Awesome Infectious Disease Modeling

A curated¹ list of awesome resources on infectious disease modeling².

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Contents

• Modeling Software & Tools
• Surveillance & Data Systems
• Epidemiological Databases
• Organizations & Networks
• Journals & Publications
• Educational Resources
• People
• Related Awesome Lists

Modeling Software & Tools

R Packages

1. EpiModel: Mathematical models of infectious disease dynamics (deterministic compartmental, stochastic individual-contact, network models using ERGMs).
2. EpiEstim: Real-time reproduction number (Rt) estimation.
3. surveillance: Temporal and spatio-temporal outbreak detection.

Standalone Software

1. STEM (Spatiotemporal Epidemiological Modeler): Eclipse Foundation open-source platform for global disease spread modeling.
2. EPIMOD: Agent-based modeling framework.
3. OpenMalaria: Microsimulation model of malaria epidemiology and control.
4. GLEAM (Global Epidemic and Mobility Model): Large-scale epidemic modeling with human mobility data.

Climate-Sensitive Disease Tools

Per The Lancet Planetary Health (2023), 37 validated tools model climate-sensitive infectious diseases:

• VECTRI: Vector-borne disease community model (malaria).
• DyMSiM: Dynamic Mosquito Simulation Model (dengue, West Nile virus).
• HYDREMATS: Hydrology, Entomology, and Malaria Transmission Simulator.
• ArboMAP: Arbovirus mapping and prediction (West Nile virus).
• BODA: Bayesian Outbreak Detection Algorithm (campylobacteriosis).

Machine Learning Tools

1. EPIDEMIA: Bayesian hierarchical models for epidemic data.
2. Metaculus COVID-19 Models: Community forecasting platform.

Surveillance & Data Systems

Global Systems

1. WHO Global Outbreak Alert and Response Network (GOARN): International outbreak response coordination.
2. WHO Global Influenza Surveillance and Response System (GISRS): Influenza virus tracking for vaccine development.
3. WHO Global Antimicrobial Resistance Surveillance System (GLASS): AMR data collection and analysis.
4. HealthMap: Automated disease outbreak monitoring from online sources.
5. ProMED-mail: Internet-based disease outbreak reporting system.
6. GPHIN (Global Public Health Intelligence Network): WHO-partnered early warning system scanning web sources.
7. Hantascan: Live global hantavirus map showing reported cases, deaths, country totals, and outbreak locations.

United States

1. CDC National Notifiable Diseases Surveillance System (NNDSS): U.S. disease case surveillance from all states.
2. CDC WONDER: Public health data query system (mortality, natality, cancer, TB, vaccinations).
3. FluView: CDC weekly influenza surveillance reports.
4. COVID-19 Forecast Hub: Ensemble forecasts from multiple modeling teams.

Regional Networks

1. CORDS (Connecting Organisations for Regional Disease Surveillance): Six regional networks in 28 countries (Africa, Asia, Middle East, Europe).

Epidemiological Databases

1. WHO Global Health Observatory (GHO): 1,000+ health topics indicators across 194 WHO Member States.
2. WHO Data Collections: Disease-specific data (TB, HIV, malaria, NCDs).
3. CDC Surveillance Systems: Multiple disease-specific surveillance networks.
4. European CDC Surveillance Portal: EU/EEA communicable disease data.

Organizations & Networks

1. Institute for Disease Modeling (IDM): Bill & Melinda Gates Foundation research institute developing freely available modeling tools.
2. MIDAS (Models of Infectious Disease Agent Study): NIH-funded network of researchers, software, and data.
3. CEID (Center for Infectious Disease Dynamics): Penn State research center.
4. Task Force for Global Health - Disease Surveillance: SONAR program strengthening outbreak notification in LMICs.

Journals & Publications

1. PLOS Computational Biology: Open access, includes disease modeling papers.
2. Epidemics: Elsevier journal focused on infectious disease dynamics.
3. Journal of Theoretical Biology: Mathematical biology including epidemiology.
4. Eurosurveillance: European CDC journal on communicable disease epidemiology and control.
5. Emerging Infectious Diseases: CDC monthly open-access journal.
6. The Lancet Infectious Diseases: High-impact clinical and public health research.

Educational Resources

Online Courses

1. Coursera Epidemiology Specialization: University of North Carolina at Chapel Hill.
2. Johns Hopkins Epidemiology in Public Health Practice: Modeling infectious diseases specialization.
3. Imperial College London Infectious Disease Modeling: Short courses and workshops.

Textbooks & Guides

1. Modeling Infectious Diseases in Humans and Animals by Keeling & Rohani (2008): Standard textbook.
2. Mathematical Models in Epidemiology by Brauer, Castillo-Chavez & Feng (2019).
3. An Introduction to Infectious Disease Modelling by Vynnycky & White (2010).

Tutorials

1. EpiModel Tutorials: Step-by-step R package tutorials.
2. STEM Documentation: Spatiotemporal Epidemiological Modeler guides.

People

• Samuel Jenness - Emory University. Creator and lead developer of the EpiModel R package for network-based infectious disease modeling.
• Sam Abbott - Epiforecasts. Developer of EpiNow2 for real-time Rt estimation and nowcasting, widely used during COVID-19.
• Sebastian Funk - London School of Hygiene & Tropical Medicine. Leads the Epiforecasts group, develops statistical and mechanistic models for infectious disease forecasting.
• Nicholas Reich - UMass Amherst. Leads the US COVID-19 Forecast Hub and CDC FluSight influenza forecasting initiative.
• Adam Kucharski - London School of Hygiene & Tropical Medicine. Author of "The Rules of Contagion." Key figure in early COVID-19 R0 estimation.
• Simon Frost - Microsoft Health Futures / LSHTM. Creator of the epirecipes project, a multilanguage cookbook of infectious disease transmission models.
• Christian Althaus - University of Bern. Develops rapid, open-source outbreak analysis models for emerging epidemics.

Related Awesome Lists

• Awesome Healthcare - Open source healthcare software, libraries, tools, and resources.
• Awesome Computational Biology - Computational biology resources.
• Awesome Parasite - Host-parasite information and resources.
• Awesome Bioinformatics - Bioinformatics libraries and software.

Contributing

Notice anything missing that would be a good fit? If interested in contributing, please see the contributing file for further direction.

Code of Conduct

Please see the code of conduct.

License

To the extent possible under law, O957 has waived all copyright and related or neighboring rights to this work.

Footnotes

1. This list follows specific scoping guidelines. Modeling Software & Tools covers R packages, standalone software, climate-sensitive disease tools, and machine learning tools for epidemic modeling. Surveillance & Data Systems includes global, US, and regional disease surveillance networks. Epidemiological Databases lists health data repositories from WHO and other agencies. Organizations & Networks features research institutes and collaborative networks. Journals & Publications covers peer-reviewed journals in epidemiology and disease modeling. Educational Resources includes online courses, textbooks, and tutorials. ↩

2. (from Wikipedia, see citation at the bottom) Mathematical models can project how infectious diseases progress to show the likely outcome of an epidemic (including in plants) and help inform public health and plant health interventions. Models use basic assumptions or collected statistics along with mathematics to find parameters for various infectious diseases and use those parameters to calculate the effects of different interventions, like mass vaccination programs. The modelling can help decide which intervention(s) to avoid and which to trial, or can predict future growth patterns, etc. CITATION: Wikipedia contributors. "Mathematical modelling of infectious diseases." Wikipedia. Last modified September 30, 2025. Accessed October 24, 2025. https://en.wikipedia.org/wiki/Mathematical_modelling_of_infectious_diseases. ↩

3. Image used under the Unsplash License, i.e. "All images can be downloaded and used for free", "Commercial and non-commercial purposes", and "No permission needed (though attribution is appreciated!)". Image Link: https://unsplash.com/photos/a-group-of-blue-and-green-cells-on-a-white-surface-VYUNnjcHyNw. Image Description: "This digitally-colorized, negative-stained transmission electron microscopic (TEM) image depicted a number of Influenza A virions.". Image Photographer: CDC. ↩