title: An assessment of external biosecurity on Southern Ontario swine farms and its application to surveillance on a geographic level.
abstract: Risk-based surveillance is becoming increasingly important in the veterinary and public health fields. It serves as a means of increasing surveillance sensitivity and improving cost-effectiveness in an increasingly resource-limited environment. Our approach for developing a tool for the risk-based geographical surveillance of contagious diseases of swine incorporates information about animal density and external biosecurity practices within swine herds in southern Ontario. The objectives of this study were to group the sample of herds into discrete biosecurity groups, to develop a map of southern Ontario that can be used as a tool in the risk-based geographical surveillance of contagious swine diseases, and to identify significant predictors of biosecurity group membership. A subset of external biosecurity variables was selected for 2-step cluster analysis and latent class analysis (LCA). It was determined that 4 was the best number of groups to describe the data, using both analytical approaches. The authors named these groups: i) high biosecurity herds that were open with respect to replacement animals; ii) high biosecurity herds that were closed with respect to replacement animals; iii) moderate biosecurity herds; and iv) low biosecurity herds. The risk map was developed using information about the geographic distribution of herds in the biosecurity groups, as well as the density of swine sites and of grower-finisher pigs in the study region. Finally, multinomial logistic regression identified heat production units (HPUs), number of incoming pig shipments per month, and herd type as significant predictors of biosecurity group membership. It was concluded that the ability to identify areas of high and low risk for disease may improve the success of surveillance and eradication projects.
authors.affiliation: Department of Population Medicine, Ontario Veterinary College (Bottoms, Poljak, Friendship, Dewey) and Department of Mathematics and Statistics (Deardon), University of Guelph, Guelph, Ontario; Ontario Ministry of Agriculture, Food and Rural Affairs, Guelph, Ontario (Alsop).
authors.forename: Kate
authors.initials: K
authors.lastname: Bottoms
authors.forename: Zvonimir
authors.initials: Z
authors.lastname: Poljak
authors.forename: Robert
authors.initials: R
authors.lastname: Friendship
authors.forename: Rob
authors.initials: R
authors.lastname: Deardon
authors.forename: Janet
authors.initials: J
authors.lastname: Alsop
authors.forename: Cate
authors.initials: C
authors.lastname: Dewey
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D062665:Epidemiological Monitoring / Q000662:veterinary*; D016015:Logistic Models; D009864:Ontario / Q000453:epidemiology; D019318:Porcine Reproductive and Respiratory Syndrome / Q000453:epidemiology / Q000517:prevention & control*; D019316:Porcine respiratory and reproductive syndrome virus / Q000254:growth & development*; D018570:Risk Assessment / Q000379:methods*; D017751:Safety Management / Q000379:methods*; D011795:Surveys and Questionnaires; D013552:Swine