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Author: Manyweathers, Jennifer; Maru, Yiheyis; Hayes, Lynne; Loechel, Barton; Kruger, Heleen; Mankad, Aditi; Xie, Gang; Woodgate, Rob; Hernandez-Jover, Marta
Title: The goat industry in Australia: Using Bayesian network analysis to understand vulnerability to a foot and mouth disease outbreak.
  • Cord-id: j1pefg7l
  • Document date: 2020_12_15
  • ID: j1pefg7l
    Snippet: Australia's goat industry is one of the largest goat product exporters in the world, managing both farmed and wild caught animals. To protect and maintain the competitive advantage afforded to the Australian goat industry by the absence of many diseases endemic elsewhere, it is important to identify the vulnerability of producers to livestock disease incursions. This study developed a framework of producer vulnerability built from the beliefs and practices of producers that may impact on their l
    Document: Australia's goat industry is one of the largest goat product exporters in the world, managing both farmed and wild caught animals. To protect and maintain the competitive advantage afforded to the Australian goat industry by the absence of many diseases endemic elsewhere, it is important to identify the vulnerability of producers to livestock disease incursions. This study developed a framework of producer vulnerability built from the beliefs and practices of producers that may impact on their likelihood of exposure and response capacity to an emergency animal disease (EAD), using foot and mouth disease as a model. A cross-sectional questionnaire gathered information on producer/enterprise demographics, animal health management and biosecurity practices, with 107 participating in the study. The biosecurity measures that were most commonly implemented by producers were always using animal movement documentation for purchased stock (74.7 %) and isolating new stock (73.1 %). However, moderate to low uptake of biosecurity protocols related to visitors to the property were reported. Response capacity variables such as checking animals daily (72.0 %) and record keeping (91.7 %) were reported by the majority of respondents, with 40.7 % reporting yearly veterinary inspection of their animals. Using the vulnerability framework, a Bayesian Network model was developed and populated by the survey data, and the relationships between variables were investigated. Six vulnerability profiles were developed, 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 sensitive exposure variables on producer vulnerability included implementation of visitor biosecurity and control of feral animals. Results from this study can inform risk based perspectives and decisions around biosecurity and surveillance resource allocation within the goat industry. The results also highlight opportunities for improving Australia's preparedness for a future EAD incursion by considering producer behaviour and beliefs by applying a vulnerability framework.

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