Python tools for short-term forecasting
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Updated
Jul 13, 2026 - Python
Python tools for short-term forecasting
A curated list of awesome resources for infectious disease modeling.
Comprehensive collection of 8 clinical data science and health analytics projects focusing on disease prediction, risk stratification, and treatment pattern analysis using advanced machine learning algorithms and statistical modeling. Portfolio: https://nana-safo-duker.github.io/
Locally-hosted web application for visualization of hubverse formatted observations and model forecasts and for annotation of data and models.
Materials for the in-person "Modelling for Pandemic Preparedness and Response" Modular Shortcourse
A program to visualise simulations of an infectious disease spreading through a procedurally generated basic town.
Calibration tools for agent-based epidemiological models built with epiworldR
Python codes used for analyzing large datasets for machine learning, statistics, data cleaning and structuring, visualizations, etc.
A replication in Python and PyRenew of a renewal model written in Epidemia for forecasting influenza hospital admissions.
Using OPTICS clustering to group US states by Covid-19 trends in hospitalizations and other metrics.
AI/ML epidemiology portfolio for infectious disease outbreak forecasting, surveillance modeling, and reproducible public health analytics.
This repository contains codes developed in 2022 to simulate the proposed Mobile Human Ad Hoc Network model to simulate the infectious disease spread based on airborne transmission.
A TabNet-based, Bayesian-optimized pipeline for predicting typhoid fever diagnosis from Bangladeshi clinical biomarker data.
Plans to be run by Cursor AI plan agents to build a project to start a learning journey about the epidemiology and modeling approaches of an infectious disease
Integrative network modelling of patient movement pathways
Deterministic compartmental models (IR & SIR) for infectious disease dynamics in R from evidence synthesis to vaccination threshold analysis using deSolve & tidyverse.
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