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Bayesian inference for multi-strain epidemics with application to Escherichia coli O157 : H7 in feedlot cattle

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Touloupou, Panayiota, Finkenstädt, Bärbel, Besser, Thomas E., French, Nigel P. and Spencer, Simon E. F. (2020) Bayesian inference for multi-strain epidemics with application to Escherichia coli O157 : H7 in feedlot cattle. The Annals of Applied Statistics, 14 (4). pp. 1925-1944. doi:10.1214/20-AOAS1366

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Official URL: https://doi.org/10.1214/20-AOAS1366

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Abstract

For most pathogens, testing procedures can be used to distinguish between different strains with which individuals are infected. Due to the growing availability of such data, multistrain models have increased in popularity over the past few years. Quantifying the interactions between different strains of a pathogen is crucial in order to obtain a more complete understanding of the transmission process, but statistical methods for this type of problem are still in the early stages of development. Motivated by this demand, we construct a stochastic epidemic model that incorporates additional strain information and propose a statistical algorithm for efficient inference. The model improves upon existing methods in the sense that it allows for both imperfect diagnostic test sensitivities and strain misclassification. Extensive simulation studies were conducted in order to assess the performance of our method, while the utility of the developed methodology is demonstrated on data obtained from a longitudinal study of Escherichia coli O157:H7 strains in feedlot cattle.

Item Type: Journal Article
Divisions: Faculty of Science > Statistics
Journal or Publication Title: The Annals of Applied Statistics
Publisher: Institute of Mathematical Statistics
ISSN: 1932-6157
Official Date: 19 December 2020
Dates:
DateEvent
19 December 2020Published
28 June 2020Accepted
Volume: 14
Number: 4
Page Range: pp. 1925-1944
DOI: 10.1214/20-AOAS1366
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Copyright Holders: Copyright © 2020 Institute of Mathematical Statistics
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