title: Bayesian model choice and infection route modelling in an outbreak of Norovirus.
abstract: A data set from an outbreak of gastroenteritis in a school is analysed using a stochastic transmission model. The causative agent of the outbreak is believed to be a Norovirus, spread through person-to-person contact. Particular attention is given to the question of whether or not vomiting episodes enhance the spread of the virus via aerosol transmission. The methodology developed uses Bayesian model choice, implemented with reversible-jump Markov chain Monte Carlo methods. The methodology appears to be highly sensitive to assumptions made concerning the data, which provides some assurance that the conclusions are driven by observations rather than the underlying model and methodology.
authors.affiliation: School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, U.K. pdo@maths.nott.ac.uk
authors.forename: Philip D
authors.initials: PD
authors.lastname: O'Neill
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Marks
mesh_terms: D001499:Bayes Theorem; D017250:Caliciviridae Infections / Q000453:epidemiology* / Q000503:physiopathology / Q000635:transmission / Q000821:virology; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004739:England / Q000453:epidemiology; D005260:Female; D005759:Gastroenteritis / Q000453:epidemiology* / Q000503:physiopathology / Q000821:virology; D006801:Humans; D008297:Male; D015233:Models, Statistical; D029322:Norovirus / Q000472:pathogenicity*; D013269:Stochastic Processes