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Quantifying the value of perfect information in emergency vaccination campaigns
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Bradbury, Naomi V., Probert, William J. M. , Shea, Katriona, Runge, Michael C., Fonnesbeck, Christopher J., Keeling, Matthew James, Ferrari, Matthew J. and Tildesley, Michael J. (2017) Quantifying the value of perfect information in emergency vaccination campaigns. PLoS Computational Biology, 13 (2). e1005318. doi:10.1371/journal.pcbi.1005318 ISSN 1553-7358.
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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1005318
Abstract
Foot-and-mouth disease outbreaks in non-endemic countries can lead to large economic costs and livestock losses but the use of vaccination has been contentious, partly due to uncertainty about emergency FMD vaccination. Value of information methods can be applied to disease outbreak problems such as FMD in order to investigate the performance improvement from resolving uncertainties. Here we calculate the expected value of resolving uncertainty about vaccine efficacy, time delay to immunity after vaccination and daily vaccination capacity for a hypothetical FMD outbreak in the UK. If it were possible to resolve all uncertainty prior to the introduction of control, we could expect savings of £55 million in outbreak cost, 221,900 livestock culled and 4.3 days of outbreak duration. All vaccination strategies were found to be preferable to a culling only strategy. However, the optimal vaccination radius was found to be highly dependent upon vaccination capacity for all management objectives. We calculate that by resolving the uncertainty surrounding vaccination capacity we would expect to return over 85% of the above savings, regardless of management objective. It may be possible to resolve uncertainty about daily vaccination capacity before an outbreak, and this would enable decision makers to select the optimal control action via careful contingency planning.
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- ) | ||||||||
Library of Congress Subject Headings (LCSH): | Foot-and-mouth disease -- Vaccination -- Great Britain | ||||||||
Journal or Publication Title: | PLoS Computational Biology | ||||||||
Publisher: | Public Library of Science | ||||||||
ISSN: | 1553-7358 | ||||||||
Official Date: | 16 January 2017 | ||||||||
Dates: |
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Volume: | 13 | ||||||||
Number: | 2 | ||||||||
Article Number: | e1005318 | ||||||||
DOI: | 10.1371/journal.pcbi.1005318 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 13 January 2017 | ||||||||
Date of first compliant Open Access: | 13 January 2017 | ||||||||
Funder: | Great Britain. Department for Environment, Food and Rural Affairs (DEFRA) |
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