Key result
Novel network model identifies vulnerabilities and critical control points to reduce classical swine fever exposure.
A novel network model provides a systematic analysis of disease incursion likelihood, identifying critical control points for exotic animal diseases like classical swine fever.
Exotic animal diseases (EADs) are characterized by their capacity to spread global distances, causing impacts on animal health and welfare with significant economic consequences. We offer a critique of current import risk analysis approaches employed in the EAD field, focusing on their capacity to assess complex systems at a policy level. To address the shortcomings identified, we propose a novel method providing a systematic analysis of the likelihood of a disease incursion, developed by reference to the multibarrier system employed for the United Kingdom. We apply the network model to a policy-level risk assessment of classical swine fever (CSF), a notifiable animal disease caused by the CSF virus. In doing so, we document and discuss a sequence of analyses that describe system vulnerabilities and reveal the critical control points (CCPs) for intervention, reducing the likelihood of U.K. pig herds being exposed to the CSF virus.
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Delgado et al. (2012) studied Classical swine fever. Network model for policy-level risk assessment vs. Current import risk analysis approaches was evaluated on System vulnerabilities and critical control points (CCPs). A novel network model for policy-level risk assessment identified system vulnerabilities and critical control points to reduce the likelihood of UK pig herds being exposed to the classical swine fever virus.
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