4.7 Article

Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak

期刊

FRONTIERS IN VETERINARY SCIENCE
卷 8, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fvets.2021.668679

关键词

Bayesian network model; foot and mouth disease; biosecurity; vulnerability; Australian sheep producers; surveillance; partnership

资金

  1. Meat and Livestock Australia from the Australian Government Department of Agriculture, Water and the Environment
  2. Animal Health Australia (AHA)

向作者/读者索取更多资源

In order to maintain and strengthen Australia's competitive international advantage in sheep meat and wool markets, robust and effective biosecurity systems are needed. An observational study was conducted to develop a Vulnerability framework to understand individual producer risk of exposure to animal diseases and their capacity to respond. The study found that while sheep producers have high levels of implementation of certain biosecurity practices, adoption of other practices such as feral animal control and visitor biosecurity protocols was limited.
To maintain and strengthen Australia's competitive international advantage in sheep meat and wool markets, the biosecurity systems that support these industries need to be robust and effective. These systems, strengthened by jurisdictional and livestock industry investments, can also be enhanced by a deeper understanding of individual producer risk of exposure to animal diseases and capacity to respond to these risks. This observational study developed a Vulnerability framework, built from current data from Australian sheep producers around behaviors and beliefs that may impact on their likelihood of Exposure and Response Capacity (willingness and ability to respond) to an emergency animal disease (EAD). Using foot and mouth disease (FMD) as a model, a cross-sectional survey gathered information on sheep producers' demographics, and their practices and beliefs around animal health management and biosecurity. Using the Vulnerability framework, a Bayesian Network (BN) model was developed as a first attempt to develop a decision making tool to inform risk based surveillance resource allocation. Populated by the data from 448 completed questionnaires, the BN model was analyzed to investigate relationships between variables and develop producer Vulnerability profiles. Respondents reported high levels of implementation of biosecurity practices that impact the likelihood of exposure to an EAD, such as the use of appropriate animal movement documentation (75.4%) and isolation of incoming stock (64.9%). However, adoption of other practices relating to feral animal control and biosecurity protocols for visitors were limited. Respondents reported a high uptake of Response Capacity practices, including identifying themselves as responsible for observing (94.6%), reporting unusual signs of disease in their animals (91.0%) and daily/weekly inspection of animals (90.0%). The BN analysis identified six Vulnerability typologies, with three levels of Exposure (high, moderate, low) and two levels of Response Capacity (high, low), as described by producer demographics and practices. The most influential Exposure variables on producer Vulnerability included adoption levels of visitor biosecurity and visitor access protocols. Findings from this study can guide decisions around resource allocation to improve Australia's readiness for EAD incursion and strengthen the country's biosecurity system.

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