Integrating social behaviour, demography and disease dynamics in network models: applications to disease management in declining wildlife populations
dc.contributor.author | Silk, MJ | |
dc.contributor.author | Hodgson, D | |
dc.contributor.author | Rozins, C | |
dc.contributor.author | Croft, D | |
dc.contributor.author | Delahay, R | |
dc.contributor.author | Boots, M | |
dc.contributor.author | McDonald, R | |
dc.date.accessioned | 2019-03-14T09:15:00Z | |
dc.date.issued | 2019-07-29 | |
dc.description.abstract | The 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.sponsorship | Natural Environment Research Council (NERC) | en_GB |
dc.description.sponsorship | Animal and Plant Health Agency | en_GB |
dc.description.sponsorship | University of Exeter | en_GB |
dc.identifier.citation | Vol. 374 (1781), article 20180211 | en_GB |
dc.identifier.doi | 10.1098/rstb.2018.0211 | |
dc.identifier.grantnumber | NE/M004546/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/36458 | |
dc.language.iso | en | en_GB |
dc.publisher | Royal Society | en_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.subject | network | en_GB |
dc.subject | multilayer network | en_GB |
dc.subject | density-dependence | en_GB |
dc.subject | frequency-dependent | en_GB |
dc.subject | disease- induced extinction | en_GB |
dc.subject | conservation | en_GB |
dc.title | Integrating social behaviour, demography and disease dynamics in network models: applications to disease management in declining wildlife populations | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-03-14T09:15:00Z | |
dc.identifier.issn | 0962-8436 | |
dc.description | This is the final version. Available on open access from the Royal Society via the DOI in this record. | en_GB |
dc.identifier.journal | Philosophical Transactions B: Biological Sciences | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-03-13 | |
exeter.funder | ::Natural Environment Research Council (NERC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2019-03-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-03-14T09:06:29Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2019-08-05T13:10:01Z | |
refterms.panel | A | en_GB |
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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.