Modeling of Epidemics using Hierarchical Bayesian Models

Flexibly specify and fit Bayesian statistical models for epidemics. 'epidemia' leverages Rs formula interface so that users can parameterize reproduction numbers and ascertainment rates in terms of predictors. Infections are propagated over time using self-exciting point processes. Multiple regions can be modeled simultaneously with multilevel models. The models and framework behind the package are described in Bhatt et al. (2021) . The design of the package has been inspired by, and has borrowed from, 'rstanarm' (Goodrich et al., 2020) < https://mc-stan.org/rstanarm/>. 'rstan' (Stan Development Team, 2020) < https://mc-stan.org/> is used as the back end for fitting models.

epidemia

The epidemia package allows researchers to flexibly specify and fit Bayesian epidemiological models in the style of Flaxman et al. (2020). The package leverages R’s formula interface to parameterize the time-varying reproduction rate as a function of covariates. Multiple populations can be modeled simultaneously with hierarchical models. The design of the package has been inspired by, and has borrowed from, rstanarm (Goodrich et al. 2020). epidemia uses rstan (Stan Development Team 2020) as the backend for fitting models.

Disclaimer

This is an early beta release of the package. As a beta release, there will be regular updates with additional features and more extensive testing. Any feedback is greatly appreciated

• in particular if you find bugs, find the documentation unclear, or have feature requests, please report them here.

Package Website

To get started, please see the package website, where you can find installation instructions, function documentation, and vignettes.