ArticlePathogens and disease2018
Implementation and applications of EMOD, an individual-based multi-disease modeling platform.
Article in Pathogens and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 2 of them syntheses that pooled it.
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Who cites it
67 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025Pooled it
- Calibration of individual-based models to epidemiological data: A systematic review.PLoS computational biology · 2020Pooled it
- Gender-responsive infectious disease models: Guidelines and systematic scoping review.Dialogues in health · 2026Review
- Cost-effectiveness of providing pre-exposure and post-exposure prophylaxis for the prevention of HIV via online pharmacies in western Kenya: a modelling study.The Lancet. Global health · 2026Article
- MEmilio: a high performance Modular EpideMIcs simuLatIOn software for multi-scale and comparative simulations of infectious disease dynamics.Scientific reports · 2026Article
- Modelling the impact of adopting new-generation insecticide-treated nets on malaria transmission and insecticide resistance.Parasites & vectors · 2026Article
- Projected burden of hypertension-associated cardiovascular disease in people living with HIV versus HIV-negative adults in Eswatini.medRxiv : the preprint server for health sciences · 2026Article
- Less is more: modelling the impact of species-targeted versus broadcast larviciding in Anopheles funestus-dominated malaria transmission settings.Malaria journal · 2026Article
- Optimizing the impact of a novel spatial repellent on malaria incidence in Western Kenya.Epidemiology and infection · 2026Article
- Assessing the potential impact of the RTS,S/ASO1 vaccine on malaria burden in Benin: a mathematical modelling approach.Malaria journal · 2026Article
- The age and sex dynamics of heterosexual HIV transmission in Zambia: an HPTN 071 (PopART) phylogenetic and modelling study.medRxiv : the preprint server for health sciences · 2026Article
- Evaluating the biomedical and behavioral drivers of HIV incidence decline in adolescent girls and young women in Uganda: A mathematical modeling study.PLoS medicine · 2026Article
- Graph neural network surrogates to leverage mechanistic expert knowledge towards reliable and immediate pandemic response.Scientific reports · 2026Article
- Identifying priority populations for HIV interventions using acquisition and transmission indicators: a combined analysis of 15 mathematical models from ten African countries.The lancet. HIV · 2026Article
- Gaussian process emulation for exploring complex infectious disease models.PLoS computational biology · 2025Article
- Impacts of US Bilateral Aid Disruptions on HIV Resurgence in Zambia: A Mathematical Modeling Study.Open forum infectious diseases · 2025Article
- Article
- Gaussian Process Emulation for Exploring Complex Infectious Disease Models.medRxiv : the preprint server for health sciences · 2025Article
- Uncovering the impact of randomness in HIV hotspot formation: A mathematical modeling study.PLoS computational biology · 2025Article
- Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing.Infectious Disease Modelling · 2025Article
7 more citing papers are in PubMed but not listed here.
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Authors and funding
28 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach developed with formal software support. The epidemiological modeling software, EMOD, has undergone a decade of software development. It is structured so that a majority of code is shared across disease modeling including malaria, HIV, tuberculosis, dengue, polio and typhoid. In additional to implementation efficiency, the sharing increases code usage and testing. The freely available codebase also includes hundreds of regression tests, scientific feature tests and component tests to help verify functionality and avoid inadvertent changes to functionality during future development. Here we describe the levels of detail, flexible configurability and modularity enabled by EMOD and the role of software development principles and processes in its development.
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