,1,8246.7 +Imported From One Health,Misc,-99,rK39 rapid diagnostic test,1749,1,1213.8 +Imported From One Health,Misc,-99,"liposomal amphotericin B (Ambisome), 50 mg vial",1750,1,11602.5 +Imported From One Health,Misc,-99,"Miltefosine (Impavido), capsule, 50 mg",1751,1,0 +Imported From One Health,Misc,-99,Paromomycin (750 mg/2 ml),1752,1,0 +Imported From One Health,Misc,-99,"Kit NECT (Nifurtimox, 120 mg + Eflornithine (200 mg/ml), 100 ml ampoule)",1753,1,32744.04 +Imported From One Health,Misc,-99,Card Agglutination Trypanosomiasis Test (CATT),1754,1,371.28 +Imported From One Health,Misc,-99,MAECT,1755,1,2363.34 +Imported From One Health,Misc,-99,"Suramine, powder for injection, 1 g",1756,1,4319.7 +Imported From One Health,Misc,-99,"Melarsoprol (36 mg/ml), 5 ml vial",1757,1,5997.6 +Imported From One Health,Misc,-99,Lumbar puncture,1758,1,6704.46 +Imported From One Health,Misc,-99,"Dapsone, 100 mg tab",1759,1,178.5 +Imported From One Health,Misc,-99,"Benznidazole, 100 mg",1760,1,428.4 +Imported From One Health,Misc,-99,"Lidocaine HCL 2%, 20 ml ampule",1761,1,314.16 +Imported From One Health,Misc,-99,"Needle (disposable), 21g",1762,1,142.8 +Imported From One Health,Misc,-99,Yaws point of care test,1763,1,1428 +Imported From One Health,Misc,-99,"Actellic, 1 g",1764,1,7.14 +Imported From One Health,Misc,-99,"Deltamethrine, 100 ml",1765,1,2142 +Imported From One Health,Misc,-99,Beta-cypermethrine,1766,1,0 +Imported From One Health,Misc,-99,"Rabies vaccine, 1 ml (canine)",1767,1,178.5 +Imported From One Health,Misc,-99,"Rabies post exposure prophylaxis, 1 vial, .5 ml",1768,1,11159.82 +Imported From One Health,Misc,-99,"Rifampicin, 600 mg tab",1769,1,60.69 +Imported From One Health,Misc,-99,Thioridazine 50mg_1000_CMST,1770,1,64438.75704 +Imported From One Health,Misc,-99,Thioridazine 25mg_1000_CMST,1771,1,50500.28466 +Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (12+12s)_100_CMST,1772,1,39527.94678 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x24_720_CMST",1773,1,32988.20658 +Imported From One Health,Misc,-99,Lorazepam 1mg_100_CMST,1774,1,23890.46142 +Imported From One Health,Misc,-99,"Vitamin A 200,000 IU_1000_CMST",1775,1,23002.99512 +Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (6+6s)_100_CMST,1776,1,21417.8937 +Imported From One Health,Misc,-99,"Vitamin A 100,000 IU_1000_CMST",1777,1,17621.2344 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x12_360_CMST",1778,1,17436.14418 +Imported From One Health,Misc,-99,Mebendazole 500mg_1000_CMST,1779,1,15485.61756 +Imported From One Health,Misc,-99,Doxycycline 100mg_1000_CMST,1780,1,12960.83502 +Imported From One Health,Misc,-99,Artesunate 50mg+Amodiaquine 153mg(base) (3+3s)_100_CMST,1781,1,12396.08244 +Imported From One Health,Misc,-99,Azithromycin 250mg_100_CMST,1782,1,12210.99936 +Imported From One Health,Misc,-99,Morphine sulphate 10mg (slow release)_60_CMST,1783,1,11233.362 +Imported From One Health,Misc,-99,Norethisterone 5mg_100_CMST,1784,1,10194.02076 +Imported From One Health,Misc,-99,Penicillin V 250mg_1000_CMST,1785,1,9415.71078 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x6_180_CMST",1786,1,8718.07566 +Imported From One Health,Misc,-99,Nicotinamide 50mg_1000_CMST,1787,1,7626.53388 +Imported From One Health,Misc,-99,Imipramine Hcl 10mg_1000_CMST,1788,1,5082.77322 +Imported From One Health,Misc,-99,Hydrocortisone acetate 20mg_100_CMST,1789,1,5054.2989 +Imported From One Health,Misc,-99,Atenolol 50mg_1000_CMST,1790,1,4143.09924 +Imported From One Health,Misc,-99,Dexamethasone 0.5mg_1000_CMST,1791,1,3991.23858 +Imported From One Health,Misc,-99,Acyclovir 400mg_100_CMST,1792,1,3796.6593 +Imported From One Health,Misc,-99,Nitrofurantoin 50mg_250_CMST,1793,1,3611.56908 +Imported From One Health,Misc,-99,Fluconazole 200mg_100_CMST,1794,1,3597.33192 +Imported From One Health,Misc,-99,Cephalexin 250mg_100_CMST,1795,1,3549.87234 +Imported From One Health,Misc,-99,Bisacodyl 5mg_1000_CMST,1796,1,3241.39578 +Imported From One Health,Misc,-99,Ibuprofen 200mg_1000_CMST,1797,1,3184.44714 +Imported From One Health,Misc,-99,Spironolactone 25mg_100_CMST,1798,1,2747.829 +Imported From One Health,Misc,-99,Pyridoxine (Vitamin B6) 20mg_1000_CMST,1799,1,2700.36942 +Imported From One Health,Misc,-99,Phenobarbitone 30mg_1000_CMST,1800,1,2671.8951 +Imported From One Health,Misc,-99,Acyclovir 200mg_100_CMST,1801,1,2501.04918 +Imported From One Health,Misc,-99,Aminophylline 100mg_1000_CMST,1802,1,2353.92948 +Imported From One Health,Misc,-99,Propranolol hydrochloride 40mg_1000_CMST,1803,1,2339.69232 +Imported From One Health,Misc,-99,Allopurinol 100mg_100_CMST,1804,1,2197.31358 +Imported From One Health,Misc,-99,Chlorpromazine 25mg_100_CMST,1805,1,2140.36494 +Imported From One Health,Misc,-99,Metformin hydrochloride 850mg_100_CMST,1806,1,2140.36494 +Imported From One Health,Misc,-99,Phenytoin sodium 25mg_1000_CMST,1807,1,2140.36494 +Imported From One Health,Misc,-99,Ferrous sulphate 200mg / folic acid 250 micrograms_1000_CMST,1808,1,2007.4824 +Imported From One Health,Misc,-99,Acetazolamide 250mg_100_CMST,1809,1,1969.51188 +Imported From One Health,Misc,-99,Loperamide HCl 2mg_1000_CMST,1810,1,1950.53376 +Imported From One Health,Misc,-99,Zinc sulphate 20mg _100_CMST,1811,1,1941.0447 +Imported From One Health,Misc,-99,Ketoconazole 200mg_100_CMST,1812,1,1912.56324 +Imported From One Health,Misc,-99,Indomethacin 25mg_1000_CMST,1813,1,1570.86426 +Imported From One Health,Misc,-99,Captopril 12.5mg_100_CMST,1814,1,1314.59538 +Imported From One Health,Misc,-99,Haloperidol 2mg_100_CMST,1815,1,1305.09918 +Imported From One Health,Misc,-99,Griseofulvin 125mg_100_CMST,1816,1,1286.12106 +Imported From One Health,Misc,-99,Benzhexol 5mg_100_CMST,1817,1,1034.586 +Imported From One Health,Misc,-99,Cimetidine 400mg_100_CMST,1818,1,783.05808 +Imported From One Health,Misc,-99,Atenolol 100mg_100_CMST,1819,1,522.0411 +Imported From One Health,Misc,-99,Hydrochlorothiazide 25mg_100_CMST,1820,1,436.61814 +Imported From One Health,Misc,-99,Atenolol 50mg_100_CMST,1821,1,412.88478 +Imported From One Health,Misc,-99,Dexamethasone 0.5mg_100_CMST,1822,1,393.89952 +Imported From One Health,Misc,-99,"Aminophylline 25mg/ml, 10ml_each_CMST",1823,1,327.46182 +Imported From One Health,Misc,-99,"Cefotaxime 500mg, PFR_each_CMST",1824,1,137.63064 +Imported From One Health,Misc,-99,"Ceftriaxone 250mg, PFR_each_CMST",1825,1,208.131 +Imported From One Health,Misc,-99,"Chlorpromazine hydrochloride 25mg/ml, 2ml_each_CMST",1826,1,1290.86202 +Imported From One Health,Misc,-99,"Dexamethasone 5mg/ml, 5ml_each_CMST",1827,1,199.32738 +Imported From One Health,Misc,-99,"Dextrose (glucose) 5%, 500ml_each_CMST",1828,1,408.14382 +Imported From One Health,Misc,-99,"Dextrose 50%, 50ml_each_CMST",1829,1,384.41046 +Imported From One Health,Misc,-99,"Ergometrine maleate 500mcg/ml + Oxytocin 10IU/ml, 1ml_each_CMST",1830,1,151.8678 +Imported From One Health,Misc,-99,"Flucloxacillin 250mg, vial, PFR_each_CMST",1831,1,341.69898 +Imported From One Health,Misc,-99,"Frusemide 10mg/ml, 2ml_each_CMST",1832,1,71.1858 +Imported From One Health,Misc,-99,"Gentamicin Sulphate 10mg/ml, 2ml_each_CMST",1833,1,99.66012 +Imported From One Health,Misc,-99,"Haloperidol 5mg/ml, 2ml_each_CMST",1834,1,578.98974 +Imported From One Health,Misc,-99,"Hydralazine hydrochloride 20mg/ml, 1ml_each_CMST",1835,1,991.87452 +Imported From One Health,Misc,-99,"Hydrocortisone sodium succinate iv 50mg/ml, 2ml_each_CMST",1836,1,341.69898 +Imported From One Health,Misc,-99,"Lignocaine hydrochloride 1%, 25ml_each_CMST",1837,1,151.8678 +Imported From One Health,Misc,-99,"Magnesium sulphate 50%, 2ml ampoule_each_CMST",1838,1,50.10852 +Imported From One Health,Misc,-99,"Medroxyprogesterone acetate injection 150mg/mL, 1mL vial with 2ml syringe with 22g 0.7 X 25mm needle_each_CMST",1839,1,783.05808 +Imported From One Health,Misc,-99,"Morphine sulphate 15mg/ml, 1ml_each_CMST",1840,1,180.34212 +Imported From One Health,Misc,-99,"Paraldehyde, 10ml_each_CMST",1841,1,28403.7411 +Imported From One Health,Misc,-99,"Phenobarbitone sodium 200mg/ml, 1ml_each_CMST",1842,1,422.38098 +Imported From One Health,Misc,-99,"Phytomenadione 2mg/ml, 1ml (Vitamin K)_each_CMST",1843,1,370.1733 +Imported From One Health,Misc,-99,"Promethazine hydrochloride 25mg/ml, 2ml_each_CMST",1844,1,455.59626 +Imported From One Health,Misc,-99,"Sodium chloride 0.9%, 500ml_each_CMST",1845,1,336.95088 +Imported From One Health,Misc,-99,"Sodium lactate + glucose (darrows half-strength in dextrose 5%), 1000ml_each_CMST",1846,1,479.32962 +Imported From One Health,Misc,-99,"Suxamethonium chloride 50mg/ml, 2ml_each_CMST",1847,1,541.02636 +Imported From One Health,Misc,-99,"Thiopentone sodium 500mg, PFR_each_CMST",1848,1,541.02636 +Imported From One Health,Misc,-99,Vincristine sulphate 1mg PFR_each_CMST,1849,1,1414.2555 +Imported From One Health,Misc,-99,"Water for injections, 10ml_each_CMST",1850,1,42.71148 +Imported From One Health,Misc,-99,"Hepatitis B vaccine, 20mcg/ml, 1ml vial_each_CMST",1851,1,1162.72758 +Imported From One Health,Misc,-99,"Rabies vaccine course, (1x 5, 0.5ml/dose PFR &_x000B_ diluent x 5 vials)_each_CMST",1852,1,40377.4497 +Imported From One Health,Misc,-99,Tetanus antitoxin 1500 IU_each_CMST,1853,1,1680.02058 +Imported From One Health,Misc,-99,Acetone_5_CMST,1854,1,5956.00236 +Imported From One Health,Misc,-99,Benzoic acid_500_CMST,1855,1,1665.78342 +Imported From One Health,Misc,-99,Calamine_25Kg_CMST,1856,1,103672.4644 +Imported From One Health,Misc,-99,Emulsifying wax _25kg_CMST,1857,1,77261.96856 +Imported From One Health,Misc,-99,Formaldehyde liquid 40%_5L_CMST,1858,1,25916.92908 +Imported From One Health,Misc,-99,Halothane _0.333333333333333_CMST,1859,1,30415.96446 +Imported From One Health,Misc,-99,Iodine_1kg_CMST,1860,1,78818.59566 +Imported From One Health,Misc,-99,Potassium iodide_1kg_CMST,1861,1,32138.70366 +Imported From One Health,Misc,-99,Salicylic acid_25_CMST,1862,1,267042.6116 +Imported From One Health,Misc,-99,Sodium citrate_500g_CMST,1863,1,6568.21452 +Imported From One Health,Misc,-99,Sodium nitrate_100g_CMST,1864,1,8903.15874 +Imported From One Health,Misc,-99,Sodium thiosulphate_500g_CMST,1865,1,2572.23498 +Imported From One Health,Misc,-99,Zinc oxide_25_CMST,1866,1,124406.953 +Imported From One Health,Misc,-99,Acyclovir eye ointment 3%_5_CMST,1867,1,1219.67622 +Imported From One Health,Misc,-99,Atropine sulphate eye ointment 1%_3.5g_CMST,1868,1,341.69898 +Imported From One Health,Misc,-99,Calamine lotion + sulphur 2%_1_CMST,1869,1,1034.586 +Imported From One Health,Misc,-99,Calamine lotion aqueous_1_CMST,1870,1,930.17778 +Imported From One Health,Misc,-99,Cetrimide 15% + chlorhexidine 1.5% solution.for dilution _5_CMST,1871,1,15243.5787 +Imported From One Health,Misc,-99,Chloramphenicol 1% eye ointment_3.5_CMST,1872,1,194.57928 +Imported From One Health,Misc,-99,Chloramphenicol 125mg/5ml suspension_1_CMST,1873,1,569.50068 +Imported From One Health,Misc,-99,Chloramphenicol ear drops 5%_5ml_CMST,1874,1,227.8017 +Imported From One Health,Misc,-99,Chloramphenicol eye drops 0.5%_1_CMST,1875,1,256.27602 +Imported From One Health,Misc,-99,Chlorpheniramine 2mg/5ml suspension_100_CMST,1876,1,223.0536 +Imported From One Health,Misc,-99,Cotrimoxazole 240mg/5ml_100_CMST,1877,1,469.83342 +Imported From One Health,Misc,-99,Dextrose monohydrate (glucose)_500g_CMST,1878,1,2353.92948 +Imported From One Health,Misc,-99,Emulsifying ointment_500g_CMST,1879,1,2690.88036 +Imported From One Health,Misc,-99,Gentamicin 0.3% eye drops_5ml_CMST,1880,1,251.52792 +Imported From One Health,Misc,-99,Glycerine_0.5_CMST,1881,1,1504.42656 +Imported From One Health,Misc,-99,Hydrocortisone eye ointment 1%_3.5g_CMST,1882,1,355.93614 +Imported From One Health,Misc,-99,Hydrocortisone skin ointment 1%_1_CMST,1883,1,393.89952 +Imported From One Health,Misc,-99,Ketoconazole suspension 100mg/5ml_100ml_CMST,1884,1,892.2144 +Imported From One Health,Misc,-99,"Lignocaine gel 2%, 30g_1_CMST",1885,1,987.13356 +Imported From One Health,Misc,-99,Metronidazole oral suspension 200mg /5ml_100 ml_CMST,1886,1,375.79962 +Imported From One Health,Misc,-99,"Nystatin oral suspension 100,000 IU/ml_20_CMST",1887,1,550.51542 +Imported From One Health,Misc,-99,Povidone iodine 10% in alcoholic solution_500ml_CMST,1888,1,2733.59184 +Imported From One Health,Misc,-99,Salbutamol solution for nebulising 5mg/ml_30ml_CMST,1889,1,726.10944 +Imported From One Health,Misc,-99,"Salbutamol sulphate aerosol inhalation, 100mcg/dose, 200 doses _each_CMST",1890,1,1219.67622 +Imported From One Health,Misc,-99,Salicylic acid 5% + sulphur 5% ointment (in EO base)_500g_CMST,1891,1,3208.17336 +Imported From One Health,Misc,-99,Silver nitrate stick pencil (toughened)_each_CMST,1892,1,522.0411 +Imported From One Health,Misc,-99,Silver sulphadiazine cream 1% 50G_1_CMST,1893,1,479.32962 +Imported From One Health,Misc,-99,Tetracycline eye ointment 1%_3.5_CMST,1894,1,408.14382 +Imported From One Health,Misc,-99,"Vitamin, multiple syrup_100ml_CMST",1895,1,441.3591 +Imported From One Health,Misc,-99,Zinc oxide & salicylic acid paste BP (Lassar's)_500g_CMST,1896,1,3369.53022 +Imported From One Health,Misc,-99,Zinc oxide 15% ointment (in EO base)_5_CMST,1897,1,3250.88484 +Imported From One Health,Misc,-99,Zinc oxide 15% ointment +sulphur 5%_5_CMST,1898,1,2168.83926 +Imported From One Health,Misc,-99,"Bandage, crepe 10cm 1.4m long (4m when stretched)_each_CMST",1899,1,322.71372 +Imported From One Health,Misc,-99,"Bandage, plaster of paris 10cm_12_CMST",1900,1,5495.658 +Imported From One Health,Misc,-99,"Bandage, WOW 10cm x 4m _10_CMST",1901,1,612.21216 +Imported From One Health,Misc,-99,"Dressing, paraffin gauze 9.5cm x 9.5cm (square)_pack_x000B_of 36_CMST",1902,1,1034.586 +Imported From One Health,Misc,-99,"Gauze, absorbent 90cm X 100m_each_CMST",1903,1,12002.18292 +Imported From One Health,Misc,-99,Plaster of Paris (POP) 7.5cm x 7.5cm slab_12_CMST,1904,1,4712.59992 +Imported From One Health,Misc,-99,Plaster of Paris (POP) 12.5cm x 7.5cm slab_12_CMST,1905,1,7066.5294 +Imported From One Health,Misc,-99,"Plaster, extension 7.5cm x 5m_each_CMST",1906,1,707.12418 +Imported From One Health,Misc,-99,"Plaster, zinc oxide 5cm x 5m_each_CMST",1907,1,522.0411 +Imported From One Health,Misc,-99,"Plaster, zinc oxide 7.5cm x 5m_each_CMST",1908,1,863.74008 +Imported From One Health,Misc,-99,Braided synthetic sterile polyglyctin 3/0 round bodied needle cc 1/2 circle 20mm_12_CMST,1909,1,27402.37038 +Imported From One Health,Misc,-99,Polyglycolic Acid (0) round bodied needle cc ½ circle 20mm _12_CMST,1910,1,6753.30474 +Imported From One Health,Misc,-99,Catgut chromic 2/0 needle round bodied ½ circle 35mm_12_CMST,1911,1,24754.2015 +Imported From One Health,Misc,-99,Catgut chromic 3/0 needle round bodied ½ circle 25mm_12_CMST,1912,1,21099.92094 +Imported From One Health,Misc,-99,"Silk (3/0), 2.0 gauge on 1/2 circle round bodied needle 75cm on 36mm _12_CMST",1913,1,55255.59606 +Imported From One Health,Misc,-99,Black braided non absorbable sterile silk 2/0 on needle cc 40mm_12_CMST,1914,1,8461.79964 +Imported From One Health,Misc,-99,Black braided non absorbable sterile silk 4/0 on needle cc 25mm_12_CMST,1915,1,76047.04044 +Imported From One Health,Misc,-99,Airway disposable PVC/Silicon size 2_each_CMST,1916,1,484.07058 +Imported From One Health,Misc,-99,"Bags urine drainage 2,000ml with outlet_each_CMST",1917,1,157.40844 +Imported From One Health,Misc,-99,Cannula iv (winged with injection pot) 22_each_CMST,1918,1,199.32738 +Imported From One Health,Misc,-99,Cannula iv (winged with injection pot) 24_each_CMST,1919,1,199.32738 +Imported From One Health,Misc,-99,Catheter disposable female FG 14_each_CMST,1920,1,341.69898 +Imported From One Health,Misc,-99,Catheter disposable female FG 16_each_CMST,1921,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 12g_each_CMST,1922,1,550.51542 +Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 16g_each_CMST,1923,1,550.51542 +Imported From One Health,Misc,-99,Catheter Foley's + urine bag (2000ml) 18g_each_CMST,1924,1,550.51542 +Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 16_each_CMST,1925,1,450.8553 +Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 24, 3 way_each_CMST",1926,1,341.69898 +Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 26, 3 way_each_CMST",1927,1,436.61814 +Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30c FG 28, 3 way_each_CMST",1928,1,256.27602 +Imported From One Health,Misc,-99,"Catheter Foley's retention 20-30cc FG 20, 3 way_each_CMST",1929,1,944.42208 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 16_each_CMST,1930,1,336.95088 +Imported From One Health,Misc,-99,"Clips, umbilical cord, polythene_each_CMST",1931,1,66.4377 +Imported From One Health,Misc,-99,Giving set paed iv administration + needle 60 drops/ml_each_CMST,1932,1,213.56454 +Imported From One Health,Misc,-99,Glove disposable powdered latex medium_100_CMST,1933,1,2221.04694 +Imported From One Health,Misc,-99,Glove gynaecological elbow length medium_each_CMST,1934,1,1570.86426 +Imported From One Health,Misc,-99,Glove gynaecological elbow length large_each_CMST,1935,1,1570.86426 +Imported From One Health,Misc,-99,Glove surgeon's size 7½ sterile_2_CMST,1936,1,242.03886 +Imported From One Health,Misc,-99,Introducer for catheters_each_CMST,1937,1,944.42208 +Imported From One Health,Misc,-99,Needle disposable Luer 23g x 2.5cm_100_CMST,1938,1,1490.1894 +Imported From One Health,Misc,-99,Plug catheter (spigot) medium_each_CMST,1939,1,156.6159 +Imported From One Health,Misc,-99,"Probe, silver 15cm_each_CMST",1940,1,783.05808 +Imported From One Health,Misc,-99,Scalp vein set disposable Luer 21g_each_CMST,1941,1,42.71148 +Imported From One Health,Misc,-99,Scalp vein set disposable Luer 23g_each_CMST,1942,1,42.71148 +Imported From One Health,Misc,-99,Scalp vein set disposable Luer 25g_each_CMST,1943,1,42.71148 +Imported From One Health,Misc,-99,Scalpel blade size 11 (individually wrapped)_100_CMST,1944,1,2050.19388 +Imported From One Health,Misc,-99,Scalpel blade size 15 (individually wrapped)_100_CMST,1945,1,2515.28634 +Imported From One Health,Misc,-99,Scalpel blade size 20 (individually wrapped)_100_CMST,1946,1,2515.28634 +Imported From One Health,Misc,-99,Scalpel blade size 21 (individually wrapped)_100_CMST,1947,1,2515.28634 +Imported From One Health,Misc,-99,Scalpel blade size 23 (individually wrapped)_100_CMST,1948,1,2515.28634 +Imported From One Health,Misc,-99,Scalpel blade size 24 (individually wrapped)_100_CMST,1949,1,2515.28634 +Imported From One Health,Misc,-99,Sharps disposal receptor_each_CMST,1950,1,450.8553 +Imported From One Health,Misc,-99,Stethoscope foetal (plastic)_each_CMST,1951,1,3924.79374 +Imported From One Health,Misc,-99,Syringe ear metal_each_CMST,1952,1,5505.1542 +Imported From One Health,Misc,-99,Syringe insulin 100 IU with 30g needle _each_CMST,1953,1,284.75034 +Imported From One Health,Misc,-99,"Syringe, 2ml, disposable, hypoluer with 23g needle_each_CMST",1954,1,85.42296 +Imported From One Health,Misc,-99,"Syringe, 2ml, disposable, hypoluer with 25g needle_each_CMST",1955,1,71.1858 +Imported From One Health,Misc,-99,"Syringe, autodestruct, 10ml, disposable with 21g needle_each_CMST",1956,1,113.89728 +Imported From One Health,Misc,-99,"Syringe, autodestruct, 20ml, disposable with 21g needle_each_CMST",1957,1,85.42296 +Imported From One Health,Misc,-99,"Syringe, autodestruct, 2ml, disposable, hypoluer with 23g needle_each_CMST",1958,1,66.4377 +Imported From One Health,Misc,-99,"Syringe, autodestruct, 2ml, disposable, hypoluer with 25g needle_each_CMST",1959,1,52.20054 +Imported From One Health,Misc,-99,"Syringe, autodestruct, 5ml, disposable, hypoluer with 21g needle_each_CMST",1960,1,80.682 +Imported From One Health,Misc,-99,"Syringe,10ml, disposable, hypoluer with 21g needle_each_CMST",1961,1,156.6159 +Imported From One Health,Misc,-99,"Tape, umbilical cotton, 3mm x 20m, non-sterile_Reel_CMST",1962,1,166.10496 +Imported From One Health,Misc,-99,"Tube, endotracheal 15mm size 7_each_CMST",1963,1,783.05808 +Imported From One Health,Misc,-99,"Tube, endotracheal, PVC cuffed, size 7mm_each_CMST",1964,1,370.1733 +Imported From One Health,Misc,-99,"Tube, endotracheal, PVC cuffed, size 7.5mm_each_CMST",1965,1,227.8017 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 8_each_CMST",1966,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 10_each_CMST",1967,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 12_each_CMST",1968,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 14_each_CMST",1969,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 16_each_CMST",1970,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 18_each_CMST",1971,1,284.75034 +Imported From One Health,Misc,-99,"Tube, stomach 75cm EG 24_each_CMST",1972,1,284.75034 +Imported From One Health,Misc,-99,"Tube, tracheostomy, cuffed size 7 with introducer and 15mm connector_each_CMST",1973,1,1727.48016 +Imported From One Health,Misc,-99,"Tube, tracheostomy, cuffed size 7.5 with introducer and 15mm connector_each_CMST",1974,1,1727.48016 +Imported From One Health,Misc,-99,"Tube, tracheostomy, non cuffed size 4_each_CMST",1975,1,1727.48016 +Imported From One Health,Misc,-99,"Bag tablet dispensing, polythene, disposable 9 x 10cm_50_CMST",1976,1,441.3591 +Imported From One Health,Misc,-99,"Bottle dropper, amber 10ml_each_CMST",1977,1,123.39348 +Imported From One Health,Misc,-99,"Apron, surgeon's polythene, foot length_each_CMST",1978,1,1471.20414 +Imported From One Health,Misc,-99,"Cup, feeding_each_CMST",1979,1,1570.86426 +Imported From One Health,Misc,-99,"Urinal, female stainless steel_each_CMST",1980,1,10208.26506 +Imported From One Health,Misc,-99,"Urinal, male stainless steel_each_CMST",1981,1,9187.90908 +Imported From One Health,Misc,-99,ABX Minoclair_ 500ml _CMST,1982,1,25855.23234 +Imported From One Health,Misc,-99,ABX Minoton_ 20L _CMST,1983,1,102723.3014 +Imported From One Health,Misc,-99,Acetone _2.5_CMST,1984,1,5011.58742 +Imported From One Health,Misc,-99,Act 5 diff Hgb_kit_CMST,1985,1,44762.5878 +Imported From One Health,Misc,-99,Act 5 diff WBC Lyse_kit_CMST,1986,1,79658.60952 +Imported From One Health,Misc,-99,Bilirubin in urine (Iactotest)_100_CMST,1987,1,26282.35428 +Imported From One Health,Misc,-99,Blood grouping serum Anti-A 10ml_each_CMST,1988,1,5970.23952 +Imported From One Health,Misc,-99,Blood in urine (Haemastix)_100_CMST,1989,1,21484.3314 +Imported From One Health,Misc,-99,"Bottle, blood collecting plain plastic vacuated, 5ml plus vacutainer needle 21G_1000_CMST",1990,1,39271.67076 +Imported From One Health,Misc,-99,"Bottle, blood collecting plain glass vacuated, 7ml _1000_CMST",1991,1,170.84592 +Imported From One Health,Misc,-99,"Bottle, blood collecting plastic vacuated with fluoride oxalate, 5ml _x000B_screw cap plus vacutainer needle 21G_1000_CMST",1992,1,43808.67666 +Imported From One Health,Misc,-99,"Bottle, blood collecting vacuated, 4.5 ml with EDTA K3 tubes plus vacutainer needle 21G_1000_CMST",1993,1,44501.56368 +Imported From One Health,Misc,-99,"Bottle, plastic plain with screw cap 12ml_1000_CMST",1994,1,73512.76884 +Imported From One Health,Misc,-99,"Bottle, wide mouth stainless steel screw cap 30ml_each_CMST",1995,1,1300.35822 +Imported From One Health,Misc,-99,Creatinine kinase test kit-Human 50ml_Kit_CMST,1996,1,66095.0514 +Imported From One Health,Misc,-99,"Culture swabs, sterile with hard plastic container with cap_1000_CMST",1997,1,3763.43688 +Imported From One Health,Misc,-99,"Dextrose, citrate blood bag with needle 16g, 250ml_each_CMST",1998,1,1347.81066 +Imported From One Health,Misc,-99,"Dextrose, citrate blood bag with needle 16g, 450ml_each_CMST",1999,1,1248.15054 +Imported From One Health,Misc,-99,Disposable Pipettes_1000g_CMST,2000,1,188333.1652 +Imported From One Health,Misc,-99,Fluorescent microscope square bulbs 100W_each_CMST,2001,1,10559.4531 +Imported From One Health,Misc,-99,Glucose in blood (Dextrostix)_25_CMST,2002,1,40609.99236 +Imported From One Health,Misc,-99,Glucose in urine (Clinistix)_100_CMST,2003,1,4299.71514 +Imported From One Health,Misc,-99,Glucose (GOD) test kit HUMAN_4 x 100ML_CMST,2004,1,73726.33338 +Imported From One Health,Misc,-99,Gram's A fluid_500ml_CMST,2005,1,3853.60794 +Imported From One Health,Misc,-99,HaemaCue Hb 201+ Machine_each_CMST,2006,1,509312.0294 +Imported From One Health,Misc,-99,Haemacue Hb 201+ - cuvettes _50_CMST,2007,1,23738.59362 +Imported From One Health,Misc,-99,Hepatitis B test kit-Dertemine_100 tests_CMST,2008,1,949.16304 +Imported From One Health,Misc,-99,Microscope slide frosted end 75mm x 25mm_50_CMST,2009,1,1808.15502 +Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 10cm_100_CMST,2010,1,4442.08674 +Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 15cm_100_CMST,2011,1,7555.34808 +Imported From One Health,Misc,-99,Paper filter Whatman no.1 size 24cm_100_CMST,2012,1,31578.69204 +Imported From One Health,Misc,-99,FACSCOUNT Paper thermal _100_CMST,2013,1,61145.16072 +Imported From One Health,Misc,-99,Partec CD4 % easy count Kit (100 tests)_Kit_CMST,2014,1,497784.4351 +Imported From One Health,Misc,-99,Partec CD4 easy count Kit (100 tests)_Kit_CMST,2015,1,212944.9951 +Imported From One Health,Misc,-99,pH/protein/glucose/ketones/blood in urine (Labstix)_50_CMST,2016,1,14731.02666 +Imported From One Health,Misc,-99,"Pipette, pasteur plastic disposable 3ml_1000_CMST",2017,1,19604.99058 +Imported From One Health,Misc,-99,"Pipette, plastic_1000_CMST",2018,1,19604.99058 +Imported From One Health,Misc,-99,Pregnancy slide test kit_100_CMST,2019,1,21982.64628 +Imported From One Health,Misc,-99,"SGOT (Aspartate Aminotransferase) test kit, 15mll-Human_Kit_CMST",2020,1,64068.58374 +Imported From One Health,Misc,-99,"SGPT (Alanine Aminotransferase ) test kit, 15ml-Human_Kit_CMST",2021,1,27872.2038 +Imported From One Health,Misc,-99,keylab cholesterol _5x40 ml_CMST,2022,1,11423.19318 +Imported From One Health,Misc,-99,keylab Glucose_5x40 ml_CMST,2023,1,9282.82824 +Imported From One Health,Misc,-99,"Barium enema administration kit (tubing, Air insufflator _x000B_and one shot inflator) _each_CMST",2024,1,20369.0634 +Imported From One Health,Misc,-99,"Barium sulphate disposable enema (Tubing, one shot inflator and air insufflator) _KIT_CMST",2025,1,22125.01788 +Imported From One Health,Misc,-99,Lead rubber x-ray protective aprons up to 150kVp 0.50mm_each_CMST,2026,1,470135.2778 +Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate inj (Urografin/Urovideo) 10%+ 66% 20ml_5_CMST,2027,1,27872.2038 +Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate inj (Urografin/Urovideo) 60% 20ml_5_CMST,2028,1,19614.47964 +Imported From One Health,Misc,-99,Sodium+ meglumine diatrizoate solution 10% + 66%. (Gastrografin) oral/rectal 100ml bottle_each_CMST,2029,1,7488.90324 +Imported From One Health,Misc,-99,Utransist 300mg/ml (20ml)_each_CMST,2030,1,13829.3232 +Imported From One Health,Misc,-99,Dental Technician lab kit_case_CMST,2031,1,1812.90312 +Imported From One Health,Misc,-99,Mepivacaine hydrochloride 3% plain 1.8ml cartridge_50_CMST,2032,1,10236.73938 +Imported From One Health,Misc,-99,"Oil spray for handpiece, universal_each_CMST",2033,1,13824.5751 +Imported From One Health,Misc,-99,"Plastic Bib, adult _each_CMST",2034,1,2254.26222 +Imported From One Health,Misc,-99,"Plastic Bib, children _each_CMST",2035,1,2254.26222 +Imported From One Health,Misc,-99,"Rolls, cotton dental_750_CMST",2036,1,2790.54048 +Imported From One Health,Misc,-99,"Syringes for dental cartridge, 2ml_each_CMST",2037,1,11717.43258 +Imported From One Health,Misc,-99,"Blanket cellular, adult, blue, 100% cotton, marked MOH 200 cm x 250 cm._each_CMST",2038,1,42033.73692 +Imported From One Health,Misc,-99,"Blanket cellular, adult, gold, 100% cotton, marked MOH 200 cm x 250 cm._each_CMST",2039,1,42033.73692 +Imported From One Health,Misc,-99,"Draw sheets, blue , 100% cotton marked MOH – 150cm x _x000B_120 cm, machine wash at high temperature_each_CMST",2040,1,12016.42008 +Imported From One Health,Misc,-99,Pillows foam_each_CMST,2041,1,3184.44714 +Imported From One Health,Misc,-99,Bromocriptine 2.5mg_100_CMST,2042,1,39428.27952 +Imported From One Health,Misc,-99,Carbimazole 5mg_100_CMST,2043,1,10516.74162 +Imported From One Health,Misc,-99,Cyclophosphamide 50mg_100_CMST,2044,1,5889.56466 +Imported From One Health,Misc,-99,Folic acid 5mg_1000_CMST,2045,1,3269.8701 +Imported From One Health,Misc,-99,Isosorbide dinitrate 10mg_1000_CMST,2046,1,14379.83862 +Imported From One Health,Misc,-99,Methotrexate 2.5mg_100_CMST,2047,1,9472.65942 +Imported From One Health,Misc,-99,Methotrexate 10mg_100_CMST,2048,1,20463.98256 +Imported From One Health,Misc,-99,Misoprostol 200 mcg _100_CMST,2049,1,4954.63878 +Imported From One Health,Misc,-99,Thioridazine HCL 100 mg_1000_CMST,2050,1,77285.69478 +Imported From One Health,Misc,-99,Ciprofloxacin 500mg_100_CMST,2051,1,2548.50876 +Imported From One Health,Misc,-99,Magnesium Slow_100_CMST,2052,1,28209.16182 +Imported From One Health,Misc,-99,Nifedipine 20mg (slow release)_100_CMST,2053,1,1570.86426 +Imported From One Health,Misc,-99,Norfloxacin 400mg _100_CMST,2054,1,1442.72982 +Imported From One Health,Misc,-99,Omeprazole 20mg_100_CMST,2055,1,3848.85984 +Imported From One Health,Misc,-99,Pericyazine 4 mg_100_CMST,2056,1,1376.28498 +Imported From One Health,Misc,-99,Procyclidine 5mg_1000_CMST,2057,1,86392.929 +Imported From One Health,Misc,-99,Proguanil hydrochloride 100mg_100_CMST,2058,1,10943.86356 +Imported From One Health,Misc,-99,Ranitidine 150mg_100_CMST,2059,1,1157.97948 +Imported From One Health,Misc,-99,"Actinomycin D 500 mcg PFR, (with mannitol)_each_CMST",2060,1,21204.32916 +Imported From One Health,Misc,-99,"Bupivacaine spinal hyperbaric 0.5%, 4ml ampoule_each_CMST",2061,1,816.2805 +Imported From One Health,Misc,-99,"Bupivacaine spinal isobaric 0.5%, 4ml ampoule_each_CMST",2062,1,669.1608 +Imported From One Health,Misc,-99,"Cyclophosphamide 200mg, PFR_each_CMST",2063,1,1305.09918 +Imported From One Health,Misc,-99,Dianeal + Dextrose 1.5% intraperitoneal dialysis soln. with minicap_2L_CMST,2064,1,9330.28068 +Imported From One Health,Misc,-99,Dianeal + Dextrose 2.5% intraperitoneal dialysis soln. with minicap_2L_CMST,2065,1,9330.28068 +Imported From One Health,Misc,-99,"Digoxin 250 micrograms/ml, 2ml_each_CMST",2066,1,393.89952 +Imported From One Health,Misc,-99,Dopamine 40mg/ml 5ml ampoule_each_CMST,2067,1,2557.99782 +Imported From One Health,Misc,-99,"Ephedrine sulphate 30mg/ml, 1ml_each_CMST",2068,1,3341.0559 +Imported From One Health,Misc,-99,"Haloperidol decanoate oily 50mg/ml, 1ml ampoule _each_CMST",2069,1,1072.55652 +Imported From One Health,Misc,-99,"Heparin sodium 5,000 IU/ml, 5ml_each_CMST",2070,1,1205.43906 +Imported From One Health,Misc,-99,"Lignocaine hydrochloride 2%, 25ml_each_CMST",2071,1,370.78734 +Imported From One Health,Misc,-99,"Metoclopramide hydrochloride 5mg/ml, 2ml_each_CMST",2072,1,3241.39578 +Imported From One Health,Misc,-99,"Neostigmine 2.5mg/ml, inj, 1ml ampoule_each_CMST",2073,1,313.22466 +Imported From One Health,Misc,-99,"Procyclidine HCl 5mg/ml, 2ml ampoule_each_CMST",2074,1,284.75034 +Imported From One Health,Misc,-99,Erythropoetin 2000 IU vial_each_CMST,2075,1,22613.83656 +Imported From One Health,Misc,-99,"Yellow fever vaccine 10-dose (5ml) vial, _x000B_PFR + diluent ampoule_each_CMST",2076,1,37843.1781 +Imported From One Health,Misc,-99,Anise oil_100ml_CMST,2077,1,4612.9398 +Imported From One Health,Misc,-99,Chloramine_1_CMST,2078,1,6126.85542 +Imported From One Health,Misc,-99,Citric acid_500g_CMST,2079,1,3535.63518 +Imported From One Health,Misc,-99,Halothane _2_CMST,2080,1,30415.96446 +Imported From One Health,Misc,-99,Nitric acid_2.5L_CMST,2081,1,6905.17254 +Imported From One Health,Misc,-99,Paraffin hard_25kg_CMST,2082,1,243474.8639 +Imported From One Health,Misc,-99,Betamethasone ointment 0.1%_1_CMST,2083,1,365.4252 +Imported From One Health,Misc,-99,Betamethasone sodium eardrops 0.1%_10ml_CMST,2084,1,1286.12106 +Imported From One Health,Misc,-99,"Lignocaine spray, 10% 20ml (for gastroscopy)_each_CMST",2085,1,6895.67634 +Imported From One Health,Misc,-99,"Lignocaine spray, 2% (for gastroscopy)_each_CMST",2086,1,6895.67634 +Imported From One Health,Misc,-99,Miconazole ear drop 1%_10ml_CMST,2087,1,28816.62588 +Imported From One Health,Misc,-99,Miconazole eye drops 1%_10ml_CMST,2088,1,24445.72494 +Imported From One Health,Misc,-99,Neomycin + Bacitracin skin ointment_1_CMST,2089,1,522.0411 +Imported From One Health,Misc,-99,"Salicylic acid 20%, ointment_0.625_CMST",2090,1,2572.23498 +Imported From One Health,Misc,-99,Sodium hypochlorite concentrated solution_5L_CMST,2091,1,3535.63518 +Imported From One Health,Misc,-99,"Bandage, plaster of paris 5cm_12_CMST",2092,1,4086.1506 +Imported From One Health,Misc,-99,"Bandage, plaster of paris 7.5cm_12_CMST",2093,1,4318.7004 +Imported From One Health,Misc,-99,"Bandage, stockinette 10cm_10m_CMST",2094,1,9031.30032 +Imported From One Health,Misc,-99,Lint_500g_CMST,2095,1,3753.94068 +Imported From One Health,Misc,-99,Catgut chromic 4/0 needle round bodied ½ circle 20mm_12_CMST,2096,1,13853.04942 +Imported From One Health,Misc,-99,Black blaided silk nonabsorbable sterile surgical ligature 2/0 150cm_12_CMST,2097,1,20198.21748 +Imported From One Health,Misc,-99,Monofilament polyamide nylon 10/0 round bodied needle_12_CMST,2098,1,47538.89112 +Imported From One Health,Misc,-99,Virgin silk twisted blue gauge 0.2 (10/0) 30cm on 6.5mm spatula curved (3/8 circle). Advanced micropoint double needle._12_CMST,2099,1,398231.3437 +Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 14_each_CMST,2100,1,313.22466 +Imported From One Health,Misc,-99,Catheter Foley's retention 10cc FG 18_each_CMST,2101,1,308.47656 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 14_each_CMST,2102,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 18_each_CMST,2103,1,242.03886 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 20_each_CMST,2104,1,280.00224 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 22_each_CMST,2105,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 24_each_CMST,2106,1,578.98974 +Imported From One Health,Misc,-99,Condom Catheter _each_CMST,2107,1,408.14382 +Imported From One Health,Misc,-99,"Currette, short blunt small_each_CMST",2108,1,783.05808 +Imported From One Health,Misc,-99,"Currette, short blunt large_each_CMST",2109,1,783.05808 +Imported From One Health,Misc,-99,ECG paper for printing_Roll_CMST,2110,1,564.75258 +Imported From One Health,Misc,-99,Forceps mosquito straight_2_CMST,2111,1,1162.72758 +Imported From One Health,Misc,-99,Forceps needle holder (Mayo's) straight_2_CMST,2112,1,1570.86426 +Imported From One Health,Misc,-99,Forceps needle holder 18cm (Mayo's)_2_CMST,2113,1,1570.86426 +Imported From One Health,Misc,-99,Forceps sinus (Lister's)_2_CMST,2114,1,2254.26222 +Imported From One Health,Misc,-99,Forceps tissue 12.5cm (Alli's)_2_CMST,2115,1,1176.96474 +Imported From One Health,Misc,-99,Giving sets iv (paediatric) with calibrated burrette_each_CMST,2116,1,650.17554 +Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,infant(90mm) _each_CMST",2117,1,17735.13168 +Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,child(114mm)_each_CMST",2118,1,17735.13168 +Imported From One Health,Misc,-99,"Laryngoscope Macintosh, blade,curved, hookfitting,adult (130mm)_each_CMST",2119,1,17735.13168 +Imported From One Health,Misc,-99,"Laryngoscope Macintosh, spare bulb_each_CMST",2120,1,355.93614 +Imported From One Health,Misc,-99,Needle lumbar puncture Luer 19g x 5cm_each_CMST,2121,1,450.8553 +Imported From One Health,Misc,-99,Needle lumbar puncture Luer 20g x 10cm_each_CMST,2122,1,450.8553 +Imported From One Health,Misc,-99,Needle spinal disposable Luer 23g x 10cm cutting bevel/pencil point_each_CMST,2123,1,450.8553 +Imported From One Health,Misc,-99,Shears plaster (Lorenz) 48cm_pair_CMST,2124,1,8091.62634 +Imported From One Health,Misc,-99,"Tube, chest drainage, size 22 with introducer_each_CMST",2125,1,85.42296 +Imported From One Health,Misc,-99,"Mortar & pestle, glass, 10cm_set_CMST",2126,1,7854.33558 +Imported From One Health,Misc,-99,"Sterilizer, instrument, 27.5 x 14 x 10cm, electrical_each_CMST",2127,1,95035.07076 +Imported From One Health,Misc,-99,"Tray, stainless steel no lid 20 x 15 x 5cm_each_CMST",2128,1,7066.5294 +Imported From One Health,Misc,-99,"Tray, stainless steel no lid 25 x 20 x 5cm_each_CMST",2129,1,7303.82016 +Imported From One Health,Misc,-99,"Tray, stainless steel no lid 45 x 32.5 x 5cm_each_CMST",2130,1,20421.27108 +Imported From One Health,Misc,-99,"Tray, stainless steel with lid 20 x15 x 5cm_each_CMST",2131,1,10208.26506 +Imported From One Health,Misc,-99,"Tray, stainless steel with lid 30 x 25 x 5cm_each_CMST",2132,1,16491.72924 +Imported From One Health,Misc,-99,"Trolley, patient_each_CMST",2133,1,278816.9929 +Imported From One Health,Misc,-99,"Trolley, soiled linen kick-about_each_CMST",2134,1,51050.80008 +Imported From One Health,Misc,-99,"Trolley, theatre stretcher-type imported_each_CMST",2135,1,282741.7866 +Imported From One Health,Misc,-99,Acetone in urine (acetest)_50_CMST,2136,1,21071.44662 +Imported From One Health,Misc,-99,ACT 5 diff Rinse_1L_CMST,2137,1,33695.33076 +Imported From One Health,Misc,-99,ACT 5 diff diluent _20L_CMST,2138,1,89748.22206 +Imported From One Health,Misc,-99,Act 5 Diff fix_1L_CMST,2139,1,266117.1748 +Imported From One Health,Misc,-99,Act 5 Diff WBC lyse_1L_CMST,2140,1,221938.3249 +Imported From One Health,Misc,-99,"Agar, dextrose_500g_CMST",2141,1,37705.54746 +Imported From One Health,Misc,-99,"Agar, SIM_500g_CMST",2142,1,64609.6101 +Imported From One Health,Misc,-99,Alkaline phosphatase test kit -HUMAN_Kit_CMST,2143,1,42161.87136 +Imported From One Health,Misc,-99,Amoxycillin disc 35mcg_1 x 50 discs_CMST,2144,1,3511.90896 +Imported From One Health,Misc,-99,"Amylase test kit, 5ml-HUMAN_Kit_CMST",2145,1,48350.42352 +Imported From One Health,Misc,-99,Anti - streptolysin (ASOT) test kit_Kit_CMST,2146,1,26040.32256 +Imported From One Health,Misc,-99,"Bacitracin 0.04 units, discs_50_CMST",2147,1,3511.90896 +Imported From One Health,Misc,-99,"Bacitracin 0.1 units, discs_50_CMST",2148,1,6876.69822 +Imported From One Health,Misc,-99,"Bottle, Bijou, 5ml, with stainless steel screw cap_each_CMST",2149,1,298.9875 +Imported From One Health,Misc,-99,"Bottle, blood collecting plastic 5ml with sod-cit 3-8% solution plus vacutainer needle 21G_1000_CMST",2150,1,86392.929 +Imported From One Health,Misc,-99,"Bottle, blood culture, 100ml_each_CMST",2151,1,906.45156 +Imported From One Health,Misc,-99,Calcium test kit-HUMAN_ 50ml_CMST,2152,1,42916.46226 +Imported From One Health,Misc,-99,Chloramphenicol discs_50_CMST,2153,1,5490.91704 +Imported From One Health,Misc,-99,Cholesterol test kit-HUMAN_250ml_CMST,2154,1,27373.89606 +Imported From One Health,Misc,-99,Cleaning solution for Nova 5_100mls_CMST,2155,1,101318.5349 +Imported From One Health,Misc,-99,Cloxacillin discs 5mcg_50_CMST,2156,1,7023.81792 +Imported From One Health,Misc,-99,"C-Reactive protein test kit,100ml_Kit_CMST",2157,1,34549.57464 +Imported From One Health,Misc,-99,Eclyte calibration cal 12_330mls_CMST,2158,1,47282.6151 +Imported From One Health,Misc,-99,Glucose (GOD/PAP)HUMAN_1000ml_CMST,2159,1,41549.66634 +Imported From One Health,Misc,-99,"Hemostat control plasma N,1ml_6X1ml_CMST",2160,1,50709.1011 +Imported From One Health,Misc,-99,"Humatrol N,5ml_6X5ML_CMST",2161,1,39997.7802 +Imported From One Health,Misc,-99,Microtome blades _50_CMST,2162,1,58985.81052 +Imported From One Health,Misc,-99,Norfloxacin disc 5mg_100_CMST,2163,1,6217.02648 +Imported From One Health,Misc,-99,Nova 5 fluid pack_ pack _CMST,2164,1,722176.3496 +Imported From One Health,Misc,-99,Novobiocin 5mg discs_50_CMST,2165,1,3511.90896 +Imported From One Health,Misc,-99,Novobiocin disc 5mg_50_CMST,2166,1,2747.829 +Imported From One Health,Misc,-99,Penicillin disc_50_CMST,2167,1,5490.91704 +Imported From One Health,Misc,-99,Penicillin G 1 unit disc_50_CMST,2168,1,5490.91704 +Imported From One Health,Misc,-99,Phosphorus test kit-Human_ 100ml _CMST,2169,1,13449.6537 +Imported From One Health,Misc,-99,Protein remover_100ml_CMST,2170,1,276273.2322 +Imported From One Health,Misc,-99,"Prothrombin time test kits, 1ml_6 x 1mls_CMST",2171,1,36557.05704 +Imported From One Health,Misc,-99,Rack for Westergreen ESR to take 6 tubes_each_CMST,2172,1,29395.61562 +Imported From One Health,Misc,-99,Rheumatoid factor test kit_ 45ml _CMST,2173,1,41625.60024 +Imported From One Health,Misc,-99,Salmonella (H) factor 1_0.4_CMST,2174,1,64068.58374 +Imported From One Health,Misc,-99,"Salmonella (H) factor 1, 2_0.4_CMST",2175,1,64068.58374 +Imported From One Health,Misc,-99,Salmonella (H) factor d_0.4_CMST,2176,1,64068.58374 +Imported From One Health,Misc,-99,"Salmonella (H) factor g, m_0.4_CMST",2177,1,64068.58374 +Imported From One Health,Misc,-99,Salmonella (O) factor (vi)_2ml_CMST,2178,1,64068.58374 +Imported From One Health,Misc,-99,Salmonella (O) factor 4_0.4_CMST,2179,1,64068.58374 +Imported From One Health,Misc,-99,Salmonella (O) factor 9_0.4_CMST,2180,1,64068.58374 +Imported From One Health,Misc,-99,Sulphuric acid_ 2.5L _CMST,2181,1,10208.26506 +Imported From One Health,Misc,-99,Total Protein test kit-Human_1000ml_CMST,2182,1,15770.36076 +Imported From One Health,Misc,-99,Triglycerides test kit - Human_100mls_CMST,2183,1,94925.91444 +Imported From One Health,Misc,-99,Uric acid test kit-Humanl_100mls_CMST,2184,1,35427.55188 +Imported From One Health,Misc,-99,X factor discs_100_CMST,2185,1,11366.24454 +Imported From One Health,Misc,-99,XV factor discs_100_CMST,2186,1,17350.72122 +Imported From One Health,Misc,-99,ABX Alphalyse_each_CMST,2187,1,14152.03692 +Imported From One Health,Misc,-99,ABX Basolyse_each_CMST,2188,1,66844.88706 +Imported From One Health,Misc,-99,Cortimoxizole prophylaxis,2189,1,4533.92142 +Imported From One Health,Misc,-99,ABX Eosinofix_each_CMST,2190,1,48578.22522 +Imported From One Health,Misc,-99,AP/PA floating markers left and right_pair_CMST,2191,1,8637.39366 +Imported From One Health,Misc,-99,Lead rubber protective aprons 0.5 mm equivalent with hunger_each_CMST,2192,1,470135.2778 +Imported From One Health,Misc,-99,"Amalgam capsule no. 1, non-gamma _50_CMST",2193,1,19135.15002 +Imported From One Health,Misc,-99,"Trimmer, Mitchell's, osteo no. 4_each_CMST",2194,1,15381.20934 +Imported From One Health,Misc,-99,Unsafe injections replaced with AD syringes,2195,1,164.20572 +Imported From One Health,Misc,-99,Prazosin 1mg _100_CMST,2196,1,17355.46932 +Imported From One Health,Misc,-99,"Fluid, viscoelastic hydroxypropylmethylcellulose, 2% w/v, 3ml ampoule_each_CMST",2197,1,469.83342 +Imported From One Health,Misc,-99,Bags syringe sterilization 20cm_1000_CMST,2198,1,9425.19984 +Imported From One Health,Misc,-99,Cannula tracheotomy Fuller's FG 17_each_CMST,2199,1,783.05808 +Imported From One Health,Misc,-99,Cannula tracheotomy Fuller's FG 24_each_CMST,2200,1,1414.2555 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 8_each_CMST,2201,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 10_each_CMST,2202,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 12_each_CMST,2203,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 16_each_CMST,2204,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 18_each_CMST,2205,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 20_each_CMST,2206,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 5cc FG 22_each_CMST,2207,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 26_each_CMST,2208,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's retention 30cc FG 28_each_CMST,2209,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 14_each_CMST,2210,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 16_each_CMST,2211,1,341.69898 +Imported From One Health,Misc,-99,Catheter Foley's suction 53cm FG 18_each_CMST,2212,1,341.69898 +Imported From One Health,Misc,-99,Needle suture round bodied no. 4_6_CMST,2213,1,550.51542 +Imported From One Health,Misc,-99,Syringe bladder disposable 100ml_each_CMST,2214,1,1176.96474 +Imported From One Health,Misc,-99,Spectacles - 0.5_pair_CMST,2215,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 1.0_pair_CMST,2216,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 1.5_pair_CMST,2217,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 2.0_pair_CMST,2218,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 2.5_pair_CMST,2219,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 3.0_pair_CMST,2220,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 3.5_pair_CMST,2221,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 4.0_pair_CMST,2222,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles - 5.0_pair_CMST,2223,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles + 0.5_pair_CMST,2224,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles + 1.0_pair_CMST,2225,1,3141.73566 +Imported From One Health,Misc,-99,Spectacles + 1.5_pair_CMST,2226,1,3141.73566 +Imported From One Health,Misc,-99,"Brush, nail bristle, plastic back_each_CMST",2227,1,792.55428 +Imported From One Health,Misc,-99,"Can, douche, stainless steel 1.5L_each_CMST",2228,1,5505.1542 +Imported From One Health,Misc,-99,"Stove, primus no 5_each_CMST",2229,1,17279.53542 +Imported From One Health,Misc,-99,"Amylase test kit,15ml_7_CMST",2230,1,47016.85002 +Imported From One Health,Misc,-99,Autoclavable bags_100_CMST,2231,1,38218.0995 +Imported From One Health,Misc,-99,CLED medium_500g_CMST,2232,1,29618.66922 +Imported From One Health,Misc,-99,"Gama- Glutamyl transferase test kit,10ml_10_CMST",2233,1,2401.38192 +Imported From One Health,Misc,-99,Haemocytometer pipette rbc_each_CMST,2234,1,2353.92948 +Imported From One Health,Misc,-99,Haemocytometer pipette wbc_each_CMST,2235,1,5813.63076 +Imported From One Health,Misc,-99,"Clock, interval timing, 0 to 120 mins_each_CMST",2236,1,9031.30032 +Imported From One Health,Misc,-99,Dental unit complete system (Belmont)_each_CMST,2237,1,7348201.643 +Imported From One Health,Misc,-99,Paper points assorted_50_CMST,2238,1,8945.87022 +Imported From One Health,Misc,-99,"Paper, articulating blue_pack_CMST",2239,1,8718.07566 +Imported From One Health,Misc,-99,Plastic instrument (Aesculap DE 6)_each_CMST,2240,1,11304.5478 +Imported From One Health,Misc,-99,Plastic instrument (black) (Aesculap DE 621)_each_CMST,2241,1,11304.5478 +Imported From One Health,Misc,-99,Plastic instrument (Frahm) ( Aesculap DF 50)_each_CMST,2242,1,17564.28576 +Imported From One Health,Misc,-99,Plastic instrument (Heidmann) (Aesculap DE 420)_each_CMST,2243,1,12566.9355 +Imported From One Health,Misc,-99,Plastic instrument (Hollenbach) (Aesculap DE 424)_each_CMST,2244,1,11546.58666 +Imported From One Health,Misc,-99,Plastic instrument (Hollenbach) (Aesculap DE 676)_each_CMST,2245,1,12566.9355 +Imported From One Health,Misc,-99,Posts assorted_pack_CMST,2246,1,157081.9349 +Imported From One Health,Misc,-99,Wax blue inlay (kerr)_pack_CMST,2247,1,9425.19984 +Imported From One Health,Misc,-99,Wax model cement (Dentisply)_pack_CMST,2248,1,9425.19984 +Imported From One Health,Misc,-99,Wax occlusal indicator (kerr)_pack_CMST,2249,1,35736.03558 +Imported From One Health,Misc,-99,Wax periphery sticks_pack_CMST,2250,1,7166.18952 +Imported From One Health,Misc,-99,Determine syphillis _100_CMST,2251,1,64794.69318 +Imported From One Health,Misc,-99,Glove surgeon's size 7½ sterile_pair_CMST,2252,1,156.6159 +Imported From One Health,Misc,-99,"Towels, paper_1000_CMST",2253,1,5842.10508 +Imported From One Health,Misc,-99,Morphine sulphate suspension 10mg/5ml_500ml_CMST,2254,1,1305.09918 +Imported From One Health,Misc,-99,"Nystatin pessaries 100,000 IU_each_CMST",2255,1,783.05808 +Imported From One Health,Misc,-99,Airway disposable (Portex) size 0_each_CMST,2256,1,484.07058 +Imported From One Health,Misc,-99,Airway disposable (Portex) size 00_each_CMST,2257,1,484.07058 +Imported From One Health,Misc,-99,Airway disposable (Portex) size 000_each_CMST,2258,1,484.07058 +Imported From One Health,Misc,-99,Airway disposable (Portex) size 1_each_CMST,2259,1,484.07058 +Imported From One Health,Misc,-99,Connection polythene straight assorted_36_CMST,2260,1,1570.86426 +Imported From One Health,Misc,-99,Glove postmortem size 7_pair_CMST,2261,1,783.05808 +Imported From One Health,Misc,-99,Glove postmortem size 7½_pair_CMST,2262,1,783.05808 +Imported From One Health,Misc,-99,Glove postmortem size 8_pair_CMST,2263,1,783.05808 +Imported From One Health,Misc,-99,Glove postmortem size 8½_pair_CMST,2264,1,783.05808 +Imported From One Health,Misc,-99,Connecting tube corrugated 9cm_each_CMST,2265,1,2828.511 +Imported From One Health,Misc,-99,"Cord, extension_each_CMST",2266,1,3924.79374 +Imported From One Health,Misc,-99,Blood grouping tilles-flat_each_CMST,2267,1,1699.00584 +Imported From One Health,Misc,-99,"Bottle, plastic plain with screw 1litre_each_CMST",2268,1,9372.9993 +Imported From One Health,Misc,-99,"Leischman's buffer ampoules,10ml_10_CMST",2269,1,12695.06994 +Imported From One Health,Misc,-99,Leischman's stain GRG_100g_CMST,2270,1,19704.6507 +Imported From One Health,Misc,-99,Composite sureful (Dentisply)_pack_CMST,2271,1,125664.5998 +Imported From One Health,Misc,-99,Ketac silver mamixcap (Espe)_pack_CMST,2272,1,376993.7921 +Imported From One Health,Misc,-99,"aciclovir 200 mg, dispersible_500_IDA",2273,1,8338.40616 +Imported From One Health,Misc,-99,"aciclovir 200 mg, dispersible, blister_50x10_IDA",2274,1,11760.14406 +Imported From One Health,Misc,-99,aciclovir 3% eye ointment 4.5g_10_IDA,2275,1,4484.79822 +Imported From One Health,Misc,-99,adhesive tape 1.25 cm x 5 m_10_IDA,2276,1,1300.35822 +Imported From One Health,Misc,-99,adhesive tape 10.0 cm x 5 m_2_IDA,2277,1,1736.96922 +Imported From One Health,Misc,-99,adhesive tape 2.5 cm x 5 m_8_IDA,2278,1,1490.1894 +Imported From One Health,Misc,-99,adhesive tape 5.0 cm x 5 m_4_IDA,2279,1,1736.96922 +Imported From One Health,Misc,-99,adhesive woundplaster 6.0 cm x 5 m_1_IDA,2280,1,1784.4288 +Imported From One Health,Misc,-99,"albendazole 200 mg/ 5 ml oral suspension, 10 ml_30_IDA",2281,1,4921.41636 +Imported From One Health,Misc,-99,amlodipine 5 mg_100_IDA,2282,1,2121.37968 +Imported From One Health,Misc,-99,"amoxicillin 125 mg/5 ml, pwd for suspension, 100ml_40_IDA",2283,1,528.36 +Imported From One Health,Misc,-99,"amoxicillin 1g + clavulanic acid 200mg, pwd f inj._10_IDA",2284,1,14844.93108 +Imported From One Health,Misc,-99,amoxicillin 500 mg_1000_IDA,2285,1,18456.50016 +Imported From One Health,Misc,-99,amoxicillin 500 mg_1000_IDA,2286,1,21156.86958 +Imported From One Health,Misc,-99,"amoxicillin 500 mg + clavulanic acid 125 mg, bl._10x5_IDA",2287,1,5832.61602 +Imported From One Health,Misc,-99,"amoxicillin 500 mg, blister_100x10_IDA",2288,1,20962.2903 +Imported From One Health,Misc,-99,anti-haemorrhoid suppositories (*a)_100_IDA,2289,1,10939.11546 +Imported From One Health,Misc,-99,"applicator stick, wood, with cotton tip, 15.0 cm_100_IDA",2290,1,336.95088 +Imported From One Health,Misc,-99,"apron utility, 120 cm, opaque, plastic, reusable_1_IDA",2291,1,1447.47792 +Imported From One Health,Misc,-99,"apron with neckband, opaque, plastic, disposable_1000_IDA",2292,1,75093.1293 +Imported From One Health,Misc,-99,"artemether 80 mg/ml, 1 ml, for injection_50_IDA",2293,1,11617.77246 +Imported From One Health,Misc,-99,"artesunate 100 mg + SP 525 mg, co-blister, adults_6+3_IDA",2294,1,768.82092 +Imported From One Health,Misc,-99,artesunate 100mg + amodiaquine 270mg tab_25X6 _IDA,2295,1,17787.33936 +Imported From One Health,Misc,-99,artesunate 100mg + amodiaquine 270mg tab_25X3 _IDA,2296,1,27089.14572 +Imported From One Health,Misc,-99,"bandage, hydrophilic 7.5 cm x 10 m, w.o.w._10_IDA",2297,1,1105.77894 +Imported From One Health,Misc,-99,Dacarabazine 200mg injection,2298,1,6819.36402 +Imported From One Health,Misc,-99,"barium sulphate BP/EP, for x-ray diagnosis_25_IDA",2299,1,41255.4198 +Imported From One Health,Misc,-99,"beclometasone or. Inh., 50 mcg/d, 200 dos (UN1950)_1_IDA",2300,1,1684.76868 +Imported From One Health,Misc,-99,"benzathine penicillin 1.2 miu, powder for inj._50_IDA",2301,1,7427.21364 +Imported From One Health,Misc,-99,blade for surgical knives size 10_100_IDA,2302,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 11_100_IDA,2303,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 12_100_IDA,2304,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 15_100_IDA,2305,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 20_100_IDA,2306,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 21_100_IDA,2307,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 23_100_IDA,2308,1,4147.84734 +Imported From One Health,Misc,-99,blade for surgical knives size 24_100_IDA,2309,1,4147.84734 +Imported From One Health,Misc,-99,"blanket, survival, disposable, 210 x 160 cm_1_IDA",2310,1,1589.84952 +Imported From One Health,Misc,-99,"bloodgroup anti A 200 tests, monoclonal, 10 ml(**)_10_IDA",2311,1,20193.46938 +Imported From One Health,Misc,-99,"bloodgroup anti A/B 200 tests, monoclonal,10ml(**)_10_IDA",2312,1,27131.8572 +Imported From One Health,Misc,-99,"bottle, plastic, 1000ml, wide neck, no screwcap_1_IDA",2313,1,915.94062 +Imported From One Health,Misc,-99,"bottle, plastic, 100ml (without screwcap, 872741)_1_IDA",2314,1,142.3716 +Imported From One Health,Misc,-99,bowl s.s. 300ml_1_IDA,2315,1,1400.01834 +Imported From One Health,Misc,-99,"bromhexine 0.8 mg/ml oral solution, 125 ml_25_IDA",2316,1,27426.0966 +Imported From One Health,Misc,-99,bromhexine HCl 8 mg_1000_IDA,2317,1,11086.23516 +Imported From One Health,Misc,-99,"bupivacaine HCl 0.5%, 20 ml, for injection_10_IDA",2318,1,11565.56478 +Imported From One Health,Misc,-99,"calamine lotion, 500 ml_1_IDA",2319,1,1589.84952 +Imported From One Health,Misc,-99,calcium lactate 300 mg_1000_IDA,2320,1,11617.77246 +Imported From One Health,Misc,-99,carbol fuchsin (Ziehl-n) dry powder UN2811_25_IDA,2321,1,45787.68474 +Imported From One Health,Misc,-99,catheter Foley ch.26 balloon 5-15ml sterile_10_IDA,2322,1,3379.02642 +Imported From One Health,Misc,-99,"catheter Foley, 3-way, balloon 30-50ml, disp.,Ch22_10_IDA",2323,1,14892.38352 +Imported From One Health,Misc,-99,"catheter Foley, 3-way, balloon 30-50ml,disp.,Ch 20_10_IDA",2324,1,14892.38352 +Imported From One Health,Misc,-99,"catheter Foley, balloon 3-5ml,sterile,disp., Ch 08_10_IDA",2325,1,12002.18292 +Imported From One Health,Misc,-99,"catheter Foley, balloon 3-5ml,sterile,disp., Ch 10_10_IDA",2326,1,12002.18292 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 12,sterile,disp._10_IDA",2327,1,3084.78702 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 14,sterile,disp._10_IDA",2328,1,3084.78702 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 16,sterile,disp._10_IDA",2329,1,3084.78702 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 18,sterile,disp._10_IDA",2330,1,3184.44714 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 20,sterile,disp._10_IDA",2331,1,3184.44714 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 22,sterile,disp._10_IDA",2332,1,3184.44714 +Imported From One Health,Misc,-99,"catheter Foley, balloon 5-15ml,Ch 24,sterile,disp._10_IDA",2333,1,3184.44714 +Imported From One Health,Misc,-99,"catheter nelaton ch.10 disp. plastic, sterile_100_IDA",2334,1,11038.78272 +Imported From One Health,Misc,-99,"catheter nelaton ch.12 disp. plastic, sterile_100_IDA",2335,1,11038.78272 +Imported From One Health,Misc,-99,"catheter nelaton ch.14 disp. plastic, sterile_100_IDA",2336,1,11475.39372 +Imported From One Health,Misc,-99,"cefixime 200 mg, blister_10x10_IDA",2337,1,9591.3048 +Imported From One Health,Misc,-99,"ceftriaxon 500 mg, powder for injection_10_IDA",2338,1,3568.8576 +Imported From One Health,Misc,-99,"centrifuge tube plastic 110x16mm, 10ml, conical_1_IDA",2339,1,52.20054 +Imported From One Health,Misc,-99,"chlorhexidine gluconate 20%, solution, 5 L(UN3082)_1_IDA",2340,1,32053.27356 +Imported From One Health,Misc,-99,"chlorhexidine gluconate 5% solution, 1 L_1_IDA",2341,1,3032.57934 +Imported From One Health,Misc,-99,"chloroq. phosphate 10 mg base/ml, oral sol., 60 ml_195_IDA",2342,1,80916.24912 +Imported From One Health,Misc,-99,"chloroxylenol 5% (4.5-5.5%) solution, 1 L_1_IDA",2343,1,8869.94346 +Imported From One Health,Misc,-99,"chlorphenamine maleate 10 mg/ml, 1 ml, injection_100_IDA",2344,1,4484.79822 +Imported From One Health,Misc,-99,"chlorpromazine HCl 50 mg/2 ml, for injection_100_IDA",2345,1,4964.12784 +Imported From One Health,Misc,-99,cimetidine 200 mg_500_IDA,2346,1,3132.23946 +Imported From One Health,Misc,-99,"cimetidine 200 mg/2 ml, for injection_10_IDA",2347,1,2648.16888 +Imported From One Health,Misc,-99,"ciprofloxacin 2 mg/ml, 100 ml infusion_10_IDA",2348,1,54799.9998 +Imported From One Health,Misc,-99,"container specimen glass wide neck + cap, 100ml_1_IDA",2349,1,484.07058 +Imported From One Health,Misc,-99,co-trimoxazole 100 mg + 20 mg_1000_IDA,2350,1,3032.57934 +Imported From One Health,Misc,-99,co-trimoxazole 400 mg + 80 mg_1000_IDA,2351,1,7953.9957 +Imported From One Health,Misc,-99,co-trimoxazole 800 mg + 160 mg_500_IDA,2352,1,8006.20338 +Imported From One Health,Misc,-99,"co-trimoxazole 800 mg + 160 mg, blister_5x10_IDA",2353,1,8817.73578 +Imported From One Health,Misc,-99,CPD-a bag 35 ml for 250 ml blood + taking set_10_IDA,2354,1,7327.54638 +Imported From One Health,Misc,-99,CPD-a bag 63 ml for 450 ml blood + taking set_10_IDA,2355,1,7617.04482 +Imported From One Health,Misc,-99,dapsone 100mg tab_28_IDA,2356,1,242.03886 +Imported From One Health,Misc,-99,dapsone 50 mg_1000_IDA,2357,1,5974.98762 +Imported From One Health,Misc,-99,"Determine chasebuffer, 2.5ml, for 100 tests_1_IDA",2358,1,6696.3561 +Imported From One Health,Misc,-99,"dexamethasone sodium phosphate 5 mg/ml, 1 ml, inj._100_IDA",2359,1,5732.94876 +Imported From One Health,Misc,-99,"dextrose 10% in water, 500 ml_20_IDA",2360,1,13928.98332 +Imported From One Health,Misc,-99,"dextrose 2.5% in sodium chloride 0.45%, 1000 ml_12_IDA",2361,1,10554.705 +Imported From One Health,Misc,-99,"dextrose 2.5% in sodium chloride 0.45%, 500 ml_20_IDA",2362,1,12965.58312 +Imported From One Health,Misc,-99,"dextrose 5% in water, 250 ml_30_IDA",2363,1,17208.34962 +Imported From One Health,Misc,-99,"dextrose 50%, 50 ml, for injection_20_IDA",2364,1,12528.96498 +Imported From One Health,Misc,-99,"diazepam 10 mg/2 ml, for injection (pt)_100_IDA",2365,1,127.2705 +Imported From One Health,Misc,-99,"digoxin 0.25 mg, blister_7x4_IDA",2366,1,1879.34796 +Imported From One Health,Misc,-99,"digoxin 0.5 mg/2 ml, for injection_100_IDA",2367,1,5927.52804 +Imported From One Health,Misc,-99,"dopamine HCl 200 mg/5 ml, for injection_100_IDA",2368,1,43476.46674 +Imported From One Health,Misc,-99,"drum for cotton wool&gauze, 15cm diam., 15cm high_1_IDA",2369,1,9159.43476 +Imported From One Health,Misc,-99,E.t. cuffed tube oral 3.5mm disposable_10_IDA,2370,1,24820.64634 +Imported From One Health,Misc,-99,E.t. cuffed tube oral 7.5mm disposable_10_IDA,2371,1,23235.53778 +Imported From One Health,Misc,-99,ear syringe 60ml rubber_1_IDA,2372,1,1105.77894 +Imported From One Health,Misc,-99,elastic bandage 10.0 cm x 2.5m (5.0 m stretched)_10_IDA,2373,1,3806.14836 +Imported From One Health,Misc,-99,"enalapril maleate 5 mg, blister_10x10_IDA",2374,1,526.7892 +Imported From One Health,Misc,-99,ergotamine 1 mg + caffeine 100 mg_30_IDA,2375,1,9496.38564 +Imported From One Health,Misc,-99,erythromycin 250mg/5ml pwd for susp 100ml_1_IDA,2376,1,1784.4288 +Imported From One Health,Misc,-99,"ethinylestradiol/levonorgestrel 0.03/0.15 mg, 28tb_200_IDA",2377,1,56200.011 +Imported From One Health,Misc,-99,"examination gloves, plastic, pre-powdered _100_IDA",2378,1,436.61814 +Imported From One Health,Misc,-99,"feeding tube, Ch 10, sterile, disp., 40 cm, luer _100_IDA",2379,1,6890.93538 +Imported From One Health,Misc,-99,"ferrous fumarate 100 mg/5 ml oral susp., 50 ml_25_IDA",2380,1,13444.91274 +Imported From One Health,Misc,-99,"ferrous fumarate 100 mg/5 ml oral suspension, 5 L_1_IDA",2381,1,20535.16836 +Imported From One Health,Misc,-99,ferrous sulphate 200 mg + folic acid 0.25 mg_1000_IDA,2382,1,1879.34796 +Imported From One Health,Misc,-99,ferrous sulphate 200 mg + folic acid 0.4 mg_1000_IDA,2383,1,1926.8004 +Imported From One Health,Misc,-99,"ferrous sulphate 200 mg, coated (65 mg iron)_1000_IDA",2384,1,1784.4288 +Imported From One Health,Misc,-99,field stain A_25_IDA,2385,1,9159.43476 +Imported From One Health,Misc,-99,field stain A_250_IDA,2386,1,10844.20344 +Imported From One Health,Misc,-99,filter set 515KS-LFS for DeVilbiss oxygen concentr_1_IDA,2387,1,34606.53042 +Imported From One Health,Misc,-99,fluconazole 100 mg_100_IDA,2388,1,4869.21582 +Imported From One Health,Misc,-99,"fluconazole 100 mg, blister_10x10_IDA",2389,1,5590.57716 +Imported From One Health,Misc,-99,fluconazole 150 mg_100_IDA,2390,1,5448.20556 +Imported From One Health,Misc,-99,fluconazole 50 mg_100_IDA,2391,1,3663.77676 +Imported From One Health,Misc,-99,"furosemide 20 mg/2 ml, for injection_100_IDA",2392,1,4726.83708 +Imported From One Health,Misc,-99,"ganciclovir 500 mg, powder for injection_1_IDA",2393,1,26989.4856 +Imported From One Health,Misc,-99,"gentamicin 20 mg/2 ml, for injection_100_IDA",2394,1,5538.37662 +Imported From One Health,Misc,-99,"giemsa solution, 500 ml, plastic bottle (UN1992)_2_IDA",2395,1,19277.52162 +Imported From One Health,Misc,-99,Glucose Control solution_1_IDA,2396,1,6311.94564 +Imported From One Health,Misc,-99,gram staining set 5 x 500 ml (UN1993)_1_IDA,2397,1,88680.41364 +Imported From One Health,Misc,-99,griseofulvin 500 mg_1000_IDA,2398,1,38749.62966 +Imported From One Health,Misc,-99,"griseofulvin 500 mg, blister_1000_IDA",2399,1,42024.24786 +Imported From One Health,Misc,-99,Guedel airway size 2_1_IDA,2400,1,2415.61908 +Imported From One Health,Misc,-99,"haloperidol 10 mg/ 5 ml, oral solution, 100 ml_1_IDA",2401,1,10165.54644 +Imported From One Health,Misc,-99,"haloperidol 5 mg/ml, 1 ml, for injection_100_IDA",2402,1,26462.6964 +Imported From One Health,Misc,-99,halothane 250 ml (in case of air shipment:UN2810)_6_IDA,2403,1,105836.5556 +Imported From One Health,Misc,-99,HIV 1 New Lav Blot I (Bio-Rad Laboratories) (**)_18_IDA,2404,1,346183.921 +Imported From One Health,Misc,-99,HIV 1+2 Determine (*a)_100_IDA,2405,1,76825.35042 +Imported From One Health,Misc,-99,HIV 1+2+O Antibodies Elisa (Abbott) (*)_96_IDA,2406,1,130367.7035 +Imported From One Health,Misc,-99,HIV 2 New Lav Blot II (Bio-Rad Laboratories) (**)_18_IDA,2407,1,346183.921 +Imported From One Health,Misc,-99,hydrochlorothiazide 50 mg_1000_IDA,2408,1,3084.78702 +Imported From One Health,Misc,-99,"hydrocortisone 100 mg (as sodium suc.), pwd f inj._50_IDA",2409,1,10939.11546 +Imported From One Health,Misc,-99,"hydrocortisone acetate 1% cream, 15 g_10_IDA",2410,1,3184.44714 +Imported From One Health,Misc,-99,"hyoscine butylbromide 20 mg/ml, 1 ml, for inj._100_IDA",2411,1,8196.03456 +Imported From One Health,Misc,-99,"ibuprofen 100mg/5ml oral suspension, 100ml_1_IDA",2412,1,963.4002 +Imported From One Health,Misc,-99,IEHK Antimalarials for Basic Unit (1.000 persons)_1_IDA,2413,1,759412.0636 +Imported From One Health,Misc,-99,IEHK Basic Unit without Antimalarials (1.000 pers)_1_IDA,2414,1,367924.5284 +Imported From One Health,Misc,-99,IEHK Suppl. Unit w/o PEP & Malaria (10.000 pers)_1_IDA,2415,1,3278223.407 +Imported From One Health,Misc,-99,infusion giving set with air inlet and needle_4x100_IDA,2416,1,55426.44198 +Imported From One Health,Misc,-99,isoflurane 250 ml (in case of air shipment:UN2810)_6_IDA,2417,1,176060.4691 +Imported From One Health,Misc,-99,isoniazid 100mg tab_1000_IDA,2418,1,3326.81874 +Imported From One Health,Misc,-99,"IV placement unit 16G, sterile, disposable_50_IDA",2419,1,5927.52804 +Imported From One Health,Misc,-99,"IV placement unit 16G, w.inj.port&wings,ster,disp_50_IDA",2420,1,6169.5669 +Imported From One Health,Misc,-99,"IV placement unit 18G, sterile, disposable_50_IDA",2421,1,5927.52804 +Imported From One Health,Misc,-99,"IV placement unit 18G, w.inj.port&wings,ster,disp_50_IDA",2422,1,5538.37662 +Imported From One Health,Misc,-99,"IV placement unit 20G, sterile, disposable_50_IDA",2423,1,5305.82682 +Imported From One Health,Misc,-99,"IV placement unit 20G, w.inj.port&wings,ster,disp_50_IDA",2424,1,6169.5669 +Imported From One Health,Misc,-99,"IV placement unit 22G, sterile, disposable_50_IDA",2425,1,5927.52804 +Imported From One Health,Misc,-99,"IV placement unit 22G, w.inj.port&wings,ster,disp_50_IDA",2426,1,6169.5669 +Imported From One Health,Misc,-99,"IV placement unit 24G, sterile, disposable_50_IDA",2427,1,5732.94876 +Imported From One Health,Misc,-99,"IV placement unit 24G, w.inj.port&wings,ster,disp_50_IDA",2428,1,6653.64462 +Imported From One Health,Misc,-99,laryngoscope + 4 Blades (1 str. neonate) + spare bulb_1_IDA,2429,1,76777.89798 +Imported From One Health,Misc,-99,laryngoscope handle standard hook-on fitting_1_IDA,2430,1,14408.31294 +Imported From One Health,Misc,-99,"levodopa 250 mg + carbidopa 25 mg, blister_10x10_IDA",2431,1,5690.23728 +Imported From One Health,Misc,-99,"levothyroxine sodium 0.1 mg, blister_7x4_IDA",2432,1,1400.01834 +Imported From One Health,Misc,-99,"lidocaine HCl 2% + epinephrine dental, 1.8 ml_100_IDA",2433,1,25394.88798 +Imported From One Health,Misc,-99,"lidocaine HCl 2% 20 ml, for injection_10_IDA",2434,1,6117.36636 +Imported From One Health,Misc,-99,"Lugol's iodine for staining (1:2:100 aqueous), 1 L_1_IDA",2435,1,11665.23204 +Imported From One Health,Misc,-99,lysine acetylsalicylate 900mg injection_100_IDA,2436,1,39713.02986 +Imported From One Health,Misc,-99,"magnesium sulphate 50%, 20 ml, for injection_10_IDA",2437,1,6269.22702 +Imported From One Health,Misc,-99,"malaria P. falciparum + P. pan RDT, Parascreen_25_IDA",2438,1,21014.49798 +Imported From One Health,Misc,-99,"malaria P.falciparum+P.vivax+P.pan RDT, Paramax_25_IDA",2439,1,29158.32486 +Imported From One Health,Misc,-99,"mebendazole 100 mg, blister_60x10_IDA",2440,1,4000.72764 +Imported From One Health,Misc,-99,"mebendazole 100 mg/5 ml oral suspension, 100 ml_1_IDA",2441,1,526.7892 +Imported From One Health,Misc,-99,"mebendazole 100 mg/5 ml oral suspension, 30 ml_1_IDA",2442,1,270.51318 +Imported From One Health,Misc,-99,"metoclopramide HCl 10 mg/2 ml, for injection_100_IDA",2443,1,4627.17696 +Imported From One Health,Misc,-99,"metronidazole 200 mg/5 ml, pwd for susp., 100 ml_250_IDA",2444,1,166274.5921 +Imported From One Health,Misc,-99,metronidazole 250 mg_1000_IDA,2445,1,4242.7665 +Imported From One Health,Misc,-99,"metronidazole 250 mg, blister_100x10_IDA",2446,1,5395.99788 +Imported From One Health,Misc,-99,"metronidazole 500 mg, vaginal_1000_IDA",2447,1,33643.12308 +Imported From One Health,Misc,-99,"microscope slides 76x26mm, trop.pack., frosted end_5000_IDA",2448,1,176971.6687 +Imported From One Health,Misc,-99,"mosquito net 130 x 180 x 150 cm, LLIN, polyester_1_IDA",2449,1,4100.38776 +Imported From One Health,Misc,-99,"mosquito net 160 x 180 x 150 cm, LLIN, polyester_1_IDA",2450,1,4532.2578 +Imported From One Health,Misc,-99,"mosquito net 190 x 180 x 150 cm, LLIN, polyester_1_IDA",2451,1,4726.83708 +Imported From One Health,Misc,-99,"naloxone 0.4 mg/ml, 1 ml, for injection_10_IDA",2452,1,11038.78272 +Imported From One Health,Misc,-99,naproxen 250 mg_1000_IDA,2453,1,17450.38134 +Imported From One Health,Misc,-99,nifedipine retard 20 mg_100_IDA,2454,1,2311.218 +Imported From One Health,Misc,-99,nitrofurantoin 100 mg_1000_IDA,2455,1,6074.65488 +Imported From One Health,Misc,-99,nitroglycerine 0.5 mg (glyceryl trinitrate)_100_IDA,2456,1,5495.658 +Imported From One Health,Misc,-99,norethisterone 5 mg_30_IDA,2457,1,1926.8004 +Imported From One Health,Misc,-99,nystatin 500.000 iu oral coated_100_IDA,2458,1,6074.65488 +Imported From One Health,Misc,-99,oxygen tube ch.10 40cm disp._100_IDA,2459,1,15523.58094 +Imported From One Health,Misc,-99,"pancuronium bromide 4 mg/2 ml, for injection (**)_100_IDA",2460,1,62122.79808 +Imported From One Health,Misc,-99,paracetamol 120 mg suppositories (*a)_100_IDA,2461,1,6553.97736 +Imported From One Health,Misc,-99,"pentazocine 30 mg/ml, 1 ml, for injection (pt)_100_IDA",2462,1,9690.96492 +Imported From One Health,Misc,-99,phenobarbital 50 mg (pt)_1000_IDA,2463,1,3763.43688 +Imported From One Health,Misc,-99,phenoxymethylpenicillin 250 mg_1000_IDA,2464,1,13881.52374 +Imported From One Health,Misc,-99,phenytoin 250 mg/5 ml for injection_5_IDA,2465,1,7711.95684 +Imported From One Health,Misc,-99,"pipette, RBC, with tubing and mouthpiece_1_IDA",2466,1,2168.83926 +Imported From One Health,Misc,-99,"pipette, WBC, with tubing and mouthpiece_1_IDA",2467,1,2168.83926 +Imported From One Health,Misc,-99,plaster of Paris bandage 20.0 cm x 2.7 m_12_IDA,2468,1,5538.37662 +Imported From One Health,Misc,-99,podophyllotoxin 0.5% solution_3_IDA,2469,1,21882.97902 +Imported From One Health,Misc,-99,"procaine penici.3miu / benzylpenici.1miu, pwd inj._50_IDA",2470,1,14023.90248 +Imported From One Health,Misc,-99,procaine penicillin 3 MIU powder for inj_50_IDA,2471,1,13686.9516 +Imported From One Health,Misc,-99,"promethazine HCl 50 mg/2 ml, for injection_100_IDA",2472,1,30510.88362 +Imported From One Health,Misc,-99,"protamine sulphate 50 mg/5 ml, for injection_10_IDA",2473,1,18750.73956 +Imported From One Health,Misc,-99,"pvp iodine 7.5% surgical scrub (betadine), 500 ml_1_IDA",2474,1,11859.80418 +Imported From One Health,Misc,-99,pyrantel 250mg_1000_IDA,2475,1,26847.10686 +Imported From One Health,Misc,-99,"quinine sulphate 200 mg, film coated_1000_IDA",2476,1,26510.15598 +Imported From One Health,Misc,-99,"rabies vacc.(vero cells), pwd inj+solv. 0.5ml(***)_1_IDA",2477,1,18651.07944 +Imported From One Health,Misc,-99,"rack, for slides, expendable, for staining_1_IDA",2478,1,9059.77464 +Imported From One Health,Misc,-99,"rifampicin 300 mg + isoniazid 150 mg, coated_1000_IDA",2479,1,36680.45052 +Imported From One Health,Misc,-99,"Ringer's lactate (Hartmann's solution), 250 ml_30_IDA",2480,1,16871.3916 +Imported From One Health,Misc,-99,"Ringer's lactate (Hartmann's solution), 500 ml_20_IDA",2481,1,12723.54426 +Imported From One Health,Misc,-99,"ringer's lactate (Hartmann's solution), 500 ml_20_IDA",2482,1,8480.7849 +Imported From One Health,Misc,-99,salbutamol 2 mg_1000_IDA,2483,1,1300.35822 +Imported From One Health,Misc,-99,"salbutamol 2 mg/5 ml, oral solution, 100 ml_25_IDA",2484,1,16719.53094 +Imported From One Health,Misc,-99,"salbutamol respirator solution 5 mg/ml, 30 ml_1_IDA",2485,1,3421.7379 +Imported From One Health,Misc,-99,screwcap for plastic bottle 1000 ml _1_IDA,2486,1,185.09022 +Imported From One Health,Misc,-99,screwcap with inlay for plastic bottle 100 ml _1_IDA,2487,1,142.3716 +Imported From One Health,Misc,-99,sheeting plastic clear 90cm x 180cm Uni0361020_1_IDA,2488,1,1490.1894 +Imported From One Health,Misc,-99,"slidebox for 100 slides, 75 x 26mm, plastic_1_IDA",2489,1,12244.22178 +Imported From One Health,Misc,-99,sodium valproate 200mg enteric coated_100_IDA,2490,1,4000.72764 +Imported From One Health,Misc,-99,sodium valproate 500mg enteric coated_100_IDA,2491,1,8775.0243 +Imported From One Health,Misc,-99,spare wick for spirit lamp 150 ml_1_IDA,2492,1,963.4002 +Imported From One Health,Misc,-99,sphygmomanometer anaeroid for children_1_IDA,2493,1,4000.72764 +Imported From One Health,Misc,-99,"spirit lamp s.s., 150 ml, alcohol burner_1_IDA",2494,1,13107.96186 +Imported From One Health,Misc,-99,"spoon 5ml, plastic (graduated)_50_IDA",2495,1,3663.77676 +Imported From One Health,Misc,-99,"stethoscope, nurse type, lightweight, single cup_1_IDA",2496,1,1542.38994 +Imported From One Health,Misc,-99,"stethoscope,Littman type,lightwght,dble cup,spares_1_IDA",2497,1,1542.38994 +Imported From One Health,Misc,-99,"stomach tube, Ch 10, sterile, disp.,125cm(06SGx03)_25_IDA",2498,1,3853.60794 +Imported From One Health,Misc,-99,"stomach tube, Ch 12, sterile, disp.,125cm(06SGx03)_25_IDA",2499,1,3853.60794 +Imported From One Health,Misc,-99,"stomach tube, Ch 12, sterile, disposable, 80 cm_100_IDA",2500,1,14460.52062 +Imported From One Health,Misc,-99,"stomach tube, Ch 14, sterile, disposable, 80 cm_100_IDA",2501,1,14460.52062 +Imported From One Health,Misc,-99,"stomach tube, Ch 16, sterile, disposable, 80 cm_100_IDA",2502,1,14460.52062 +Imported From One Health,Misc,-99,"streptomycin 1 g, powder for injection_50_IDA",2503,1,8480.7849 +Imported From One Health,Misc,-99,"suction tube no. 08, sterile, disposable_100_IDA",2504,1,11518.1052 +Imported From One Health,Misc,-99,"suction tube no. 10, sterile, disposable_100_IDA",2505,1,11518.1052 +Imported From One Health,Misc,-99,"suction tube no. 14, sterile, disposable_100_IDA",2506,1,11518.1052 +Imported From One Health,Misc,-99,"suction tube no. 16, sterile, disposable_100_IDA",2507,1,11518.1052 +Imported From One Health,Misc,-99,sulfadiazine 500mg tab_56_IDA,2508,1,1400.01834 +Imported From One Health,Misc,-99,supplementary reagents kit for Enzygnost TMB (***)_1152_IDA,2509,1,135431.4986 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile pwd-free, size 6_8X50_IDA",2510,1,91428.24264 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pre-pwd, size 6.0_8x50_IDA",2511,1,72051.05376 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pre-pwd, size 6.5_8x50_IDA",2512,1,72051.05376 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 6.5_8x50_IDA",2513,1,88049.22336 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 7.0_8x50_IDA",2514,1,91428.24264 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 7.5_8x50_IDA",2515,1,88049.22336 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 8.0_8x50_IDA",2516,1,88049.22336 +Imported From One Health,Misc,-99,"surgical gloves, latex, sterile, pwd-free,size 8.5_8x50_IDA",2517,1,88049.22336 +Imported From One Health,Misc,-99,"surgical scrub brush, sterilisable, plastic_1_IDA",2518,1,1015.60788 +Imported From One Health,Misc,-99,"suture catgut chromic (0) 1 x 150 cm, S114H_36_IDA",2519,1,12775.75194 +Imported From One Health,Misc,-99,suture catgut chromic (1) 1 x 150 cm_36_IDA,2520,1,13829.3232 +Imported From One Health,Misc,-99,suture catgut chromic (2) 1 x 150 cm_36_IDA,2521,1,14602.89222 +Imported From One Health,Misc,-99,"suture catgut chromic (2/0) 1 x 150 cm, S113H_36_IDA",2522,1,12723.54426 +Imported From One Health,Misc,-99,"suture catgut chromic (3/0) 1 x 150 cm, S112H_36_IDA",2523,1,12723.54426 +Imported From One Health,Misc,-99,"suture needles, assorted sizes, cutting_12_IDA",2524,1,526.7892 +Imported From One Health,Misc,-99,"suture needles, assorted sizes, round body_12_IDA",2525,1,578.98974 +Imported From One Health,Misc,-99,"suture polyester (0) 150 cm, non-abs., braided_36_IDA",2526,1,12438.80106 +Imported From One Health,Misc,-99,"suture polyester (2/0) 150 cm, non-abs., braided_36_IDA",2527,1,12196.7622 +Imported From One Health,Misc,-99,"suture polyester (3/0) 150 cm, non-abs., braided_36_IDA",2528,1,12196.7622 +Imported From One Health,Misc,-99,"suture silk (2/0) 45 cm + 3/8ct ndl 24.5 mm, 7633H_36_IDA",2529,1,13829.3232 +Imported From One Health,Misc,-99,"suture synth.abs.(1) 90cm+1/2ct ndl 36.5mm, V519H_36_IDA",2530,1,33880.42098 +Imported From One Health,Misc,-99,"suture synth.abs.(2/0) 70cm+3/8ct ndl 30mm, V586H_36_IDA",2531,1,30985.46514 +Imported From One Health,Misc,-99,"suture synthetic absorbable (1) 2 x 70 cm, V627H_36_IDA",2532,1,33401.09136 +Imported From One Health,Misc,-99,"suture Vicryl® (0) 70cm + 1/2 rb ndl 40mm, V352H_36_IDA",2533,1,116581.0989 +Imported From One Health,Misc,-99,"suture Vicryl® (1) 70cm + 1/2 rb ndl 48mm, V365H_36_IDA",2534,1,116581.0989 +Imported From One Health,Misc,-99,"suture Vicryl® (1) 90cm + 1/2 ct ndl 36.5mm, V519H_36_IDA",2535,1,149792.3519 +Imported From One Health,Misc,-99,"suture Vicryl® (2/0) 70cm + 3/8 ct ndl 30mm, V586H_36_IDA",2536,1,85785.46494 +Imported From One Health,Misc,-99,"suture Vicryl® (3/0) 45cm+3/8ct ndl 18.5mm, V393H_36_IDA",2537,1,85785.46494 +Imported From One Health,Misc,-99,"suture Vicryl® (3/0) 70cm+1/2rb ndl 17.5mm, V305H_36_IDA",2538,1,101351.7574 +Imported From One Health,Misc,-99,"suture Vicrylâ (0) 2 x 70 cm, V626H_24_IDA",2539,1,44582.24568 +Imported From One Health,Misc,-99,"suture Vicrylâ (1) 2 x 70 cm, V627H_36_IDA",2540,1,68292.36498 +Imported From One Health,Misc,-99,"suture Vicrylâ (2/0) 2 x 70 cm, V625H_24_IDA",2541,1,42940.18848 +Imported From One Health,Misc,-99,"suture Vicrylâ (3/0) 2 x 70 cm, V624H_24_IDA",2542,1,55957.97928 +Imported From One Health,Misc,-99,"suxamethonium chloride 100 mg/2 ml, inj.(**)_100_IDA",2543,1,36243.83238 +Imported From One Health,Misc,-99,"syringe 60 ml catheter tip+luer adapt, disp_100_IDA",2544,1,77641.63092 +Imported From One Health,Misc,-99,"syringe luer 1 ml sterile, disp., without needle_100_IDA",2545,1,5305.82682 +Imported From One Health,Misc,-99,"syringe luer 10 ml sterile, disp., without needle_100_IDA",2546,1,3953.26806 +Imported From One Health,Misc,-99,"syringe luer 10 ml, with bypacked needle 21Gx 1.5""_100_IDA",2547,1,5111.24754 +Imported From One Health,Misc,-99,"syringe luer 2 ml sterile, disp., without needle_100_IDA",2548,1,2069.17914 +Imported From One Health,Misc,-99,"syringe luer 2 ml, with bypacked ndle 23G x 1.1/4""_100_IDA",2549,1,3379.02642 +Imported From One Health,Misc,-99,"syringe luer 2ml, with bypacked needle, 21G x 1.5""_100_IDA",2550,1,3379.02642 +Imported From One Health,Misc,-99,"syringe luer 5 ml sterile, disp., without needle_100_IDA",2551,1,2747.829 +Imported From One Health,Misc,-99,"syringe luer 5 ml, with bypacked needle 21G x 1.5""_100_IDA",2552,1,3853.60794 +Imported From One Health,Misc,-99,"syringe luer 5 ml, with bypacked needle 22Gx1.1/4""_100_IDA",2553,1,3853.60794 +Imported From One Health,Misc,-99,syringes (double valve) +cannulas_1_IDA,2554,1,192537.9611 +Imported From One Health,Misc,-99,"tabletbags resealable, 80 x 100 mm, with pictogram_500_IDA",2555,1,1205.43906 +Imported From One Health,Misc,-99,tamoxifen 20mg_30_IDA,2556,1,1784.4288 +Imported From One Health,Misc,-99,"tetracycline HCl 3% skin ointment, 15 g_10_IDA",2557,1,2168.83926 +Imported From One Health,Misc,-99,"thiopental sodium 1 gram, powder for injection_50_IDA",2558,1,50841.98364 +Imported From One Health,Misc,-99,"thiopental sodium 500 mg, powder for injection_50_IDA",2559,1,36291.29196 +Imported From One Health,Misc,-99,timer 60 min. (with signal)_1_IDA,2560,1,7517.37756 +Imported From One Health,Misc,-99,tinidazole 500 mg_100_IDA,2561,1,1926.8004 +Imported From One Health,Misc,-99,"toilet soap in wrapper, 100 g_100_IDA",2562,1,17877.51042 +Imported From One Health,Misc,-99,"tourniquet (arm), cotton white, with buckle_1_IDA",2563,1,270.51318 +Imported From One Health,Misc,-99,"tramadol HCl 100 mg/2 ml, for injection_100_IDA",2564,1,6606.18504 +Imported From One Health,Misc,-99,"tuberculin (ppd) 10 iu/0.1 ml, 1.5 ml pwd inj.(**)_1_IDA",2565,1,21593.48772 +Imported From One Health,Misc,-99,"turk solution, acet. acid/gentianviolet, 100 ml_1_IDA",2566,1,7517.37756 +Imported From One Health,Misc,-99,"umbilical cord tie, 3 mm non-sterile, 100 m_1_IDA",2567,1,1589.84952 +Imported From One Health,Misc,-99,urine collecting bags pediatric 100ml_100_IDA,2568,1,9301.80636 +Imported From One Health,Misc,-99,"Vacutainer® blood coll.tube 4ml, Li-heparin, green_100_IDA",2569,1,10217.75412 +Imported From One Health,Misc,-99,"Vacutainer® blood coll.tube 4ml, plain silica, red_100_IDA",2570,1,9975.71526 +Imported From One Health,Misc,-99,"Vacutainer® tubes holder for 5, 10 & 20 ml, disp._1000_IDA",2571,1,24725.72718 +Imported From One Health,Misc,-99,valganciclovir 450 mg_60_IDA,2572,1,1439103.814 +Imported From One Health,Misc,-99,"VDRL carbon antigen (vd24), 5 ml (**)_1_IDA",2573,1,18261.92088 +Imported From One Health,Misc,-99,"vecuronium bromide 4 mg, powder for injection_25_IDA",2574,1,36243.83238 +Imported From One Health,Misc,-99,vincristine sulphate 1mg/ml inj **_5_IDA,2575,1,35569.93062 +Imported From One Health,Misc,-99,"vitamin A (retinol) 50.000 iu, gelcapsules_1000_IDA",2576,1,13686.9516 +Imported From One Health,Misc,-99,"vitamin B compound, 2 ml, for injection_100_IDA",2577,1,19661.93922 +Imported From One Health,Misc,-99,"vitamin B12 (cyanocobalamine) 1 mg/ml, 1 ml, inj._100_IDA",2578,1,5253.62628 +Imported From One Health,Misc,-99,vitamin B-6 100mg/2ml inj (pyridoxine HCl)_100_IDA,2579,1,5348.5383 +Imported From One Health,Misc,-99,"vitamin K1 (phytomenadione) 1 mg/ml, 1 ml, inj._100_IDA",2580,1,18840.91062 +Imported From One Health,Misc,-99,"vitamin K1(phytomenadione) 10 mg/ml, 1ml, inj.(*a)_100_IDA",2581,1,24198.94512 +Imported From One Health,Misc,-99,"washbottle plastic 250 ml, complete squeeze type_1_IDA",2582,1,1300.35822 +Imported From One Health,Misc,-99,"waterbag foldable, 20 L, strong quality with tap_1_IDA",2583,1,3032.57934 +Imported From One Health,Misc,-99,x-ray fixer powder for 22.5 L ( for manual use)_3.3_IDA,2584,1,9638.76438 +Imported From One Health,Misc,-99,"zinc oxide ointment 10%, 100 g_10_IDA",2585,1,7132.9671 +Imported From One Health,Misc,-99,"zinc oxide ointment 10%, 800 g_1_IDA",2586,1,6553.97736 +Imported From One Health,Misc,-99,Ethambutol400mg/isoniazid 150mg (Fatol®)_1000_CMST,2587,1,14101.5 +Imported From One Health,Misc,-99,Rifampicin 150mg/isoniazid 100mg tablet (Rifinah®)_1000_CMST,2588,1,16022.16 +Imported From One Health,Misc,-99,Amikacin sulphate 1g inj_Each_CMST,2589,1,778.26 +Imported From One Health,Misc,-99,Microscope slides-frosted end(Tropical packaging)_50_CMST,2590,1,4241.16 +Imported From One Health,Misc,-99,Microscope slides-frosted end(Tropical packaging)_50_CMST,2591,1,12280.8 +Imported From One Health,Misc,-99,Isoniazid 100mg _1000_CMST,2592,1,5191.92954 +Imported From One Health,Misc,-99,Rifampicin 150mg/isoniazid 75mg _672_CMST,2593,1,17057.46 +Imported From One Health,Misc,-99,Rifampicin 60 mg/isoniazid 30mg _672_CMST,2594,1,6340.32 +Imported From One Health,Misc,-99,Streptomycin Suphate injection 1g_Each_CMST,2595,1,13830.18 +Imported From One Health,Misc,-99,"Water for injection, 5ml_Each_CMST",2596,1,28.56 +Imported From One Health,Misc,-99,"Syringe, disposable 2ml, hypoluer with 23g needle_each_CMST",2597,1,42.84 +Imported From One Health,Misc,-99,"Syringe, disposable 5ml, hypoluer with 21g needle_each_CMST",2598,1,49.98 +Imported From One Health,Misc,-99,Ethinylestradiol 0.03mg + levonorgestrel 0.15mg_3cycles_CMST,2599,1,364.14 +Imported From One Health,Misc,-99,Copper containing IUCD (Copper T®)_Each_CMST,2600,1,414.12 +Imported From One Health,Misc,-99,Male condoms with spermicide_Box of 100_CMST,2601,1,2049.18 +Imported From One Health,Misc,-99,"Medroxyprogesterone acetate injection 150mg/mL, 1mL vial (Depo Provera®) with 2ml autodestruct syringe 22G needle_each_CMST",2602,1,785.4 +Imported From One Health,Misc,-99,Metronidazole 250mg _1000_CMST,2603,1,5654.88 +Imported From One Health,Misc,-99,"Syringes, disposable, 10ml with 21G needle_Each_CMST",2604,1,42.84 +Imported From One Health,Misc,-99,"Syringes, disposable, autodestruct, 10ml with 21G needle_Each_CMST",2605,1,357 +Imported From One Health,Misc,-99,"Benzylpenicillin 1g (1MU), PFR_Each_CMST",2606,1,42.84 +Imported From One Health,Misc,-99,"Chloramphenicol succinate 1g, PFR_Each_CMST",2607,1,107.1 +Imported From One Health,Misc,-99,"Gentamicin 10mg/ml, 2ml_Each_CMST",2608,1,692.58 +Imported From One Health,Misc,-99,Water for injections 10ml_Each_CMST,2609,1,435.54 +Imported From One Health,Misc,-99,Amoxycillin 125mg/5ml suspension_100ml_CMST,2610,1,571.2 +Imported From One Health,Misc,-99,"Syringes, hypoluer, 5ml 21g, disposable_Each_CMST",2611,1,7.14 +Imported From One Health,Misc,-99,"Syringes, hypoluer, 2ml 23g, disposable_Each_CMST",2612,1,21.42 +Imported From One Health,Misc,-99,"Syringes, hypoluer, 2ml 25g, disposable_Each_CMST",2613,1,21.42 +Imported From One Health,Misc,-99,Albendazole 400mg_100.005320936485_CMST,2614,1,428.4 +Imported From One Health,Misc,-99,Co-trimoxazole 120mg_100_CMST,2615,1,549.78 +Imported From One Health,Misc,-99,Co-trimoxazole 480mg_120_CMST,2616,1,185.64 +Imported From One Health,Misc,-99,Co-trimoxazole 480mg_60_CMST,2617,1,556.92 +Imported From One Health,Misc,-99,Co-trimoxazole 480mg_1000_CMST,2618,1,1063.86 +Imported From One Health,Misc,-99,Lamivudine 150 mg (3TC) + Zidovudine 300mg AZT_60_CMST,2619,1,74.27028 +Imported From One Health,Misc,-99,Lamivudine 150mg + Stavudine 30mg (Dual comb.)_60_CMST,2620,1,27988.8 +Imported From One Health,Misc,-99,Lamivudine 150mg + Stavudine 30mg + Nevirapine 200mg _x000B_ (Triple Combination)_60_CMST,2621,1,27988.8 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg,30x6_180_CMST",2622,1,8717.94 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg,30x12_360_CMST",2623,1,17435.88 +Imported From One Health,Misc,-99,"Lumefantrine 120mg/Artemether 20mg, 30x18_540_CMST",2624,1,26153.82 +Imported From One Health,Misc,-99,Nevirapine 200mg_60_CMST,2625,1,109820.34 +Imported From One Health,Misc,-99,Pyridoxine 25mg_1000_CMST,2626,1,9267.72 +Imported From One Health,Misc,-99,Zidovudine 300 mg_60_CMST,2627,1,5819.1 +Imported From One Health,Misc,-99,Zidovudine 300 mg + Lamivudine 150 (3TC) + Nevirapine 200mg _60_CMST,2628,1,8932.14 +Imported From One Health,Misc,-99,"Ceftriaxone 500mg, PFR_Each_CMST",2629,1,235.62 +Imported From One Health,Misc,-99,"Dextrose 50%, 20ml_Each_CMST",2630,1,903.58842 +Imported From One Health,Misc,-99,Nevirapine 10mg/ml oral solution_240ml_CMST,2631,1,29345.4 +Imported From One Health,Misc,-99,Zidovudine 10mg/ml oral solution_100ml_CMST,2632,1,1078.14 +Imported From One Health,Misc,-99,Bioline HIV 1/2 test kit _30_CMST,2633,1,8832.18 +Imported From One Health,Misc,-99,Determine HIV 1/2 test kit_100 tests_CMST,2634,1,49501.62 +Imported From One Health,Misc,-99,Unigold HIV test kit_20 tests_CMST,2635,1,50265.6 +Imported From One Health,Misc,-99,Apron laboratory sleeves_50_CMST,2636,1,66223.5 +Imported From One Health,Misc,-99,"Exacta-med oral dispensers 1ml,pack with blue seal caps_100_CMST",2637,1,24468.78 +Imported From One Health,Misc,-99,"Glove disposable latex, large_100_CMST",2638,1,1956.36 +Imported From One Health,Misc,-99,Haemacue glucose HB 301 machine_each_CMST,2639,1,375416.2805 +Imported From One Health,Misc,-99,Haemacue control HB 201 Machine_50_CMST,2640,1,509310.48 +Imported From One Health,Misc,-99,Haemacue HB 301_50_CMST,2641,1,48545.20986 +Imported From One Health,Misc,-99,Vacuette Blood Collection set (adult)_100_CMST,2642,1,14108.64 +Imported From One Health,Misc,-99,Vacuette Blood Collection set (pead)_100_CMST,2643,1,14108.64 +Imported From One Health,Misc,-99,Adult First line 1A d4T-based,2644,1,41927.24382 +Imported From One Health,Misc,-99,Adult First line 3A d4T-based,2645,1,54985.98252 +Imported From One Health,Misc,-99,Adult First line 2A AZT-based,2646,1,80255.87052 +Imported From One Health,Misc,-99,Adult First line 4A AZT-based,2647,1,90971.60394 +Imported From One Health,Misc,-99,Adult First line 5A TDF-based,2648,1,104310.2521 +Imported From One Health,Misc,-99,Adult First line 6A TDF-based,2649,1,69572.17428 +Imported From One Health,Misc,-99,Adult Second line 7A ,2650,1,263414.5706 +Imported From One Health,Misc,-99,Adult Second line 8A ,2651,1,275793.617 +Imported From One Health,Misc,-99,Paediatric First line 1P d4T-based,2652,1,57456.99372 +Imported From One Health,Misc,-99,Paediatric First line 3P d4T-based,2653,1,124846.0416 +Imported From One Health,Misc,-99,Paediatric First line 2P AZT-based,2654,1,103146.7177 +Imported From One Health,Misc,-99,Paediatric First line 4P AZT-based,2655,1,150995.5633 +Imported From One Health,Misc,-99,Paediatric Second line 9P ,2656,1,635649.6313 +Imported From One Health,Misc,-99,Doxorubicin (Adreamycin) 50mg Injection,2657,1,9128.49 +Imported From One Health,Misc,-99,Cyclophosphamide 500mg Injection,2658,1,1612.79748 +Imported From One Health,Misc,-99,Paclitaxel 300mg Injection,2659,1,48051.29322 +Imported From One Health,Misc,-99,PackTeeth,2660,1,0 +Imported From One Health,Misc,-99,Average ART cost,2661,1,0 +Imported From One Health,Misc,-99,"AlerDeterm.HIV1/2Ag/AbCombo,Wbkit/100",2662,1,963.9 +Imported From One Health,Misc,-99,"Humasis Malaria P.f Antigen, kit/25",2663,1,378.42 +Imported From One Health,Misc,-99,"Proca,benz.peni.pdr/inj 1MIU vl/BOX-50",2664,1,12159.42 +Imported From One Health,Misc,-99,"Tube Feeding, CH08, L40cm, ster,disp, 50 per box",2665,1,142.8 +Imported From One Health,Misc,-99,"Syringe, feeeding, 50ml, catheter tips, ster 50 per box",2666,1,257.04 +Imported From One Health,Misc,-99,"Soap, Toilet, bar, 100-110g, wrapped (36 per box)",2667,1,128.52 +Imported From One Health,Misc,-99,"Plaster, elastic adhesive 7.5cm x 5m",2668,1,0 +Added by JC,Misc,-99,"Forceps, obstetric",2669,1,1 +Added by JC,Misc,-99,"Vacuum, obstetric",2670,1,1 +Added by TM,Misc,-99,First-line ART regimen: adult,2671,1,1 +Added by TM,Misc,-99,First line ART regimen: older child,2672,1,1 +Added by TM,Misc,-99,First line ART regimen: young child,2673,1,1 +Added by TM,Misc,-99,Pre-exposure prophlaxis for HIV,2674,1,1 +Added by SM (Recommended by TM),Isoniazid preventative therapy for HIV+ no TB,82,Isoniazid/Rifapentine,2678,1,1 +Added by SM (Recommended by EJ),Misc,-99,Cystoscope,285,1, +Added by SM (Recommended by EJ),Misc,-99,Endoscope,280,1, +Added by SM (Recommended by EJ),Misc,-99,Prostate specific antigen test,281,1, Added by UN ,Misc,-99,Haemodialysis dialysate flow of 500 ml/min,282,1,200 -Added by WM Misc,-99,Anesthetic Eye drops, 15ml,1,1 -Added by WM Misc,-99,Aflibercept, 2mg,3,3 -Added by WM Misc,-99,Mydriatic/Dilation Drops, 15ml,1,1 -Added by WM Misc,-99,Methylcellulose,1,1 -Added by WM Misc,-99,Antiseptic solution, 15ml,1,1 -Added by WM Misc,-99,Sterile gloves and drapes,3,3 -Added by WM Misc,-99,Diagnostic dye,1,1 -Added by WM Misc,-99,Fluorescin dye,1,1 -Added by WM Misc,-99,Alcohol wipes for lens,1,1 -Added by WM Misc,-99,30G needle,1,1 -Added by WM Misc,-99,Speculum,1,1 +Added by WM,Misc,-99,"Anesthetic Eye drops, 15ml",1,1, +Added by WM,Misc,-99,"Aflibercept, 2mg",3,3, +Added by WM,Misc,-99,"Mydriatic/Dilation Drops, 15ml",1,1, +Added by WM,Misc,-99,Methylcellulose,1,1, +Added by WM,Misc,-99,"Antiseptic solution, 15ml",1,1, +Added by WM,Misc,-99,Sterile gloves and drapes,3,3, +Added by WM,Misc,-99,Diagnostic dye,1,1, +Added by WM,Misc,-99,Fluorescin dye,1,1, +Added by WM,Misc,-99,Alcohol wipes for lens,1,1, +Added by WM,Misc,-99,30G needle,1,1, +Added by WM,Misc,-99,Speculum,1,1, diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index efc872bccc..b7c6a0c42e 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -40,13 +40,13 @@ class DiabeticRetinopathy(Module): gbd_causes='Diabetes mellitus', label='Diabetes'), } PARAMETERS = { - "rate_onset_to_mild_or_moderate_dr": Parameter(Types.REAL, + "prob_onset_to_mild_or_moderate_dr": Parameter(Types.REAL, "Probability of people who get diagnosed with non-proliferative " "mild/moderate diabetic retinopathy"), - "rate_mild_or_moderate_to_severe": Parameter(Types.REAL, + "prob_mild_or_moderate_to_severe": Parameter(Types.REAL, "Probability of people who get diagnosed with severe " "diabetic retinopathy"), - "rate_severe_to_proliferative": Parameter(Types.REAL, + "prob_severe_to_proliferative": Parameter(Types.REAL, "Probability of people who get diagnosed with " "proliferative diabetic retinopathy"), @@ -97,6 +97,10 @@ class DiabeticRetinopathy(Module): Types.REAL, "Probability that clinically significant DMO requires repeat treatment at review" ), + "prob_antivegf_for_clinically_significant_dmo": Parameter( + Types.REAL, + "Probability that Anti-VEGF is selected rather than focal laser for clinically significant DMO" + ), "next_screening_if_mild_or_moderate": Parameter( Types.INT, "Number of months until next eye screening if DR status is mild or moderate" @@ -463,12 +467,12 @@ def make_the_linear_models(self) -> None: self.lm['onset_mild_or_moderate_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - intercept=p['rate_onset_to_mild_or_moderate_dr'] + intercept=p['prob_onset_to_mild_or_moderate_dr'] ) self.lm['mildmoderate_severe_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - p['rate_mild_or_moderate_to_severe'], + p['prob_mild_or_moderate_to_severe'], Predictor('had_treatment_during_this_stage', external=True) .when(True, p['rr_progression_after_treatment']), Predictor('diabetes_duration_greater_than_15_years', external=True) @@ -477,7 +481,7 @@ def make_the_linear_models(self) -> None: self.lm['severe_proliferative_dr'] = LinearModel( LinearModelType.MULTIPLICATIVE, - p['rate_severe_to_proliferative'], + p['prob_severe_to_proliferative'], Predictor('had_treatment_during_this_stage', external=True) .when(True, p['rr_progression_after_treatment']), Predictor('diabetes_duration_greater_than_15_years', external=True) @@ -706,27 +710,29 @@ def apply(self, population: Population) -> None: df.is_alive & df.nc_diabetes & (df.dr_status == 'mild_or_moderate')] diabetes_and_alive_severedr = df.loc[df.is_alive & df.nc_diabetes & (df.dr_status == 'severe')] - will_progress = self.module.lm['onset_mild_or_moderate_dr'].predict(diabetes_and_alive_nodr, self.module.rng) - # will_progress_idx = will_progress[will_progress].index - will_progress_idx = df.index[np.where(will_progress)[0]] + will_progress = self.module.lm['onset_mild_or_moderate_dr'].predict( + diabetes_and_alive_nodr, + self.module.rng, + squeeze_single_row_output=False) + will_progress_idx = will_progress[will_progress].index df.loc[will_progress_idx, 'dr_status'] = 'mild_or_moderate' mildmoderate_to_severe = self.module.lm['mildmoderate_severe_dr'].predict( diabetes_and_alive_mild_moderate_dr, self.module.rng, + squeeze_single_row_output=False, had_treatment_during_this_stage=had_treatment_during_this_stage, diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) - # moderate_to_severe_idx = moderate_to_severe[moderate_to_severe].index - mildmoderate_to_severe_idx = df.index[np.where(mildmoderate_to_severe)[0]] + mildmoderate_to_severe_idx = mildmoderate_to_severe[mildmoderate_to_severe].index df.loc[mildmoderate_to_severe_idx, 'dr_status'] = 'severe' severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict( diabetes_and_alive_severedr, self.module.rng, + squeeze_single_row_output=False, had_treatment_during_this_stage=had_treatment_during_this_stage, diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) - # severe_to_proliferative_idx = mild_to_moderate[severe_to_proliferative].index - severe_to_proliferative_idx = df.index[np.where(severe_to_proliferative)[0]] + severe_to_proliferative_idx = severe_to_proliferative[severe_to_proliferative].index df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' # Update DMO status @@ -878,7 +884,8 @@ def apply(self, person_id, squeeze_factor): if person.dmo_status == 'clinically_significant': # Randomise between AntiVEGF or Focal Laser treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ - if self.module.rng.random_sample() < 0.5 else HSI_Dr_Dmo_Focal_Laser + if self.module.rng.random_sample() < p[ + 'prob_antivegf_for_clinically_significant_dmo'] else HSI_Dr_Dmo_Focal_Laser hs.schedule_hsi_event( hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), topen=self.sim.date, @@ -1106,7 +1113,8 @@ def apply(self, person_id, squeeze_factor): if df.at[person_id, 'dmo_status'] == 'clinically_significant': if self.module.rng.random_sample() < p['prob_repeat_dmo_treatment']: treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ - if self.module.rng.random_sample() < 0.5 else HSI_Dr_Dmo_Focal_Laser + if self.module.rng.random_sample() < p[ + 'prob_antivegf_for_clinically_significant_dmo'] else HSI_Dr_Dmo_Focal_Laser hs.schedule_hsi_event( hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), topen=self.sim.date, @@ -1120,8 +1128,8 @@ class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): def __init__(self, module): """schedule logging to repeat every 1 month """ - self.repeat = 30 - super().__init__(module, frequency=DateOffset(days=self.repeat)) + self.repeat = 1 + super().__init__(module, frequency=DateOffset(months=self.repeat)) def apply(self, population): """Compute statistics regarding the current status of persons and output to the logger diff --git a/tests/test_diabetic_retinopathy.py b/tests/test_diabetic_retinopathy.py index ac2d2a31e1..9feea66ef6 100644 --- a/tests/test_diabetic_retinopathy.py +++ b/tests/test_diabetic_retinopathy.py @@ -120,23 +120,23 @@ def make_high_init_prev(sim): return sim -def incr_rate_of_onset_mild_or_moderate(sim): +def incr_prob_of_onset_mild_or_moderate(sim): # Rate of cancer onset per # months: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] = 0.05 + sim.modules['DiabeticRetinopathy'].parameters['prob_onset_to_mild_or_moderate_dr'] = 0.05 return sim -def zero_rate_of_onset_mild_or_moderate(sim): +def zero_prob_of_onset_mild_or_moderate(sim): # Rate of cancer onset per # months: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] = 0.00 + sim.modules['DiabeticRetinopathy'].parameters['prob_onset_to_mild_or_moderate_dr'] = 0.00 return sim -def incr_rates_of_progression(sim): +def incr_probs_of_progression(sim): # Rates of DR progression: - sim.modules['DiabeticRetinopathy'].parameters['rate_onset_to_mild_or_moderate_dr'] *= 4 - sim.modules['DiabeticRetinopathy'].parameters['rate_mild_or_moderate_to_severe'] *= 4 - sim.modules['DiabeticRetinopathy'].parameters['rate_severe_to_proliferative'] *= 4 + sim.modules['DiabeticRetinopathy'].parameters['prob_onset_to_mild_or_moderate_dr'] *= 4 + sim.modules['DiabeticRetinopathy'].parameters['prob_mild_or_moderate_to_severe'] *= 4 + sim.modules['DiabeticRetinopathy'].parameters['prob_severe_to_proliferative'] *= 4 return sim @@ -202,7 +202,7 @@ def test_run_sim_from_high_prevalence(seed): properties at the end""" sim = get_simulation_healthsystemdisabled(seed=seed) sim = make_high_init_prev(sim) - sim = incr_rates_of_progression(sim) + sim = incr_probs_of_progression(sim) sim.make_initial_population(n=popsize) check_dtypes(sim) check_configuration_of_population(sim) From 866c7378c3092249688842aa7b1f835aa397d597 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 31 Mar 2026 13:48:22 +0200 Subject: [PATCH 78/85] Use dictionary --- src/tlo/methods/cardio_metabolic_disorders.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/src/tlo/methods/cardio_metabolic_disorders.py b/src/tlo/methods/cardio_metabolic_disorders.py index f2ad9c75f1..17d8c73ee5 100644 --- a/src/tlo/methods/cardio_metabolic_disorders.py +++ b/src/tlo/methods/cardio_metabolic_disorders.py @@ -301,6 +301,9 @@ def __init__(self, name=None, do_log_df: bool = False, do_condition_combos: bool self.lms_event_death = dict() self.lms_event_symptoms = dict() + # Dictionary to hold date onset + self.diabetes_onset_dates = {} + def read_parameters(self, resourcefilepath: Optional[Path] = None): """Read parameter values from files for condition onset, removal, deaths, and initial prevalence. @@ -1058,6 +1061,12 @@ def schedule_death_to_occur_before_next_poll(p_id, cond): idx_acquires_condition = acquires_condition[acquires_condition].index df.loc[idx_acquires_condition, f'nc_{condition}'] = True + # Store onset dates only for diabetes + if condition == 'nc_diabetes': + for person_id in idx_acquires_condition: + if person_id not in self.diabetes_onset_dates: + self.diabetes_onset_dates[person_id] = self.sim.date + # Add incident cases to the tracker self.module.trackers['onset_condition'].add( condition, df.loc[idx_acquires_condition].groupby('age_range').size().to_dict() From d7764e9be3f8db0ad2a5c2491dbc5847c47cf380 Mon Sep 17 00:00:00 2001 From: thewati Date: Tue, 31 Mar 2026 13:56:58 +0200 Subject: [PATCH 79/85] Rollback. Changed wrong file --- src/tlo/methods/cardio_metabolic_disorders.py | 9 --------- 1 file changed, 9 deletions(-) diff --git a/src/tlo/methods/cardio_metabolic_disorders.py b/src/tlo/methods/cardio_metabolic_disorders.py index 17d8c73ee5..f2ad9c75f1 100644 --- a/src/tlo/methods/cardio_metabolic_disorders.py +++ b/src/tlo/methods/cardio_metabolic_disorders.py @@ -301,9 +301,6 @@ def __init__(self, name=None, do_log_df: bool = False, do_condition_combos: bool self.lms_event_death = dict() self.lms_event_symptoms = dict() - # Dictionary to hold date onset - self.diabetes_onset_dates = {} - def read_parameters(self, resourcefilepath: Optional[Path] = None): """Read parameter values from files for condition onset, removal, deaths, and initial prevalence. @@ -1061,12 +1058,6 @@ def schedule_death_to_occur_before_next_poll(p_id, cond): idx_acquires_condition = acquires_condition[acquires_condition].index df.loc[idx_acquires_condition, f'nc_{condition}'] = True - # Store onset dates only for diabetes - if condition == 'nc_diabetes': - for person_id in idx_acquires_condition: - if person_id not in self.diabetes_onset_dates: - self.diabetes_onset_dates[person_id] = self.sim.date - # Add incident cases to the tracker self.module.trackers['onset_condition'].add( condition, df.loc[idx_acquires_condition].groupby('age_range').size().to_dict() From d79246d98ef2d4d52e76a48e4bdfba10f9b99837 Mon Sep 17 00:00:00 2001 From: thewati Date: Fri, 17 Apr 2026 14:16:19 +0200 Subject: [PATCH 80/85] incidence and its plots --- .../diabetic_retinopathy_analyses.py | 188 +++++++----------- src/tlo/methods/diabetic_retinopathy.py | 169 ++++++++++++---- 2 files changed, 202 insertions(+), 155 deletions(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 040749f1b1..5adbe875d3 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -37,39 +37,44 @@ # The resource files resourcefilepath = Path("./resources") +# Alternative from DR calibrarion check +# root = get_root_path() +# resourcefilepath = root / "resources" + # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2012, 1, 1) -popsize = 5000 +end_date = Date(2013, 1, 1) +popsize = 2000 + def run_sim(service_availability): # log_config = { # 'filename': 'LogFile', # 'directory': outputpath # } - sim = Simulation(start_date=start_date, seed=0, log_config={"filename": "LogFile"}) + sim = Simulation(start_date=start_date, seed=0, + log_config={"filename": "LogFile"}, resourcefilepath=resourcefilepath) # Register the appropriate modules - sim.register(care_of_women_during_pregnancy.CareOfWomenDuringPregnancy(resourcefilepath=resourcefilepath), - demography.Demography(resourcefilepath=resourcefilepath), - contraception.Contraception(resourcefilepath=resourcefilepath), - enhanced_lifestyle.Lifestyle(resourcefilepath=resourcefilepath), - healthsystem.HealthSystem(resourcefilepath=resourcefilepath, - service_availability=service_availability), - symptommanager.SymptomManager(resourcefilepath=resourcefilepath), - healthseekingbehaviour.HealthSeekingBehaviour(resourcefilepath=resourcefilepath), - healthburden.HealthBurden(resourcefilepath=resourcefilepath), - labour.Labour(resourcefilepath=resourcefilepath), - newborn_outcomes.NewbornOutcomes(resourcefilepath=resourcefilepath), - pregnancy_supervisor.PregnancySupervisor(resourcefilepath=resourcefilepath), - oesophagealcancer.OesophagealCancer(resourcefilepath=resourcefilepath), - postnatal_supervisor.PostnatalSupervisor(resourcefilepath=resourcefilepath), + sim.register(care_of_women_during_pregnancy.CareOfWomenDuringPregnancy(), + demography.Demography(), + contraception.Contraception(), + enhanced_lifestyle.Lifestyle(), + healthsystem.HealthSystem(service_availability=service_availability), + symptommanager.SymptomManager(), + healthseekingbehaviour.HealthSeekingBehaviour(), + healthburden.HealthBurden(), + labour.Labour(), + newborn_outcomes.NewbornOutcomes(), + pregnancy_supervisor.PregnancySupervisor(), + oesophagealcancer.OesophagealCancer(), + postnatal_supervisor.PostnatalSupervisor(), diabetic_retinopathy.DiabeticRetinopathy(), - hiv.Hiv(resourcefilepath=resourcefilepath), - tb.Tb(resourcefilepath=resourcefilepath), - epi.Epi(resourcefilepath=resourcefilepath), - cardio_metabolic_disorders.CardioMetabolicDisorders(resourcefilepath=resourcefilepath), - depression.Depression(resourcefilepath=resourcefilepath), + hiv.Hiv(), + tb.Tb(), + epi.Epi(), + cardio_metabolic_disorders.CardioMetabolicDisorders(), + depression.Depression(), ) # Run the simulation @@ -78,111 +83,36 @@ def run_sim(service_availability): return sim.log_filepath + def get_summary_stats(logfile): output = parse_log_file(logfile) - counts_by_stage = output['tlo.methods.diabetic_retinopathy']['summary_stats'] - counts_by_stage['date'] = pd.to_datetime(counts_by_stage['date']) - counts_by_stage = counts_by_stage.set_index('date', drop=True) - - # summary = { - # 'total': counts_by_stage.filter(like='total_').sum(axis=1), - # 'off': counts_by_stage.filter(like='off_treatment_').sum(axis=1), - # 'tr': counts_by_stage.filter(like='treatment_').sum(axis=1), - # 'new_early': counts_by_stage.get('new_early', pd.Series(0, index=counts_by_stage.index)), - # 'new_late': counts_by_stage.get('new_late', pd.Series(0, index=counts_by_stage.index)) - # } - # 2) NUMBERS UNDIAGNOSED-DIAGNOSED-TREATED-PALLIATIVE CARE OVER TIME (SUMMED ACROSS TYPES OF CANCER) - def get_cols_excl_none(allcols, stub): - # helper function to some columns with a certain prefix stub - excluding the 'none' columns (ie. those - # that do not have cancer) - cols = allcols[allcols.str.startswith(stub)] - cols_not_none = [s for s in cols if ("none" not in s)] - return cols_not_none - - summary = { - 'total': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'total_')].sum(axis=1), - 'udx': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'undiagnosed_')].sum(axis=1), - 'dx': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'diagnosed_')].sum(axis=1), - 'tr': counts_by_stage[get_cols_excl_none(counts_by_stage.columns, 'treatment_')].sum(axis=1) - } - - counts_by_cascade = pd.DataFrame(summary) - # counts_by_stage['year'] = counts_by_stage.index.year - # incidence_by_stage = pd.DataFrame({'new_early': summary['new_early'], 'new_late': summary['new_late']}) - - # Rates of diagnosis per year: - counts_by_stage['year'] = counts_by_stage.index.year - annual_count_of_dxtr = counts_by_stage.groupby(by='year')[['diagnosed_since_last_log', - 'treated_since_last_log']].sum() - - return { - 'total_counts_by_stage_over_time': counts_by_stage, - 'counts_by_cascade': counts_by_cascade, - 'annual_count_of_dxtr': annual_count_of_dxtr - } - - -def plot_dr_progression(counts_by_stage, title): - """Plot stacked bars for early and late diabetic retinopathy over time.""" - - # Set the index to be years only - counts_by_stage = counts_by_stage.copy() - counts_by_stage.index = counts_by_stage.index.strftime('%Y-%m') - - fig, ax = plt.subplots(figsize=(12, 6)) - - counts_by_stage[['total_early', 'total_late']].plot( - kind='bar', stacked=True, ax=ax, colormap="viridis" - ) - - ax.set_title(title) - ax.set_xlabel("Time (Months & Years)") - ax.set_ylabel("Number of People") - ax.legend(["Early DR", "Late DR"]) - plt.xticks(rotation=45) # Rotate x-axis labels for readability - - plt.tight_layout() - plt.show() - -def plot_treatment_cascade(counts_by_cascade, title): - """Plot stacked bar chart for treatment status over time.""" + df = output['tlo.methods.diabetic_retinopathy']['summary_stats'] + df['date'] = pd.to_datetime(df['date']) + df = df.set_index('date') - counts_by_cascade = counts_by_cascade.copy() - counts_by_cascade.index = counts_by_cascade.index.strftime('%Y-%m') + return df - fig, ax = plt.subplots(figsize=(12, 6)) - counts_by_cascade[['udx', 'dx', 'tr']].plot( - kind='bar', stacked=True, ax=ax, colormap="coolwarm" - ) +def plot_prevalence(df, prefix, title): + cols = [c for c in df.columns if c.startswith(prefix)] - ax.set_title(title) - ax.set_xlabel("Time (Months & Years)") - ax.set_ylabel("Number of People") - ax.legend(['Undiagnosed', 'Diagnosed', 'On Treatment']) - plt.xticks(rotation=45) + prev = df[cols].div(df[cols].sum(axis=1), axis=0) - plt.tight_layout() + prev.plot(figsize=(12, 6)) + plt.title(title) + plt.ylabel("Prevalence") + plt.xlabel("Time") plt.show() -def plot_dr_incidence(incidence_by_stage, title): - """Plot stacked bars for new cases of early and late DR over time.""" - incidence_by_stage = incidence_by_stage.copy() - incidence_by_stage.index = incidence_by_stage.index.strftime('%Y-%m') - - print(f'Incidence data for plotting {incidence_by_stage.head()}') +def plot_incidence(df, prefix, title): + cols = [c for c in df.columns if c.startswith(prefix)] - fig, ax = plt.subplots(figsize=(12, 6)) - incidence_by_stage[['new_early', 'new_late']].plot(kind='bar', stacked=True, ax=ax, colormap="plasma") - - ax.set_title(title) - ax.set_xlabel("Time (Months & Years)") - ax.set_ylabel("Number of New Cases") - ax.legend(["New Early DR Cases", "New Late DR Cases"]) - plt.xticks(rotation=45) - plt.tight_layout() + df[cols].plot(figsize=(12, 6)) + plt.title(title) + plt.ylabel("New Cases") + plt.xlabel("Time") plt.show() @@ -193,12 +123,28 @@ def plot_dr_incidence(incidence_by_stage, title): logfile_no_healthsystem = run_sim(service_availability=[]) results_no_healthsystem = get_summary_stats(logfile_no_healthsystem) - plot_dr_progression(results_with_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (With Health System)") - plot_dr_progression(results_no_healthsystem['total_counts_by_stage_over_time'], "DR Progression Over Time (No Health System)") - plot_treatment_cascade(results_with_healthsystem['counts_by_cascade'], "Treatment Status Over Time (With Health System)") - plot_treatment_cascade(results_no_healthsystem['counts_by_cascade'], "Treatment Status Over Time (No Health System)") - # plot_dr_incidence(results_with_healthsystem['incidence_by_stage'], "DR Incidence Over Time (With Health System)") - # plot_dr_incidence(results_no_healthsystem['incidence_by_stage'], "DR Incidence Over Time (No Health System)") + df_with = get_summary_stats(logfile_with_healthsystem) + df_without = get_summary_stats(logfile_no_healthsystem) + + # WITH HEALTH SYSTEM + plot_prevalence(df_with, 'total_dr_', 'DR Prevalence (With Health System)') + plot_incidence(df_with, 'inc_dr_', 'DR Incidence (With Health System)') + + plot_prevalence(df_with, 'total_dmo_', 'DMO Prevalence (With Health System)') + plot_incidence(df_with, 'inc_dmo_', 'DMO Incidence (With Health System)') + + plot_prevalence(df_with, 'total_vision_', 'Vision Prevalence (With Health System)') + plot_incidence(df_with, 'inc_vision_', 'Vision Incidence (With Health System)') + + # WITHOUT HEALTH SYSTEM + plot_prevalence(df_without, 'total_dr_', 'DR Prevalence (No Health System)') + plot_incidence(df_without, 'inc_dr_', 'DR Incidence (No Health System)') + + plot_prevalence(df_without, 'total_dmo_', 'DMO Prevalence (No Health System)') + plot_incidence(df_without, 'inc_dmo_', 'DMO Incidence (No Health System)') + + plot_prevalence(df_without, 'total_vision_', 'Vision Prevalence (No Health System)') + plot_incidence(df_without, 'inc_vision_', 'Vision Incidence (No Health System)') except Exception as e: print(f"Error running simulation: {str(e)}") diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b7c6a0c42e..f57aaa5181 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -1,3 +1,4 @@ +import copy from pathlib import Path from typing import Optional @@ -223,6 +224,32 @@ def __init__(self): self.cons_item_codes = None # (Will store consumable item codes) self.daly_wts = dict() + import copy + + # DR incidence tracker + self.dr_incident_case_tracker = { + 'mild_or_moderate': [], + 'severe': [], + 'proliferative': [] + } + self.dr_incident_case_tracker_blank = copy.deepcopy(self.dr_incident_case_tracker) + + # DMO incidence tracker + self.dmo_incident_case_tracker = { + 'clinically_significant': [], + 'non_clinically_significant': [] + } + self.dmo_incident_case_tracker_blank = copy.deepcopy(self.dmo_incident_case_tracker) + + # Vision impairment incidence tracker + self.vision_incident_case_tracker = { + 'moderate_vision_impairment': [], + 'severe_vision_impairment': [], + 'blindness': [] + } + + self.vision_incident_case_tracker_blank = copy.deepcopy(self.vision_incident_case_tracker) + def read_parameters(self, resourcefilepath: Optional[Path] = None): """ Read all parameters and define symptoms (if any)""" self.load_parameters_from_dataframe( @@ -361,6 +388,7 @@ def initialise_simulation(self, sim: Simulation) -> None: sim.schedule_event(DiabeticRetinopathyLoggingEvent(self), sim.date + DateOffset(months=1)) self.make_the_linear_models() self.look_up_consumable_item_codes() + self.reset_incidence_trackers() # ----- DX TESTS ----- # Create the diagnostic test representing dilated eye exam for DR and DMO @@ -578,6 +606,7 @@ def update_dmo_status(self): Ensures dmo_status is none when dr_status is none/nan.""" df = self.sim.population.props p = self.parameters + old_dmo = df['dmo_status'].copy() # First reset dmo_status to 'none' for anyone without DR no_dr_mask = (df.dr_status == 'none') | df.dr_status.isna() @@ -585,6 +614,7 @@ def update_dmo_status(self): # Now only process people with valid DR status valid_dr_statuses = ['mild_or_moderate', 'severe', 'proliferative'] + dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses) & (df.dmo_status == 'none')].index dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses)].index if not dr_idx.empty: @@ -603,6 +633,17 @@ def update_dmo_status(self): p=probs ) + new_dmo = df['dmo_status'] + # changed = old_dmo != new_dmo + changed = (old_dmo == 'none') & (new_dmo != 'none') + + # Counts new cases (excludes transitions to 'none') + for status, count in new_dmo[changed].value_counts().items(): + if status != 'none': + self.dmo_incident_case_tracker[status].extend( + [self.sim.date] * count + ) + invalid_cases = df[ ((df.dr_status == 'none') | df.dr_status.isna()) & (df.dmo_status.isin(['clinically_significant', 'non_clinically_significant'])) @@ -613,10 +654,11 @@ def update_dmo_status(self): ) def update_vision_status(self): - """Update vision status for people living with diabtes""" + """Update vision status for people living with diabetes""" df = self.sim.population.props p = self.parameters rng = self.rng + old_vision = df['vision_status'].copy() alive_diabetes = df.is_alive & df.nc_diabetes if not alive_diabetes.any(): @@ -676,6 +718,21 @@ def update_vision_status(self): df.loc[impaired & df.nc_diabetes, 'vision_loss_due_to_dr'] = True + new_vision = df['vision_status'] + changed = old_vision != new_vision + + # Exclude 'normal' + for status, count in new_vision[changed].value_counts().items(): + if status != 'normal': + self.vision_incident_case_tracker[status].extend( + [self.sim.date] * count + ) + + def reset_incidence_trackers(self): + self.dr_incident_case_tracker = copy.deepcopy(self.dr_incident_case_tracker_blank) + self.dmo_incident_case_tracker = copy.deepcopy(self.dmo_incident_case_tracker_blank) + self.vision_incident_case_tracker = copy.deepcopy(self.vision_incident_case_tracker_blank) + class DrPollEvent(RegularEvent, PopulationScopeEventMixin): """An event that controls the development process of Diabetes Retinopathy (DR) and logs current states. DR diagnosis @@ -716,6 +773,9 @@ def apply(self, population: Population) -> None: squeeze_single_row_output=False) will_progress_idx = will_progress[will_progress].index df.loc[will_progress_idx, 'dr_status'] = 'mild_or_moderate' + self.module.dr_incident_case_tracker['mild_or_moderate'].extend( + [self.sim.date] * len(will_progress_idx) + ) mildmoderate_to_severe = self.module.lm['mildmoderate_severe_dr'].predict( diabetes_and_alive_mild_moderate_dr, @@ -725,6 +785,9 @@ def apply(self, population: Population) -> None: diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) mildmoderate_to_severe_idx = mildmoderate_to_severe[mildmoderate_to_severe].index df.loc[mildmoderate_to_severe_idx, 'dr_status'] = 'severe' + self.module.dr_incident_case_tracker['severe'].extend( + [self.sim.date] * len(mildmoderate_to_severe_idx) + ) severe_to_proliferative = self.module.lm['severe_proliferative_dr'].predict( diabetes_and_alive_severedr, @@ -734,6 +797,9 @@ def apply(self, population: Population) -> None: diabetes_duration_greater_than_15_years=diabetes_duration_greater_than_15_years) severe_to_proliferative_idx = severe_to_proliferative[severe_to_proliferative].index df.loc[severe_to_proliferative_idx, 'dr_status'] = 'proliferative' + self.module.dr_incident_case_tracker['proliferative'].extend( + [self.sim.date] * len(severe_to_proliferative_idx) + ) # Update DMO status self.module.update_dmo_status() @@ -817,7 +883,9 @@ def apply(self, person_id, squeeze_factor): # The person is not alive, the event did not happen: so return a blank footprint return hs.get_blank_appt_footprint() - if person["dr_on_treatment"] and not pd.isna(person["dr_date_last_screening"]): + # if person["dr_on_treatment"] and not pd.isna(person["dr_date_last_screening"]): + # return hs.get_blank_appt_footprint() + if person["dr_on_treatment"] or person["dmo_on_treatment"]: return hs.get_blank_appt_footprint() is_cons_available = self.get_consumables( @@ -1043,6 +1111,7 @@ def apply(self, person_id, squeeze_factor): self.add_equipment({'Visual acuity chart', 'Opthalmic laser system', 'Silt lamp laser delivery system', 'Indirect laser delivery system', 'Laser wide-field contact lens'}) + df.at[person_id, 'dr_on_treatment'] = True # Increment the per-person session count df.at[person_id, 'total_laser_pan_retinal_coagulation_sessions'] += 1 sessions = df.at[person_id, 'total_laser_pan_retinal_coagulation_sessions'] @@ -1126,8 +1195,7 @@ class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): """The only logging event for this module""" def __init__(self, module): - """schedule logging to repeat every 1 month - """ + """schedule logging to repeat every 1 month""" self.repeat = 1 super().__init__(module, frequency=DateOffset(months=self.repeat)) @@ -1140,39 +1208,72 @@ def apply(self, population): # Create dictionary for each subset, adding prefix to key name, and adding to make a flat dict for logging. out = {} - # Vision-related stats - vision_out = { - 'total_normal_vision': (df.vision_status == 'normal').sum(), - 'total_moderate_vision_impairment': (df.vision_status == 'moderate_vision_impairment').sum(), - 'total_severe_vision_impairment': (df.vision_status == 'severe_vision_impairment').sum(), - 'total_blindness': (df.vision_status == 'blindness').sum(), - 'vision_loss_due_to_dr': df.vision_loss_due_to_dr.sum(), - 'total_diagnosed': df.dr_diagnosed.sum(), - 'total_on_treatment': df.dr_on_treatment.sum(), - 'treatment_success_rate': df[df.dr_on_treatment & (df.vision_status == 'normal')].shape[0] / - max(1, df.dr_on_treatment.sum()) + # # Vision-related stats + # vision_out = { + # 'total_normal_vision': (df.vision_status == 'normal').sum(), + # 'total_moderate_vision_impairment': (df.vision_status == 'moderate_vision_impairment').sum(), + # 'total_severe_vision_impairment': (df.vision_status == 'severe_vision_impairment').sum(), + # 'total_blindness': (df.vision_status == 'blindness').sum(), + # 'vision_loss_due_to_dr': df.vision_loss_due_to_dr.sum(), + # 'total_diagnosed': df.dr_diagnosed.sum(), + # 'total_on_treatment': df.dr_on_treatment.sum(), + # 'treatment_success_rate': df[df.dr_on_treatment & (df.vision_status == 'normal')].shape[0] / + # max(1, df.dr_on_treatment.sum()) + # } + # + # out.update(vision_out) + + # DR prevalence + # out.update({ + # f'total_dr_{k}': v + # for k, v in df.loc[df.is_alive].dr_status.value_counts().items() + # }) + # # DMO prevalence + # out.update({ + # f'total_dmo_{k}': v + # for k, v in df.loc[df.is_alive].dmo_status.value_counts().items() + # }) + # # Vision impairment prevalence + # out.update({ + # f'total_vision_{k}': v + # for k, v in df.loc[df.is_alive].vision_status.value_counts().items() + # }) + alive = df.loc[df.is_alive] + + for state in df.dr_status.cat.categories: + # out[f'total_dr_{state}'] = (alive.dr_status == state).sum() + out[f'total_dr_{state}'] = int((alive.dr_status == state).sum()) + + for state in df.dmo_status.cat.categories: + # out[f'total_dmo_{state}'] = (alive.dmo_status == state).sum() + out[f'total_dmo_{state}'] = int((alive.dmo_status == state).sum()) + + for state in df.vision_status.cat.categories: + # out[f'total_vision_{state}'] = (alive.vision_status == state).sum() + out[f'total_vision_{state}'] = int((alive.vision_status == state).sum()) + + # DR incidence + dr_inc = { + f'inc_dr_{k}': len(v) + for k, v in self.module.dr_incident_case_tracker.items() } - out.update(vision_out) - - # Current counts, total - out.update({ - f'total_{k}': v for k, v in df.loc[df.is_alive].dr_status.value_counts().items()}) - - # Current counts, off treatment - out.update({f'off_treatment_{k}': v for k, v in df.loc[df.is_alive].loc[ - pd.isnull(df.dr_date_treatment), 'dr_status'].value_counts().items()}) - - # Current counts, on treatment (excl. palliative care) - out.update({f'treatment_{k}': v for k, v in df.loc[df.is_alive].loc[(~pd.isnull( - df.dr_date_treatment)), 'dr_status'].value_counts().items()}) + # DMO incidence + dmo_inc = { + f'inc_dmo_{k}': len(v) + for k, v in self.module.dmo_incident_case_tracker.items() + } - date_now = self.sim.date - date_lastlog = self.sim.date - pd.DateOffset(months=self.repeat) + # Vision incidence + vision_inc = { + f'inc_vision_{k}': len(v) + for k, v in self.module.vision_incident_case_tracker.items() + } - out.update({ - 'diagnosed_since_last_log': df.dr_date_diagnosis.between(date_lastlog, date_now).sum(), - 'treated_since_last_log': df.dr_date_treatment.between(date_lastlog, date_now).sum(), - }) + out.update(dr_inc) + out.update(dmo_inc) + out.update(vision_inc) logger.info(key='summary_stats', data=out) + + self.module.reset_incidence_trackers() From 93830d1f77ad043295e31ea827e086ef7d115063 Mon Sep 17 00:00:00 2001 From: Gabbie123king Date: Thu, 23 Apr 2026 09:32:47 +0200 Subject: [PATCH 81/85] use nc_diabetes_date_onset from CMD as a risk factor --- src/tlo/methods/diabetic_retinopathy.py | 31 ++++++++++++++++++------- 1 file changed, 23 insertions(+), 8 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index f57aaa5181..04cc938bd8 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -744,17 +744,32 @@ def __init__(self, module): def apply(self, population: Population) -> None: df = population.props - # Getting all those with diagnosed diabetes from the cardio_metabolic_disorders module - alive_diabetes_diagnosed_in_cmd = df.is_alive & df.nc_diabetes & df.nc_diabetes_date_diagnosis.notna() + # Getting all those with diabetes from CMD module + alive_with_diabetes = df.is_alive & df.nc_diabetes - # Compute diabetes duration (years) + # Access the diabetes_date_onset dates from CMD module + cmd_module = self.sim.modules['CardioMetabolicDisorders'] + print(f"Size of diabetes_onset_dates dictionary: {len(cmd_module.diabetes_onset_dates)}") + print(f"Keys in diabetes_onset_dates: {list(cmd_module.diabetes_onset_dates.keys())[:10]}") + diabetes_onset_series = pd.Series(cmd_module.diabetes_onset_dates) + + # Convert to pandas datetime if not already + diabetes_onset_series = pd.to_datetime(diabetes_onset_series) + + # Compute diabetes duration (years) from biological onset diabetes_duration_years = pd.Series(0.0, index=df.index) - diabetes_duration_years.loc[alive_diabetes_diagnosed_in_cmd] = ( - (self.sim.date - df.loc[alive_diabetes_diagnosed_in_cmd, 'nc_diabetes_date_diagnosis']).dt.days / 365.25 + # Calculate only for those who have onset dates recorded + has_onset_date = alive_with_diabetes & df.index.isin(diabetes_onset_series.index) + diabetes_duration_years.loc[has_onset_date] = ( + (self.sim.date - diabetes_onset_series.loc[has_onset_date]).dt.days / 365.25 ) - # Compute the boolean threshold as a variable you can inspect + print("--------------------------DEBUG---------------------------") + print(f"Number of people with diabetes and onset date: {has_onset_date.sum()}") + print(f"Total people with diabetes: {alive_with_diabetes.sum()}") + print("--------------------------DEBUG END---------------------------") + # Boolean for >15 years diabetes_duration_greater_than_15_years = diabetes_duration_years >= 15 @@ -827,7 +842,7 @@ def apply(self, population: Population) -> None: df.selected_for_eye_screening = False eligible_population_for_eye_screening = ( - (df.is_alive & df.nc_diabetes) & #todo add condition for people not to be selected again witin 1 year + (df.is_alive & df.nc_diabetes) & # todo add condition for people not to be selected again witin 1 year # (df.dr_status == 'none') & # (df.dmo_status == 'none') & (df.age_years >= 20) & @@ -891,7 +906,7 @@ def apply(self, person_id, squeeze_factor): is_cons_available = self.get_consumables( self.module.cons_item_codes['eye_screening'] ) - #todo should I create another test so that the second one is for dmo? + # todo should I create another test so that the second one is for dmo? dx_result = hs.dx_manager.run_dx_test( dx_tests_to_run='dilated_eye_exam_dr_dmo', hsi_event=self From f934aaf24b847a5747b97fb8a070baa4fca2611c Mon Sep 17 00:00:00 2001 From: Gabbie123king Date: Thu, 30 Apr 2026 09:53:32 +0200 Subject: [PATCH 82/85] use diabetes_onset_dates from CMD as a risk factor --- src/tlo/methods/diabetic_retinopathy.py | 47 +++++++++++-------------- 1 file changed, 20 insertions(+), 27 deletions(-) diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 04cc938bd8..a183f01683 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -665,8 +665,8 @@ def update_vision_status(self): return sight_threatening = ( - df.dr_status.isin(['severe', 'proliferative']) | - (df.dmo_status == 'clinically_significant') + df.dr_status.isin(['severe', 'proliferative']) | + (df.dmo_status == 'clinically_significant') ) # People on treatment should have better outcomes so should be isolated @@ -747,13 +747,11 @@ def apply(self, population: Population) -> None: # Getting all those with diabetes from CMD module alive_with_diabetes = df.is_alive & df.nc_diabetes - # Access the diabetes_date_onset dates from CMD module + # Access the diabetes_onset_dates from CMD module cmd_module = self.sim.modules['CardioMetabolicDisorders'] - print(f"Size of diabetes_onset_dates dictionary: {len(cmd_module.diabetes_onset_dates)}") - print(f"Keys in diabetes_onset_dates: {list(cmd_module.diabetes_onset_dates.keys())[:10]}") diabetes_onset_series = pd.Series(cmd_module.diabetes_onset_dates) - # Convert to pandas datetime if not already + # Convert to pandas datetime format diabetes_onset_series = pd.to_datetime(diabetes_onset_series) # Compute diabetes duration (years) from biological onset @@ -762,14 +760,9 @@ def apply(self, population: Population) -> None: # Calculate only for those who have onset dates recorded has_onset_date = alive_with_diabetes & df.index.isin(diabetes_onset_series.index) diabetes_duration_years.loc[has_onset_date] = ( - (self.sim.date - diabetes_onset_series.loc[has_onset_date]).dt.days / 365.25 + (self.sim.date - diabetes_onset_series.loc[has_onset_date]).dt.days / 365.25 ) - print("--------------------------DEBUG---------------------------") - print(f"Number of people with diabetes and onset date: {has_onset_date.sum()}") - print(f"Total people with diabetes: {alive_with_diabetes.sum()}") - print("--------------------------DEBUG END---------------------------") - # Boolean for >15 years diabetes_duration_greater_than_15_years = diabetes_duration_years >= 15 @@ -842,19 +835,19 @@ def apply(self, population: Population) -> None: df.selected_for_eye_screening = False eligible_population_for_eye_screening = ( - (df.is_alive & df.nc_diabetes) & # todo add condition for people not to be selected again witin 1 year - # (df.dr_status == 'none') & - # (df.dmo_status == 'none') & - (df.age_years >= 20) & - (pd.isna(df.dr_date_diagnosis)) & - # Add time since last screening condition - ((df.dr_date_last_screening.isna()) | - (df.dr_date_last_screening < self.sim.date - pd.DateOffset(years=1))) + (df.is_alive & df.nc_diabetes) & # todo add condition for people not to be selected again witin 1 year + # (df.dr_status == 'none') & + # (df.dmo_status == 'none') & + (df.age_years >= 20) & + (pd.isna(df.dr_date_diagnosis)) & + # Add time since last screening condition + ((df.dr_date_last_screening.isna()) | + (df.dr_date_last_screening < self.sim.date - pd.DateOffset(years=1))) ) df.loc[eligible_population_for_eye_screening, 'selected_for_eye_screening'] = ( - np.random.random_sample(size=len(df[eligible_population_for_eye_screening])) - < self.module.parameters['prob_eye_screening'] + np.random.random_sample(size=len(df[eligible_population_for_eye_screening])) + < self.module.parameters['prob_eye_screening'] ) for idx in df.index[df.selected_for_eye_screening]: @@ -865,11 +858,11 @@ def apply(self, population: Population) -> None: tclose=None) def do_at_generic_first_appt( - self, - person_id: int, - individual_properties: IndividualProperties, - schedule_hsi_event: HSIEventScheduler, - **kwargs, + self, + person_id: int, + individual_properties: IndividualProperties, + schedule_hsi_event: HSIEventScheduler, + **kwargs, ) -> None: pass From 713f4899c5e6a5a5a91fbab50a54c1b4c613f3cf Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 4 May 2026 09:38:05 +0200 Subject: [PATCH 83/85] plotting incidence and prevalence --- .../diabetic_retinopathy_analyses.py | 156 +++++++++++++++++- src/tlo/methods/diabetic_retinopathy.py | 38 ++++- 2 files changed, 178 insertions(+), 16 deletions(-) diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index 5adbe875d3..ced3222eee 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -43,7 +43,7 @@ # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2013, 1, 1) +end_date = Date(2020, 1, 1) popsize = 2000 @@ -86,11 +86,10 @@ def run_sim(service_availability): def get_summary_stats(logfile): output = parse_log_file(logfile) - df = output['tlo.methods.diabetic_retinopathy']['summary_stats'] + # Create a date column for filtering df['date'] = pd.to_datetime(df['date']) df = df.set_index('date') - return df @@ -106,16 +105,150 @@ def plot_prevalence(df, prefix, title): plt.show() +# def plot_incidence(df, prefix, title): +# cols = [c for c in df.columns if c.startswith(prefix)] +# +# df[cols].plot(figsize=(12, 6)) +# plt.title(title) +# plt.ylabel("New Cases") +# plt.xlabel("Time") +# plt.show() + + def plot_incidence(df, prefix, title): cols = [c for c in df.columns if c.startswith(prefix)] - df[cols].plot(figsize=(12, 6)) + fig, ax = plt.subplots(figsize=(12, 6)) + df[cols].plot(ax=ax) + + # Force integer y-axis ticks + from matplotlib.ticker import MaxNLocator + ax.yaxis.set_major_locator(MaxNLocator(integer=True)) + plt.title(title) - plt.ylabel("New Cases") + plt.ylabel("Number of New Cases") plt.xlabel("Time") plt.show() +def plot_dr_status(df, title_prefix): + """Plot DR status both as counts and as prevalence among diabetics""" + + # Plot 1: Absolute counts + fig, axes = plt.subplots(1, 2, figsize=(15, 6)) + + # Absolute counts + dr_cols = ['total_dr_mild_or_moderate', 'total_dr_severe', 'total_dr_proliferative'] + # for col in dr_cols: + # label = col.replace('total_dr_', '').replace('_', ' ').title() + # axes[0].plot(df.index, df[col], label=label, linewidth=2) + # axes[0].set_title(f'{title_prefix} - Absolute Counts') + # axes[0].set_xlabel('Date') + # axes[0].set_ylabel('Number of People') + # axes[0].legend() + # axes[0].grid(True, alpha=0.3) + + # Prevalence among diabetics + total_diabetics = df[dr_cols].sum(axis=1) + df['total_dr_none'] + for col in dr_cols: + label = col.replace('total_dr_', '').replace('_', ' ').title() + prevalence = (df[col] / total_diabetics * 100).fillna(0) + axes[1].plot(df.index, prevalence, label=label, linewidth=2) + axes[1].set_title(f'{title_prefix} - Prevalence Among Diabetics') + axes[1].set_xlabel('Date') + axes[1].set_ylabel('Prevalence Among Diabetics (%)') + axes[1].legend() + axes[1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.show() + + +def plot_dmo_status(df, title_prefix): + """Plot DMO status among people with DR""" + fig, axes = plt.subplots(1, 2, figsize=(15, 6)) + + dmo_cols = ['total_dmo_clinically_significant', 'total_dmo_non_clinically_significant'] + total_with_dr = df[['total_dr_mild_or_moderate', 'total_dr_severe', 'total_dr_proliferative']].sum(axis=1) + + # Absolute counts + # for col in dmo_cols: + # label = col.replace('total_dmo_', '').replace('_', ' ').title() + # axes[0].plot(df.index, df[col], label=label, linewidth=2) + # axes[0].set_title(f'{title_prefix} - Absolute Counts') + # axes[0].set_xlabel('Date') + # axes[0].set_ylabel('Number of People') + # axes[0].legend() + # axes[0].grid(True, alpha=0.3) + + # Prevalence among those with DR + for col in dmo_cols: + label = col.replace('total_dmo_', '').replace('_', ' ').title() + prevalence = (df[col] / total_with_dr * 100).fillna(0) + axes[1].plot(df.index, prevalence, label=label, linewidth=2) + axes[1].set_title(f'{title_prefix} - Prevalence Among People with DR') + axes[1].set_xlabel('Date') + axes[1].set_ylabel('Prevalence Among DR Patients (%)') + axes[1].legend() + axes[1].grid(True, alpha=0.3) + + plt.tight_layout() + plt.show() + + +def plot_dmo_by_dr_stage(df_with): + """Plot DMO prevalence stratified by DR stage""" + fig, axes = plt.subplots(1, 3, figsize=(15, 5)) + + stages = ['mild_or_moderate', 'severe', 'proliferative'] + titles = ['Mild/Moderate DR', 'Severe DR', 'Proliferative DR'] + + for idx, (stage, title) in enumerate(zip(stages, titles)): + # Need to track DMO by DR stage separately + # This may require additional logging + axes[idx].set_title(f'DMO in {title}') + axes[idx].set_ylabel('Prevalence') + + plt.tight_layout() + plt.show() + + +def plot_vision_attribution(df_with): + """Plot what proportion of vision impairment is due to DR vs other causes""" + fig, axes = plt.subplots(1, 2, figsize=(12, 5)) + + # Calculate vision loss due to DR as proportion of total vision impairment + if 'vision_loss_due_to_dr' in df_with.columns: + total_vision_impaired = (df_with['total_vision_moderate_vision_impairment'] + + df_with['total_vision_severe_vision_impairment'] + + df_with['total_vision_blindness']) + + dr_attributed = df_with['vision_loss_due_to_dr'] + + axes[0].plot(df_with.index, dr_attributed / (total_vision_impaired + 0.01) * 100) + axes[0].set_title('Vision Impairment Attributed to DR') + axes[0].set_ylabel('Percentage') + + # Stacked area chart of vision outcomes + vision_cols = ['total_vision_normal', 'total_vision_moderate_vision_impairment', + 'total_vision_severe_vision_impairment', 'total_vision_blindness'] + + if all(col in df_with.columns for col in vision_cols): + axes[1].stackplot(df_with.index, + df_with[vision_cols[0]] / df_with[vision_cols].sum(axis=1), + df_with[vision_cols[1]] / df_with[vision_cols].sum(axis=1), + df_with[vision_cols[2]] / df_with[vision_cols].sum(axis=1), + df_with[vision_cols[3]] / df_with[vision_cols].sum(axis=1), + labels=['Normal', 'Moderate', 'Severe', 'Blindness'], + alpha=0.8) + axes[1].set_title('Vision Status Distribution Over Time') + axes[1].set_ylabel('Proportion') + axes[1].legend(loc='center left', bbox_to_anchor=(1, 0.5)) + + plt.tight_layout() + plt.show() + + try: logfile_with_healthsystem = run_sim(service_availability=['*']) results_with_healthsystem = get_summary_stats(logfile_with_healthsystem) @@ -127,15 +260,21 @@ def plot_incidence(df, prefix, title): df_without = get_summary_stats(logfile_no_healthsystem) # WITH HEALTH SYSTEM - plot_prevalence(df_with, 'total_dr_', 'DR Prevalence (With Health System)') + # plot_prevalence(df_with, 'total_dr_', 'DR Prevalence (With Health System)') plot_incidence(df_with, 'inc_dr_', 'DR Incidence (With Health System)') - plot_prevalence(df_with, 'total_dmo_', 'DMO Prevalence (With Health System)') + # plot_prevalence(df_with, 'total_dmo_', 'DMO Prevalence (With Health System)') plot_incidence(df_with, 'inc_dmo_', 'DMO Incidence (With Health System)') plot_prevalence(df_with, 'total_vision_', 'Vision Prevalence (With Health System)') plot_incidence(df_with, 'inc_vision_', 'Vision Incidence (With Health System)') + plot_dr_status(df_with, 'DR Status (With Health System)') + plot_dmo_status(df_with, 'DMO Status (With Health System)') + + plot_dmo_by_dr_stage(df_with) + plot_vision_attribution(df_with) + # WITHOUT HEALTH SYSTEM plot_prevalence(df_without, 'total_dr_', 'DR Prevalence (No Health System)') plot_incidence(df_without, 'inc_dr_', 'DR Incidence (No Health System)') @@ -146,6 +285,9 @@ def plot_incidence(df, prefix, title): plot_prevalence(df_without, 'total_vision_', 'Vision Prevalence (No Health System)') plot_incidence(df_without, 'inc_vision_', 'Vision Incidence (No Health System)') + plot_dr_status(df_without, 'DR Status (Without Health System)') + plot_dmo_status(df_without, 'DMO Status (Without Health System)') + except Exception as e: print(f"Error running simulation: {str(e)}") raise diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index f57aaa5181..cbb2d4564e 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -283,6 +283,9 @@ def initialise_population(self, population: Population) -> None: df.loc[df.is_alive & ~df.nc_diabetes, 'dr_status'] = 'none' df.loc[df.is_alive & ~df.nc_diabetes, 'dmo_status'] = 'none' + df.loc[df.is_alive & df.nc_diabetes, 'dr_status'] = 'none' + df.loc[df.is_alive & df.nc_diabetes, 'dmo_status'] = 'none' + df.loc[list(alive_diabetes_idx), "dr_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dmo_on_treatment"] = False df.loc[list(alive_diabetes_idx), "dr_diagnosed"] = False @@ -342,6 +345,9 @@ def initialise_population(self, population: Population) -> None: p=probs ) + # Assign DMO for those with DR at baseline + self.update_dmo_status() + # dr_stage_probs = p["init_prob_any_dr"] # Determine the stage of DR for those who have DM: # if any_dr.sum(): @@ -615,7 +621,7 @@ def update_dmo_status(self): # Now only process people with valid DR status valid_dr_statuses = ['mild_or_moderate', 'severe', 'proliferative'] dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses) & (df.dmo_status == 'none')].index - dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses)].index + # dr_idx = df.loc[df.is_alive & df.dr_status.isin(valid_dr_statuses)].index if not dr_idx.empty: for person in dr_idx: @@ -692,6 +698,26 @@ def update_vision_status(self): # Propose new vision states proposed = transition_states(current, base_matrix, rng) + treated_idx = idx & on_treatment + if treated_idx.any(): + current_treated = df.loc[treated_idx, 'vision_status'] + proposed_treated = proposed.loc[treated_idx] + + # Keep best (min index = better vision) + vision_categories = df.vision_status.cat.categories + cat_to_int = {cat: i for i, cat in enumerate(vision_categories)} + + current_int = current_treated.map(cat_to_int) + proposed_int = proposed_treated.map(cat_to_int) + + # improved = proposed_int < current_int + not_worse = proposed_int <= current_int + + final_int = current_int.copy() + final_int[not_worse] = proposed_int[not_worse] + + int_to_cat = {i: cat for cat, i in cat_to_int.items()} + proposed.loc[treated_idx] = final_int.map(int_to_cat) # on_treatment = df.loc[idx, 'dr_on_treatment'] # @@ -744,16 +770,8 @@ def __init__(self, module): def apply(self, population: Population) -> None: df = population.props - # Getting all those with diagnosed diabetes from the cardio_metabolic_disorders module - alive_diabetes_diagnosed_in_cmd = df.is_alive & df.nc_diabetes & df.nc_diabetes_date_diagnosis.notna() - - # Compute diabetes duration (years) diabetes_duration_years = pd.Series(0.0, index=df.index) - diabetes_duration_years.loc[alive_diabetes_diagnosed_in_cmd] = ( - (self.sim.date - df.loc[alive_diabetes_diagnosed_in_cmd, 'nc_diabetes_date_diagnosis']).dt.days / 365.25 - ) - # Compute the boolean threshold as a variable you can inspect # Boolean for >15 years diabetes_duration_greater_than_15_years = diabetes_duration_years >= 15 @@ -1238,6 +1256,8 @@ def apply(self, population): # f'total_vision_{k}': v # for k, v in df.loc[df.is_alive].vision_status.value_counts().items() # }) + + #Prevalence alive = df.loc[df.is_alive] for state in df.dr_status.cat.categories: From 94056d87416fbb959704a424518507587fc0687e Mon Sep 17 00:00:00 2001 From: thewati Date: Mon, 18 May 2026 09:45:35 +0200 Subject: [PATCH 84/85] change to yearly poll and logging --- .../parameter_values.csv | 10 +++++----- src/tlo/methods/diabetic_retinopathy.py | 6 +++--- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index acf5724d95..ed9baf8866 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,12 +1,12 @@ parameter_name,value,param_label,prior_min,prior_max,prior_note init_prob_any_dr,"[0.4, 0.3, 0.3]",undetermined,"[0,0,0]","[1,1,1]", -prob_onset_to_mild_or_moderate_dr,0.29,local,0,1, -prob_mild_or_moderate_to_severe,0.5,local,0,1, -prob_severe_to_proliferative,0.07,local,0,1, +prob_onset_to_mild_or_moderate_dr,0.21,local,0,1, +prob_mild_or_moderate_to_severe,0.11,local,0,1, +prob_severe_to_proliferative,0.09,local,0,1, probs_for_dmo_when_dr_status_mild_or_moderate,"[0.7, 0.1, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_severe,"[0.3, 0.5, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_proliferative,"[0.1, 0.7, 0.2]",local,"[0,0,0]","[1,1,1]", -prob_eye_screening,0.07,local,0,1, +prob_eye_screening,0.49,local,0,1, prob_repeat_laser,0.3,local,0,1, prob_repeat_dmo_treatment,0.3,local,0,1, rp_dr_ex_alc,1.1,local,0.01,100, @@ -24,7 +24,7 @@ prob_focal_laser_success_clinically_significant,0.5,universal,0,1, prob_laser_prc_success_proliferative,0.6,universal,0,1, prob_antivegf_for_clinically_significant_dmo,0.5,local,0,1, rr_progression_after_treatment,0.5,universal,0,1, -vision_transition_matrix_no_dr,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_no_dr,"[[0.9998, 0.0002, 0, 0], [0.01, 0.985, 0.005, 0], [0, 0.02, 0.97, 0.01], [0, 0, 0.02, 0.98]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", vision_transition_matrix_sight_threatening,"[[0.970,0.025,0.005,0], [0.030,0.920,0.045,0.005], [0,0.050,0.890,0.060], [0,0,0.060,0.940]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", vision_transition_matrix_treated_sight_threatening,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", sensitivity_of_dilated_eye_exam_dr_dmo,0.8,universal,0,1, diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index 577c8f5801..b1b83a39c4 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -765,7 +765,7 @@ class DrPollEvent(RegularEvent, PopulationScopeEventMixin): begins at least after 3 years of being infected with Diabetes Mellitus.""" def __init__(self, module): - super().__init__(module, frequency=DateOffset(months=1)) + super().__init__(module, frequency=DateOffset(years=1)) def apply(self, population: Population) -> None: df = population.props @@ -1217,7 +1217,7 @@ def apply(self, person_id, squeeze_factor): if self.module.rng.random_sample() < p['prob_repeat_dmo_treatment']: treatment_for_cs_dmo = HSI_Dr_Dmo_AntiVEGF \ if self.module.rng.random_sample() < p[ - 'prob_antivegf_for_clinically_significant_dmo'] else HSI_Dr_Dmo_Focal_Laser + 'prob_antivegf_for_clinically_significant_dmo'] else HSI_Dr_Dmo_Focal_Laser hs.schedule_hsi_event( hsi_event=treatment_for_cs_dmo(module=self.module, person_id=person_id), topen=self.sim.date, @@ -1231,7 +1231,7 @@ class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): def __init__(self, module): """schedule logging to repeat every 1 month""" self.repeat = 1 - super().__init__(module, frequency=DateOffset(months=self.repeat)) + super().__init__(module, frequency=DateOffset(years=self.repeat)) def apply(self, population): """Compute statistics regarding the current status of persons and output to the logger From be82c21a284b11d37c8bdb727aa220c412b2d635 Mon Sep 17 00:00:00 2001 From: thewati Date: Thu, 18 Jun 2026 12:29:13 +0200 Subject: [PATCH 85/85] log every month and plot prev among diabetics --- .../parameter_values.csv | 12 +++++------ .../diabetic_retinopathy_analyses.py | 20 ++++++++++++++++++- src/tlo/methods/diabetic_retinopathy.py | 17 +++++++++++++--- 3 files changed, 39 insertions(+), 10 deletions(-) diff --git a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv index ed9baf8866..a1905997a5 100644 --- a/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv +++ b/resources/ResourceFile_Diabetic_Retinopathy/parameter_values.csv @@ -1,12 +1,12 @@ parameter_name,value,param_label,prior_min,prior_max,prior_note init_prob_any_dr,"[0.4, 0.3, 0.3]",undetermined,"[0,0,0]","[1,1,1]", prob_onset_to_mild_or_moderate_dr,0.21,local,0,1, -prob_mild_or_moderate_to_severe,0.11,local,0,1, -prob_severe_to_proliferative,0.09,local,0,1, +prob_mild_or_moderate_to_severe,0.2,local,0,1, +prob_severe_to_proliferative,0.15,local,0,1, probs_for_dmo_when_dr_status_mild_or_moderate,"[0.7, 0.1, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_severe,"[0.3, 0.5, 0.2]",local,"[0,0,0]","[1,1,1]", probs_for_dmo_when_dr_status_proliferative,"[0.1, 0.7, 0.2]",local,"[0,0,0]","[1,1,1]", -prob_eye_screening,0.49,local,0,1, +prob_eye_screening,0.07,local,0,1, prob_repeat_laser,0.3,local,0,1, prob_repeat_dmo_treatment,0.3,local,0,1, rp_dr_ex_alc,1.1,local,0.01,100, @@ -24,7 +24,7 @@ prob_focal_laser_success_clinically_significant,0.5,universal,0,1, prob_laser_prc_success_proliferative,0.6,universal,0,1, prob_antivegf_for_clinically_significant_dmo,0.5,local,0,1, rr_progression_after_treatment,0.5,universal,0,1, -vision_transition_matrix_no_dr,"[[0.9998, 0.0002, 0, 0], [0.01, 0.985, 0.005, 0], [0, 0.02, 0.97, 0.01], [0, 0, 0.02, 0.98]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", -vision_transition_matrix_sight_threatening,"[[0.970,0.025,0.005,0], [0.030,0.920,0.045,0.005], [0,0.050,0.890,0.060], [0,0,0.060,0.940]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", -vision_transition_matrix_treated_sight_threatening,"[[0.995,0.005,0,0], [0.005,0.985,0.010,0],[ 0,0.010,0.985,0.005],[0,0,0.005,0.995]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_no_dr,"[[0.9995,0.0005,0,0],[0.02,0.975,0.005,0],[0,0.03,0.965,0.005],[0,0,0.02,0.98]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_sight_threatening,"[[0.96,0.03,0.01,0],[0.02,0.90,0.06,0.02],[0,0.03,0.87,0.10],[0,0,0.02,0.98]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", +vision_transition_matrix_treated_sight_threatening,"[[0.997,0.003,0,0],[0.010,0.985,0.005,0],[0,0.015,0.980,0.005],[0,0,0.010,0.990]]",local,"[[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]","[[1,1,1,1],[1,1,1,1],[1,1,1,1],[1,1,1,1]]", sensitivity_of_dilated_eye_exam_dr_dmo,0.8,universal,0,1, diff --git a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py index ced3222eee..38cf8e39f2 100644 --- a/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py +++ b/src/scripts/diabetic_retinopathy_analyses/diabetic_retinopathy_analyses.py @@ -43,7 +43,7 @@ # Set parameters for the simulation start_date = Date(2010, 1, 1) -end_date = Date(2020, 1, 1) +end_date = Date(2015, 1, 1) popsize = 2000 @@ -114,6 +114,18 @@ def plot_prevalence(df, prefix, title): # plt.xlabel("Time") # plt.show() +def plot_prevalence_among_diabetics(df, prefix, title): + + cols = [c for c in df.columns if c.startswith(prefix)] + + prev = df[cols].div(df['total_alive_diabetics'], axis=0) + + prev.plot(figsize=(12,6)) + plt.title(title) + plt.ylabel("Prevalence among diabetics") + plt.xlabel("Time") + plt.show() + def plot_incidence(df, prefix, title): cols = [c for c in df.columns if c.startswith(prefix)] @@ -275,6 +287,8 @@ def plot_vision_attribution(df_with): plot_dmo_by_dr_stage(df_with) plot_vision_attribution(df_with) + plot_prevalence_among_diabetics(df_with,'total_vision_','Vision Prevalence Among Diabetics (With Health System)') + # WITHOUT HEALTH SYSTEM plot_prevalence(df_without, 'total_dr_', 'DR Prevalence (No Health System)') plot_incidence(df_without, 'inc_dr_', 'DR Incidence (No Health System)') @@ -288,6 +302,10 @@ def plot_vision_attribution(df_with): plot_dr_status(df_without, 'DR Status (Without Health System)') plot_dmo_status(df_without, 'DMO Status (Without Health System)') + plot_prevalence_among_diabetics(df_without, 'total_vision_', 'Vision Prevalence Among Diabetics (No Health System)') + + + except Exception as e: print(f"Error running simulation: {str(e)}") raise diff --git a/src/tlo/methods/diabetic_retinopathy.py b/src/tlo/methods/diabetic_retinopathy.py index b1b83a39c4..220c4adc3e 100644 --- a/src/tlo/methods/diabetic_retinopathy.py +++ b/src/tlo/methods/diabetic_retinopathy.py @@ -666,7 +666,15 @@ def update_vision_status(self): rng = self.rng old_vision = df['vision_status'].copy() - alive_diabetes = df.is_alive & df.nc_diabetes + # alive_diabetes = df.is_alive & df.nc_diabetes + alive_diabetes = ( + df.is_alive & + df.nc_diabetes & + ( + (df.dr_status != "none") | + (df.dmo_status != "none") + ) + ) if not alive_diabetes.any(): return @@ -765,7 +773,7 @@ class DrPollEvent(RegularEvent, PopulationScopeEventMixin): begins at least after 3 years of being infected with Diabetes Mellitus.""" def __init__(self, module): - super().__init__(module, frequency=DateOffset(years=1)) + super().__init__(module, frequency=DateOffset(months=1)) def apply(self, population: Population) -> None: df = population.props @@ -1231,7 +1239,7 @@ class DiabeticRetinopathyLoggingEvent(RegularEvent, PopulationScopeEventMixin): def __init__(self, module): """schedule logging to repeat every 1 month""" self.repeat = 1 - super().__init__(module, frequency=DateOffset(years=self.repeat)) + super().__init__(module, frequency=DateOffset(months=self.repeat)) def apply(self, population): """Compute statistics regarding the current status of persons and output to the logger @@ -1288,6 +1296,9 @@ def apply(self, population): # out[f'total_vision_{state}'] = (alive.vision_status == state).sum() out[f'total_vision_{state}'] = int((alive.vision_status == state).sum()) + # To calculate prevalence among total alive diabetics + out['total_alive_diabetics'] = int(alive.nc_diabetes.sum()) + # DR incidence dr_inc = { f'inc_dr_{k}': len(v)