title: Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry.
abstract: Infectious diseases exert a large and in many contexts growing burden on human health, but violate most of the assumptions of classical epidemiological statistics and hence require a mathematically sophisticated approach. Viral shedding data are collected during human studies-either where volunteers are infected with a disease or where existing cases are recruited-in which the levels of live virus produced over time are measured. These have traditionally been difficult to analyse due to strong, complex correlations between parameters. Here, we show how a Bayesian approach to the inverse problem together with modern Markov chain Monte Carlo algorithms based on information geometry can overcome these difficulties and yield insights into the disease dynamics of two of the most prevalent human pathogens-influenza and norovirus-as well as Ebola virus disease.
authors: School of Mathematics, University of Manchester, Oxford Road, Manchester M13 9PL, UK Warwick Infectious Disease Epidemiology Research Centre (WIDER), Warwick Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK thomas.house@manchester.ac.uk.
authors: Thomas
authors: 0000-0001-5835-8062
authors: T
authors: House
authors: School of Mathematics, University of Bristol, Bristol BS8 1TW, UK.
authors: Ashley
authors: A
authors: Ford
authors: Department of Statistics, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
authors: Shiwei
authors: S
authors: Lan
authors: Warwick Infectious Disease Epidemiology Research Centre (WIDER), Warwick Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
authors: Samuel
authors: S
authors: Bilson
authors: Warwick Infectious Disease Epidemiology Research Centre (WIDER), Warwick Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK Complexity Science Doctoral Training Centre, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
authors: Elizabeth
authors: E
authors: Buckingham-Jeffery
authors: Department of Statistics, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
authors: Mark
authors: M
authors: Girolami
mesh_terms: D001499:Bayes Theorem; D017250:Caliciviridae Infections / Q000453:epidemiology / Q000635:transmission; D029043:Ebolavirus; D019142:Hemorrhagic Fever, Ebola / Q000453:epidemiology / Q000635:transmission; D006801:Humans; D009980:Influenza A virus; D007251:Influenza, Human / Q000453:epidemiology / Q000635:transmission; D008954:Models, Biological; D029322:Norovirus
keywords: Markov chain Monte Carlo; compartmental model; shedding