Bayesian Inference for Contact Networks Given Epidemic Data

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Show simple item record Groendyke, Chris en Welch, John en Hunter, David R en 2012-03-14T23:49:09Z en 2010 en
dc.identifier.citation Scandinavian Journal of Statistics 38(3):600-616 01 Sep 2011 en
dc.identifier.issn 1467-9469 en
dc.identifier.uri en
dc.description.abstract In this article, we estimate the parameters of a simple random network and a stochastic epidemic on that network using data consisting of recovery times of infected hosts. The SEIR epidemic model we fit has exponentially distributed transmission times with Gamma distributed exposed and infectious periods on a network where every edge exists with the same probability, independent of other edges. We employ a Bayesian framework and Markov chain Monte Carlo (MCMC) integration to make estimates of the joint posterior distribution of the model parameters. We discuss the accuracy of the parameter estimates under various prior assumptions and show that it is possible in many scientifically interesting cases to accurately recover the parameters. We demonstrate our approach by studying a measles outbreak in Hagelloch, Germany, in 1861 consisting of 188 affected individuals.We provide an R package to carry out these analyses, which is available publicly on the Comprehensive R Archive Network. en
dc.publisher Blackwell Publishing Ltd en
dc.relation.ispartofseries Scandinavian Journal of Statistics en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from: en
dc.rights.uri en
dc.title Bayesian Inference for Contact Networks Given Epidemic Data en
dc.type Journal Article en
dc.identifier.doi 10.1111/j.1467-9469.2010.00721.x en
pubs.begin-page 600 en
pubs.volume 38 en
dc.rights.holder Copyright: Blackwell Publishing Ltd en
pubs.end-page 616 en
dc.rights.accessrights en
pubs.subtype Article en
pubs.elements-id 250444 en Science en School of Computer Science en
pubs.record-created-at-source-date 2011-12-15 en

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