stochasticGEM: R Package for Fitting Stochastic General Epidemic Models

stochasticGEM is a publicly available package that implements Bayesian inference for partially observed stochastic epidemics. The general epidemic model is used for estimating the parameters governing the infectious and incubation period length, and the parameters governing susceptibility. In real-life epidemics the infection process is unobserved, and the data consists of the times individuals are detected, usually via appearance of symptoms. The stochasticGEM package fits several variants of the general epidemic model, namely the stochastic SIR with Markovian and nonMarkovian infectious periods. The estimation is based on Markov chain Monte Carlo algorithm.

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