Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes

TL;DR

Epidemia is an R package that enables semi-mechanistic Bayesian modeling of infectious diseases, incorporating transmission dynamics and allowing for estimation, simulation, and evaluation of epidemiological quantities.

Contribution

The paper introduces epidemia, a novel R package that models infectious disease spread using semi-mechanistic Bayesian methods based on point processes.

Findings

Allows estimation of reproduction numbers and latent infections.

Enables evaluation of control measures' effects.

Supports epidemic simulation and forecasting.

Abstract

This article introduces epidemia, an R package for Bayesian, regression-oriented modeling of infectious diseases. The implemented models define a likelihood for all observed data while also explicitly modeling transmission dynamics: an approach often termed as semi-mechanistic. Infections are propagated over time using renewal equations. This approach is inspired by self-exciting, continuous-time point processes such as the Hawkes process. A variety of inferential tasks can be performed using the package. Key epidemiological quantities, including reproduction numbers and latent infections, may be estimated within the framework. The models may be used to evaluate the determinants of changes in transmission rates, including the effects of control measures. Epidemic dynamics may be simulated either from a fitted model or a prior model; allowing for prior/posterior predictive checks, experimentation, and forecasting.