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Multi-species SIR models from a dynamical bayesian perspective
Centre for Statistical & Survey Methodology Working Paper Series
  • Lili Zhuang, Ohio State University
  • Noel Cressie, University of Wollongong
  • Laura Pomeroy, Ohio State University
  • Daniel Janies, University of North Carolina at Charlotte
Publication Date
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.
Citation Information
Lili Zhuang, Noel Cressie, Laura Pomeroy and Daniel Janies. "Multi-species SIR models from a dynamical bayesian perspective" (2013)
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