title: A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods.
abstract: Recent Bayesian methods for the analysis of infectious disease outbreak data using stochastic epidemic models are reviewed. These methods rely on Markov chain Monte Carlo methods. Both temporal and non-temporal data are considered. The methods are illustrated with a number of examples featuring different models and datasets.
authors.affiliation: School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK. pdo@maths.nott.ac.uk
authors.forename: Philip D
authors.initials: PD
authors.lastname: O'Neill
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D004196:Disease Outbreaks; D004812:Epidemiologic Methods; D006801:Humans; D008390:Markov Chains; D008954:Models, Biological; D009010:Monte Carlo Method; D013269:Stochastic Processes