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dc.contributor.authorSilk, MJ
dc.contributor.authorHodgson, D
dc.contributor.authorRozins, C
dc.contributor.authorCroft, D
dc.contributor.authorDelahay, R
dc.contributor.authorBoots, M
dc.contributor.authorMcDonald, R
dc.date.accessioned2019-03-14T09:15:00Z
dc.date.issued2019-07-29
dc.description.abstractThe emergence and spread of infections can contribute to the decline and extinction of populations, particularly in conjunction with anthropogenic environmental change. The importance of heterogeneity in processes of transmission, resistance and tolerance is increasingly well understood in theory, but empirical studies that consider both the demographic and behavioural implications of infection are scarce. Non-random mixing of host individuals can impact the demographic thresholds that determine the amplification or attenuation of disease prevalence. Risk assessment and management of disease in threatened wildlife populations must therefore consider not just host density, but also the social structure of host populations. Here we integrate the most recent developments in epidemiological research from a demographic and social network perspective and synthesise the latest developments in social network modelling for wildlife disease, to explore their applications to disease management in populations in decline and at risk of extinction. We use simulated examples to support our key points and reveal how disease-management strategies can and should exploit both behavioural and demographic information to prevent or control the spread of disease. Our synthesis highlights the importance of considering the combined impacts of demographic and behavioural processes in epidemics to successful disease management in a conservation context.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipAnimal and Plant Health Agencyen_GB
dc.description.sponsorshipUniversity of Exeteren_GB
dc.identifier.citationVol. 374 (1781), article 20180211en_GB
dc.identifier.doi10.1098/rstb.2018.0211
dc.identifier.grantnumberNE/M004546/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/36458
dc.language.isoenen_GB
dc.publisherRoyal Societyen_GB
dc.rights© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
dc.subjectnetworken_GB
dc.subjectmultilayer networken_GB
dc.subjectdensity-dependenceen_GB
dc.subjectfrequency-dependenten_GB
dc.subjectdisease- induced extinctionen_GB
dc.subjectconservationen_GB
dc.titleIntegrating social behaviour, demography and disease dynamics in network models: applications to disease management in declining wildlife populationsen_GB
dc.typeArticleen_GB
dc.date.available2019-03-14T09:15:00Z
dc.identifier.issn0962-8436
dc.descriptionThis is the final version. Available on open access from the Royal Society via the DOI in this record.en_GB
dc.identifier.journalPhilosophical Transactions B: Biological Sciencesen_GB
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-03-13
exeter.funder::Natural Environment Research Council (NERC)en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-03-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-03-14T09:06:29Z
refterms.versionFCDAM
refterms.dateFOA2019-08-05T13:10:01Z
refterms.panelAen_GB


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© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Except where otherwise noted, this item's licence is described as © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.