Untangling the complex inter-relationships between horse managers' perceptions of effectiveness of biosecurity practices using Bayesian graphical modelling.
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Schemann, KathrinLewis, F. I.
Firestone, S. M.
Ward, M. P.
Toribio, Jenny-Ann L. M. L.
Taylor, M. R.
Dhand, Navneet K.
Abstract
On-farm biosecurity practices have been promoted in many animal industries to protect animal populations from infections. Current approaches based on regression modelling techniques for assessing biosecurity perceptions and practices are limited for analysis of the interrelationships ...
See moreOn-farm biosecurity practices have been promoted in many animal industries to protect animal populations from infections. Current approaches based on regression modelling techniques for assessing biosecurity perceptions and practices are limited for analysis of the interrelationships between multivariate data. A suitable approach, which does not require background knowledge of relationships, is provided by Bayesian network modelling. Here we apply such an approach to explore the complex interrelationships between the variables representing horse managers’ perceptions of effectiveness of on-farm biosecurity practices. The dataset was derived from interviews conducted with 200 horse managers in Australia after the 2007 equine influenza outbreak. Using established computationally intensive techniques, an optimal graphical statistical model was identified whose structure was objectively determined, directly from the observed data. This methodology is directly analogous to multivariate regression (i.e. multiple response variables). First, an optimal model structure was identified using an exact (exhaustive) search algorithm, followed by pruning the selected model for over-fitting by the parametric bootstrapping approach. Perceptions about effectiveness of movement restrictions and access control were linked but were generally segregated from the perceptions about effectiveness of personal and equipment hygiene. Horse managers believing in the effectiveness of complying with movement restrictions in stopping equine influenza spread onto their premises were also more likely to believe in the effectiveness of reducing their own contact with other horses and curtailing professional visits. Similarly, the variables representing the effectiveness of disinfecting vehicles, using a disinfectant footbath, changing into clean clothes on arrival at the premises and washing hands before contact with managed horses were clustered together. In contrast, horse managers believing in the effectiveness of disinfecting vehicles (hygiene measure) were less likely to believe in the effectiveness of controlling who has access to managed horses (access control). The findings of this analysis provide new insights into the relationships between perceptions of effectiveness of different biosecurity measures. Different extension education strategies might be required for horse managers believing more strongly in the effectiveness of access control or hygiene measures. Keywords: Biosecurity, Equine influenza, Effectiveness, Graphical network modelling, Perceptions.
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See moreOn-farm biosecurity practices have been promoted in many animal industries to protect animal populations from infections. Current approaches based on regression modelling techniques for assessing biosecurity perceptions and practices are limited for analysis of the interrelationships between multivariate data. A suitable approach, which does not require background knowledge of relationships, is provided by Bayesian network modelling. Here we apply such an approach to explore the complex interrelationships between the variables representing horse managers’ perceptions of effectiveness of on-farm biosecurity practices. The dataset was derived from interviews conducted with 200 horse managers in Australia after the 2007 equine influenza outbreak. Using established computationally intensive techniques, an optimal graphical statistical model was identified whose structure was objectively determined, directly from the observed data. This methodology is directly analogous to multivariate regression (i.e. multiple response variables). First, an optimal model structure was identified using an exact (exhaustive) search algorithm, followed by pruning the selected model for over-fitting by the parametric bootstrapping approach. Perceptions about effectiveness of movement restrictions and access control were linked but were generally segregated from the perceptions about effectiveness of personal and equipment hygiene. Horse managers believing in the effectiveness of complying with movement restrictions in stopping equine influenza spread onto their premises were also more likely to believe in the effectiveness of reducing their own contact with other horses and curtailing professional visits. Similarly, the variables representing the effectiveness of disinfecting vehicles, using a disinfectant footbath, changing into clean clothes on arrival at the premises and washing hands before contact with managed horses were clustered together. In contrast, horse managers believing in the effectiveness of disinfecting vehicles (hygiene measure) were less likely to believe in the effectiveness of controlling who has access to managed horses (access control). The findings of this analysis provide new insights into the relationships between perceptions of effectiveness of different biosecurity measures. Different extension education strategies might be required for horse managers believing more strongly in the effectiveness of access control or hygiene measures. Keywords: Biosecurity, Equine influenza, Effectiveness, Graphical network modelling, Perceptions.
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Date
2013-01-01Publisher
ElsevierDepartment, Discipline or Centre
Veterinary ScienceCitation
Schemann, K., Lewis, F. I., Firestone, S. M., Ward, M. P., Toribio, J. A., Taylor, M. R., et al. (2013). Untangling the complex inter-relationships between horse managers' perceptions of effectiveness of biosecurity practices using Bayesian graphical modelling. Prev Vet Med. 110(1), 37-44Share