Cargando…
Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak
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 enhance...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226010/ https://www.ncbi.nlm.nih.gov/pubmed/34179162 http://dx.doi.org/10.3389/fvets.2021.668679 |
_version_ | 1783712192576618496 |
---|---|
author | Manyweathers, Jennifer Maru, Yiheyis Hayes, Lynne Loechel, Barton Kruger, Heleen Mankad, Aditi Xie, Gang Woodgate, Rob Hernandez-Jover, Marta |
author_facet | Manyweathers, Jennifer Maru, Yiheyis Hayes, Lynne Loechel, Barton Kruger, Heleen Mankad, Aditi Xie, Gang Woodgate, Rob Hernandez-Jover, Marta |
author_sort | Manyweathers, Jennifer |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8226010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82260102021-06-26 Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak Manyweathers, Jennifer Maru, Yiheyis Hayes, Lynne Loechel, Barton Kruger, Heleen Mankad, Aditi Xie, Gang Woodgate, Rob Hernandez-Jover, Marta Front Vet Sci Veterinary Science 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. Frontiers Media S.A. 2021-06-11 /pmc/articles/PMC8226010/ /pubmed/34179162 http://dx.doi.org/10.3389/fvets.2021.668679 Text en Copyright © 2021 Manyweathers, Maru, Hayes, Loechel, Kruger, Mankad, Xie, Woodgate and Hernandez-Jover. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Veterinary Science Manyweathers, Jennifer Maru, Yiheyis Hayes, Lynne Loechel, Barton Kruger, Heleen Mankad, Aditi Xie, Gang Woodgate, Rob Hernandez-Jover, Marta Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title | Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title_full | Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title_fullStr | Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title_full_unstemmed | Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title_short | Using a Bayesian Network Predictive Model to Understand Vulnerability of Australian Sheep Producers to a Foot and Mouth Disease Outbreak |
title_sort | using a bayesian network predictive model to understand vulnerability of australian sheep producers to a foot and mouth disease outbreak |
topic | Veterinary Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226010/ https://www.ncbi.nlm.nih.gov/pubmed/34179162 http://dx.doi.org/10.3389/fvets.2021.668679 |
work_keys_str_mv | AT manyweathersjennifer usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT maruyiheyis usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT hayeslynne usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT loechelbarton usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT krugerheleen usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT mankadaditi usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT xiegang usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT woodgaterob usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak AT hernandezjovermarta usingabayesiannetworkpredictivemodeltounderstandvulnerabilityofaustraliansheepproducerstoafootandmouthdiseaseoutbreak |