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Modelling livestock infectious disease control policy under differing social perspectives on vaccination behaviour
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Hill, Edward M., Prosser, Naomi S., Ferguson, Eamonn, Kaler, Jasmeet, Green, Martin J., Keeling, Matt J. and Tildesley, Michael J. (2022) Modelling livestock infectious disease control policy under differing social perspectives on vaccination behaviour. PLOS Computational Biology, 18 (7). e1010235. doi:10.1371/journal.pcbi.1010235 ISSN 1553-7358.
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Official URL: https://doi.org/10.1371/journal.pcbi.1010235
Abstract
The spread of infection amongst livestock depends not only on the traits of the pathogen and the livestock themselves, but also on the veterinary health behaviours of farmers and how this impacts their implementation of disease control measures. Controls that are costly may make it beneficial for individuals to rely on the protection offered by others, though that may be sub-optimal for the population. Failing to account for socio-behavioural properties may produce a substantial layer of bias in infectious disease models. We investigated the role of heterogeneity in vaccine response across a population of farmers on epidemic outbreaks amongst livestock, caused by pathogens with differential speed of spread over spatial landscapes of farms for two counties in England (Cumbria and Devon). Under different compositions of three vaccine behaviour groups (precautionary, reactionary, non-vaccination), we evaluated from population- and individual-level perspectives the optimum threshold distance to premises with notified infection that would trigger responsive vaccination by the reactionary vaccination group. We demonstrate a divergence between population and individual perspectives in the optimal scale of reactive voluntary vaccination response. In general, minimising the population-level perspective cost requires a broader reactive uptake of the intervention, whilst optimising the outcome for the average individual increased the likelihood of larger scale disease outbreaks. When the relative cost of vaccination was low and the majority of premises had undergone precautionary vaccination, then adopting a perspective that optimised the outcome for an individual gave a broader spatial extent of reactive response compared to a perspective wanting to optimise outcomes for everyone in the population. Under our assumed epidemiological context, the findings identify livestock disease intervention receptiveness and cost combinations where one would expect strong disagreement between the intervention stringency that is best from the perspective of a stakeholder responsible for supporting the livestock industry compared to a sole livestock owner. Were such discord anticipated and achieving a consensus view across perspectives desired, the findings may also inform those managing veterinary health policy the requisite reduction in intervention cost and/or the required extent of nurturing beneficial community attitudes towards interventions.
| Item Type: | Journal Article | |||||||||
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| Subjects: | S Agriculture > SF Animal culture | |||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | |||||||||
| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | Livestock -- Infections -- Prevention, Livestock -- Diseases -- Prevention, Communicable diseases in animals, Livestock -- Diseases -- Vaccination, Farm management -- Decision making | |||||||||
| Journal or Publication Title: | PLOS Computational Biology | |||||||||
| Publisher: | Public Library of Science | |||||||||
| ISSN: | 1553-7358 | |||||||||
| Official Date: | 14 July 2022 | |||||||||
| Dates: |
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| Volume: | 18 | |||||||||
| Number: | 7 | |||||||||
| Article Number: | e1010235 | |||||||||
| DOI: | 10.1371/journal.pcbi.1010235 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Reuse Statement (publisher, data, author rights): | ||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 15 July 2022 | |||||||||
| Date of first compliant Open Access: | 15 July 2022 | |||||||||
| RIOXX Funder/Project Grant: |
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