EpiModel - Mathematical Modeling of Infectious Disease Dynamics

Tools for simulating mathematical models of infectious disease dynamics. Epidemic model classes include deterministic compartmental models, stochastic individual-contact 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 API for extending these templates to address novel scientific research aims. Full methods for EpiModel are detailed in Jenness et al. (2018, <doi:10.18637/jss.v084.i08>).

Last updated 17 days ago

agent-based-modelingepidemicsepidemiologyinfectious-diseasesnetwork-graph

11.48 score 247 stars 315 scripts 1.2k downloads

networkLite - An Simplified Implementation of the 'network' Package Functionality

An implementation of some of the core 'network' package functionality based on a simplified data structure that is faster in many research applications. This package is designed for back-end use in the 'statnet' family of packages, including 'EpiModel'. Support is provided for binary and weighted, directed and undirected, bipartite and unipartite networks; no current support for multigraphs, hypergraphs, or loops.

Last updated 4 days ago

5.03 score 1 stars 12 packages 1 scripts 3.0k downloads

tergmLite - Fast Simulation of Simple Temporal Exponential Random Graph Models

Provides functions for the computationally efficient simulation of dynamic networks estimated with the statistical framework of temporal exponential random graph models, implemented in the 'tergm' package.

Last updated 2 years ago

1.70 score 5 scripts 238 downloads