Rapidly assessing the risks of infectious diseases to wildlife species

Predicting the likelihood of rare events is increasingly demanded by risk managers. A key challenge is dealing with different types of uncertainty, including epistemic uncertainties (lack of knowledge), stochasticity (inherent randomness) and natural variation. One potentially catastrophic event whi...

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Bibliographic Details
Published in:Royal Society open science Vol. 6; no. 1; p. 181043
Main Authors: Beauvais, Wendy, Zuther, Steffen, Villeneuve, Chantal, Kock, Richard, Guitian, Javier
Format: Journal Article
Language:English
Published: England The Royal Society 01-01-2019
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Summary:Predicting the likelihood of rare events is increasingly demanded by risk managers. A key challenge is dealing with different types of uncertainty, including epistemic uncertainties (lack of knowledge), stochasticity (inherent randomness) and natural variation. One potentially catastrophic event which is impacted by high levels of all three of these uncertainty types is the transmission of livestock pathogens to wildlife, particularly for endangered species. There is often a lack of basic information, e.g. about a given pathogen's presence in local livestock populations or the susceptibility of a given wildlife species to infection by the pathogen. We adapted the OIE (World Organisation for Animal Health) risk assessment framework to rapidly assess and prioritize the risks of livestock pathogens for wildlife, taking account of epistemic uncertainties, stochasticity, seasonal movement of animals and interaction between different species at different spatial and temporal scales. We demonstrate the approach using the endangered saiga antelope ( ) as a case study. We conclude that, in general, transmission events are likely to be rare and limited to small geographical areas; however, their impact could be high. spp. and foot-and-mouth disease virus are among those most likely to be transmitted from livestock to the Betpak-Dala saiga population.
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Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.4334348.
ISSN:2054-5703
2054-5703
DOI:10.1098/rsos.181043