Multi-species SIR models from a dynamical bayesian perspective

Authors

Lili Zhuang, Ohio State University
Noel Cressie, University of WollongongFollow
Laura Pomeroy, Ohio State University
Daniel Janies, University of North Carolina at Charlotte

Publication Date

2013

Recommended Citation

Zhuang, Lili; Cressie, Noel; Pomeroy, Laura; and Janies, Daniel, Multi-species SIR models from a dynamical bayesian perspective, Centre for Statistical and Survey Methodology, University of Wollongong, Working Paper 5-13, 2013.
https://ro.uow.edu.au/cssmwp/123

Abstract

Multi-species compartment epidemic models, such as the multispecies SIR (susceptible-infectious-recovered) model, are extensions of classic SIR models, used to explore the transient dynamics of pathogens that infect multiple hosts in a large population. In this article, we propose a dynamical Bayesian hierarchical SIR (HSIR) model, to capture the stochastic or random nature of an epidemic process in a multi-species SIR (with recovered becoming susceptible again) dynamical setting, under hidden mass-balance constraints. We call this an MSIRB model. Different from a classic multi-species SIR model (which we call MSIRc), our approach imposes mass balance on the underlying.