A Bayesian modelling framework with model comparison for epidemics with super-spreading.

ABSTRACT: The transmission dynamics of an epidemic are rarely homogeneous. Super-spreading events and super-spreading individuals are two types of heterogeneous transmissibility. Inference of super-spreading is commonly carried out on secondary case data, the expected distribution of which is known as the offspring distribution. However, this data is seldom available. Here we introduce a multi-model framework fit to incidence time-series, data that is much more readily available. The framework consists of five discrete-time, stochastic, branching-process models of epidemics spread through a susceptible population. The framework includes a baseline model of homogeneous transmission, a unimodal and a bimodal model for super-spreading events, as well as a unimodal and a bimodal model for super-spreadin

SUBMITTER: Craddock H 

PROVIDER: S-EPMC12351329 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature