EpiModel: Mathematical Modeling of Infectious Disease

Samuel M. Jenness, Steven M. Goodreau, Martina Morris


The EpiModel package provides tools for simulating mathematical models of infectious disease dynamics. Epidemic model classes include deterministic compartmental models, stochastic agent-based models, and stochastic network models. Network models use the 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.

This vignette is a placeholder for the EpiModel tutorials and documentation hosted online and external to the package to minimize testing and building timing. Tutorials may be found at the EpiModel website (http://epimodel.org).

A good place to start learning about EpiModel is the main methods paper. It is currently in press at the Journal of Statistical Software but available as pre-press at bioRxiv here: https://www.biorxiv.org/content/early/2017/11/03/213009.

Within the package, please consult the extensive help documentation:

help(package = "EpiModel")

To see the latest updates to EpiModel, consult the software NEWS:

news(package = "EpiModel")

If using EpiModel for teaching or research, please include a citation:

Jenness SM, Goodreau SM, Morris M. EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks. bioRxiv 2017; 213009. DOI: https://doi.org/10.1101/213009.