All of the software listed below are written in the R statistical computing language, with some C++ code embedded to increase computational efficiency. Each package may be accessed and installed in R using the links provided. My preferred tool for interactive R coding and data analysis is Rstudio, when I'm not using Hyak supercomputer.


Website    CRAN    Github

Tools for simulating mathematical models of infectious disease. Epidemic model classes include deterministic compartmental models, stochastic agent-based, and stochastic network models. Network models use robust statistical methods of exponential-family random graph models (ERGMs) from the Statnet suite of software packages in R. Standard templates for epidemic modeling include SI, SIR, and SIS disease types. EpiModel features an easy API for extending these templates to address novel scientific research aims.



EpiModelHIV is an extension package to EpiModel for simulating network models for HIV transmission dynamics, based on generalized framework of heterosexual mixing within couples in Sub-Saharan Africa and men who have sex with men (MSM) in the United States. In contrast to EpiModel, EpiModelHIV development has been driven by specific research needs versus a general platform, but ongoing expansion efforts will include different subpopulations for persons at risk of infection.



tergmLite addresses the computational burdens of simulating dynamic contact networks with ERGMs by representing these networks in a more data-efficient manner than the more flexible Statnet implementations. This representation results in a 25-50x increase in the speed of simulating these networks within epidemic modeling projects.



EpiModelHPC supports simulating large-scale stochastic network models on modern high-performance computing systems. Functionality provided to simulate models in parallel using either single-node, multiple-core or multiple-node setups.