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dc.contributor.authorBenson, Leeen_UK
dc.contributor.authorDavidson, Ross Sen_UK
dc.contributor.authorGreen, Darren Men_UK
dc.contributor.authorHoyle, Andrewen_UK
dc.contributor.authorHutchings, Mike Ren_UK
dc.contributor.authorMarion, Glennen_UK
dc.description.abstractVariants of the susceptible-infected-removed (SIR) model of Kermack & McKendrick (1927) enjoy wide application in epidemiology, offering simple yet powerful inferential and predictive tools in the study of diverse infectious diseases across human, animal and plant populations. Direct transmission models (DTM) are a subset of these that treat the processes of disease transmission as comprising a series of discrete instantaneous events. Infections transmitted indirectly by persistent environmental pathogens, however, are examples where a DTM description might fail and are perhaps better described by models that comprise explicit environmental transmission routes, so-called environmental transmission models (ETM). In this paper we discuss the stochastic susceptible-exposed-infected-removed (SEIR) DTM and susceptible-exposed-infected-removed-pathogen (SEIR-P) ETM and we show that the former is the timescale separation limit of the latter, with ETM host-disease dynamics increasingly resembling those of a DTM when the pathogen’s characteristic timescale is shortened, relative to that of the host population. Using graphical posterior predictive checks (GPPC), we investigate the validity of the SEIR model when fitted to simulated SEIR-P host infection and removal times. Such analyses demonstrate how, in many cases, the SEIR model is robust to departure from direct transmission. Finally, we present a case study of white spot disease (WSD) in penaeid shrimp with rates of environmental transmission and pathogen decay (SEIR-P model parameters) estimated using published results of experiments. Using SEIR and SEIR-P simulations of a hypothetical WSD outbreak management scenario, we demonstrate how relative shortening of the pathogen timescale comes about in practice. With atttempts to remove diseased shrimp from the population every 24h, we see SEIR and SEIR-P model outputs closely conincide. However, when removals are 6-hourly, the two models’ mean outputs diverge, with distinct predictions of outbreak size and duration.en_UK
dc.publisherPublic Library of Science (PLoS)en_UK
dc.relationBenson L, Davidson RS, Green DM, Hoyle A, Hutchings MR & Marion G (2021) When and why direct transmission models can be used for environmentally persistent pathogens. PLOS Computational Biology, 17 (12), Art. No.: e1009652.
dc.rights© 2021 Benson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_UK
dc.subjectComputational Theory and Mathematicsen_UK
dc.subjectCellular and Molecular Neuroscienceen_UK
dc.subjectMolecular Biologyen_UK
dc.subjectModelling and Simulationen_UK
dc.subjectEcology, Evolution, Behavior and Systematicsen_UK
dc.titleWhen and why direct transmission models can be used for environmentally persistent pathogensen_UK
dc.typeJournal Articleen_UK
dc.citation.jtitlePLoS Computational Biologyen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderScotland's Rural Collegeen_UK
dc.contributor.funderRural and Environment Science and Analytical Services Divisionen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationScotland's Rural College (SRUC)en_UK
dc.contributor.affiliationInstitute of Aquacultureen_UK
dc.contributor.affiliationScotland's Rural College (SRUC)en_UK
dc.contributor.affiliationBiomathematics & Statistics Scotlanden_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorBenson, Lee|en_UK
local.rioxx.authorDavidson, Ross S|0000-0003-1468-5867en_UK
local.rioxx.authorGreen, Darren M|0000-0001-9026-5675en_UK
local.rioxx.authorHoyle, Andrew|0000-0002-9117-7041en_UK
local.rioxx.authorHutchings, Mike R|en_UK
local.rioxx.authorMarion, Glenn|0000-0002-0454-9338en_UK
local.rioxx.projectProject ID unknown|Scotland's Rural College|en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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