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dc.contributor.authorHouse, T.-
dc.contributor.authorRoss, J.-
dc.contributor.authorSirl, D.-
dc.identifier.citationProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2013; 469(2150):1-22-
dc.description.abstractEpidemic models have become a routinely used tool to inform policy on infectious disease. A particular interest at the moment is the use of computationally intensive inference to parametrize these models. In this context, numerical efficiency is critically important. We consider methods for evaluating the probability mass function of the total number of infections over the course of a stochastic epidemic, with a focus on homogeneous finite populations, but also considering heterogeneous and large populations. Relevant methods are reviewed critically, with existing and novel extensions also presented. We provide code in Matlab and a systematic comparison of numerical efficiency.-
dc.description.statementofresponsibilityThomas House, Joshua V. Ross and David Sirl-
dc.publisherRoyal Soc London-
dc.rights©2012 The Authors. Published by the Royal Society under the terms of theCreative Commons Attribution License, which permits unrestricted use, provided the original author andsource are credited.-
dc.subjectinfectious disease-
dc.subjectMarkov chain-
dc.titleHow big is an outbreak likely to be? Methods for epidemic final-size calculation-
dc.typeJournal article-
dc.identifier.orcidRoss, J. [0000-0002-9918-8167]-
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