EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks | Zendy

Samuel M. Jenness | Zendy; Steven M. Goodreau | Zendy; Martina Morris | Zendy

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EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks

Author(s) -

Samuel M. Jenness,

Steven M. Goodreau,

Martina Morris

Publication year - 2018

Publication title -

journal of statistical software

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.636

H-Index - 145

ISSN - 1548-7660

DOI - 10.18637/jss.v084.i08

Subject(s) - computer science , r package , infectious disease (medical specialty) , exponential random graph models , software package , population , software , theoretical computer science , data science , graph , machine learning , random graph , programming language , disease , medicine , demography , pathology , sociology

Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel , designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel , designed to facilitate the exploration of novel research questions for advanced modelers.

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