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dc.contributor.authorBoden LAen
dc.contributor.authorAuty HKen
dc.contributor.authorReeves Aen
dc.contributor.authorRydevik Gen
dc.contributor.authorBessell Pen
dc.contributor.authorMcKendrick IJen
dc.date.accessioned2017-11-15T12:33:04Z
dc.date.available2017-11-15T12:33:04Z
dc.date.issued2017
dc.identifier.citation4:201
dc.identifier.issn2297-1769
dc.identifier.urihttps://doi.org/10.3389/fvets.2017.00201
dc.identifier.urihttp://hdl.handle.net/11262/11337
dc.description.abstractAnimal health surveillance is necessary to protect human and animal health, rural economies and the environment from the consequences of large-scale disease outbreaks. In Scotland, since the Kinnaird review in 2011, efforts have been made to engage with stakeholders to ensure that the strategic goals of surveillance are better aligned with the needs of the end-users and other beneficiaries. The aims of this study were to engage with Scottish surveillance stakeholders and multidisciplinary experts to inform the future long-term strategy for animal health surveillance in Scotland. In this paper, we describe the use of scenario planning as an effective tool for the creation and exploration of five plausible long-term futures; we describe prioritisation of critical drivers of change (i.e. international trade policy, data sharing philosophies and public versus private resourcing of surveillance capacity) that will unpredictably influence the future implementation of animal health surveillance activities and we present ten participant-developed strategies to support three long-term visions to improve future resilience of animal health surveillance and contingency planning for animal and zoonotic disease outbreaks in Scotland. In the absence of any certainty about the nature of post-Brexit trade agreements for agriculture, participants considered the best investments for long-term resilience to include: data collection strategies to improve animal health benchmarking, user-benefit strategies to improve digital literacy in farming communities and investment strategies to increase veterinary and scientific research capacity in rural areas. This is the first scenario planning study to explore stakeholder beliefs and perceptions about important environmental, technological, societal, political and legal drivers (in addition to epidemiological “risk factors”) and effective strategies to manage future uncertainties for both the Scottish livestock industry and animal health surveillance after Brexit. This insight from stakeholders is important in order to improve uptake and implementation of animal heath surveillance activities and the future resilience of the livestock industry. The conclusions drawn from this study are applicable not only to Scotland, but to other countries and international organizations involved in global animal health surveillance activities.en
dc.description.sponsorshipScottish Government RESAS Centres of Excellence - EPICen
dc.language.isoenen
dc.relation.isformatof14712en
dc.relation.ispartofFrontiers in Veterinary Scienceen
dc.rightsCopyright © 2017 Boden, Auty, Reeves, Rydevik, Bessell and McKendrick. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectFuturesen
dc.subjectScenario planningen
dc.subjectUncertaintyen
dc.subjectResilienceen
dc.subjectPublic healthen
dc.subjectSurveillanceen
dc.subjectBrexiten
dc.subjectNotifiable diseasesen
dc.titleAnimal health surveillance in Scotland in 2030: using scenario planning to develop strategies in the context of 'Brexit'en
dc.typeArticleen
dc.description.versionVersion of Record
rioxxterms.publicationdate2017-11-27
rioxxterms.typeJournal Article/Reviewen
dcterms.dateAccepted2017-11-08
refterms.accessExceptionNAen
refterms.dateDeposit2017-11-15
refterms.depositExceptionNAen
refterms.panelUnspecifieden
refterms.technicalExceptionNAen
refterms.versionAMen


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Copyright © 2017 Boden, Auty, Reeves, Rydevik, Bessell and McKendrick. 

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Except where otherwise noted, this item's license is described as Copyright © 2017 Boden, Auty, Reeves, Rydevik, Bessell and McKendrick. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.