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.

Highlights

  • Predicting the likelihood of catastrophic or rare events is increasingly in demand by risk managers

  • One example of a potentially catastrophic event which is impacted by high levels of epistemic uncertainty, stochasticity and natural variation is the transmission of livestock pathogens to wildlife, for endangered species

  • One-hundred-and-seventeen pathogens featured on the Organisation for Animal Health (OIE) list of livestock diseases, in addition to 45 on the OIE list of wildlife diseases

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Summary

Introduction

Predicting the likelihood of catastrophic or rare events is increasingly in demand by risk managers. Uncertainty, for example epistemic uncertainties (lack of knowledge), stochasticity (inherent randomness) 2 and natural variation, often driven by spatial and temporal determinants [2]. Natural variation is not always classified as a type of uncertainty, but it produces uncertainties because it can lead to difficulties in synthesizing information from disparate sources to produce guidelines that are comprehensible and useful for risk managers. There is a demand for systematic assessments of the likelihood of events that limit bias and make epistemic uncertainties, stochasticity and natural variation explicit [2]

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