Rapidly assessing the risks of infectious diseases to wildlife species

Beauvais, W; Zuther, S; Villeneuve, C; Kock, R A; Guitian, J

Abstract

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 (Saiga tatarica tatarica) 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. Brucella spp. and foot-and-mouth disease virus are among those most likely to be transmitted from livestock to the Betpak-Dala saiga population.

Citation

Beauvais, W., Zuther, S., Villeneuve, C., Kock, R. A., & Guitian, J. (2019). Rapidly assessing the risks of infectious diseases to wildlife species. Royal Society Open Science, 6(1), https://doi.org/10.1098/rsos.181043

• Journal Article Type: Article
• Acceptance Date: Nov 30, 2018
• Publication Date: Jan 16, 2019
• Deposit Date: Feb 15, 2019
• Publicly Available Date: Feb 15, 2019
• Journal: Royal Society Open Science
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Issue: 1
• DOI: https://doi.org/10.1098/rsos.181043
• Public URL: https://rvc-repository.worktribe.com/output/1383946
• Related Public URLs: https://doi.org/10.6084/m9.figshare.c.4334348.v1