title: Suitability of sentinel abattoirs for syndromic surveillance using provincially inspected bovine abattoir condemnation data.
abstract: BACKGROUND
  Sentinel surveillance has previously been used to monitor and identify disease outbreaks in both human and animal contexts. Three approaches for the selection of sentinel sites are proposed and evaluated regarding their ability to capture overall respiratory disease trends using provincial abattoir condemnation data from all abattoirs open throughout the study for use in a sentinel syndromic surveillance system.
  
  
  RESULTS
  All three sentinel selection criteria approaches resulted in the identification of sentinel abattoirs that captured overall temporal trends in condemnation rates similar to those reported by the full set of abattoirs. However, all selection approaches tended to overestimate the condemnation rates of the full dataset by 1.4 to as high as 3.8 times for cows, heifers and steers. Given the results, the selection approach using abattoirs open all weeks had the closest approximation of temporal trends when compared to the full set of abattoirs.
  
  
  CONCLUSIONS
  Sentinel abattoirs show promise for integration into a food animal syndromic surveillance system using Ontario provincial abattoir condemnation data. While all selection approaches tended to overestimate the condemnation rates of the full dataset to some degree, the abattoirs open all weeks selection approach appeared to best capture the overall seasonal and temporal trends of the full dataset and would be the most suitable approach for sentinel abattoir selection.
authors.affiliation: Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, N1G 2 W1, Canada. altong@uoguelph.ca.
authors.forename: Gillian D
authors.initials: GD
authors.lastname: Alton
authors.affiliation: Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, N1G 2 W1, Canada. dpearl@uoguelph.ca.
authors.forename: David L
authors.initials: DL
authors.lastname: Pearl
authors.affiliation: Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, N1G 2 W1, Canada. kbateman@uoguelph.ca.
authors.forename: Ken G
authors.initials: KG
authors.lastname: Bateman
authors.affiliation: Ontario Ministry of Agriculture & Food, Guelph, ON, N1G 4Y2, Canada. bruce.mcnab@rogers.com.
authors.forename: W Bruce
authors.initials: WB
authors.lastname: McNab
authors.affiliation: Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, N1G 2 W1, Canada. oberke@uoguelph.ca.|Department of Mathematics and Statistics, University of Guelph, Guelph, ON, N1G 2 W1, Canada. oberke@uoguelph.ca.
authors.forename: Olaf
authors.initials: O
authors.lastname: Berke
mesh_terms: D000003:Abattoirs; D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000175:diagnosis / Q000453:epidemiology*; D004196:Disease Outbreaks / Q000517:prevention & control / Q000662:veterinary*; D005260:Female; D008297:Male; D009864:Ontario / Q000453:epidemiology; D011014:Pneumonia / Q000175:diagnosis / Q000453:epidemiology / Q000662:veterinary; D018571:Sentinel Surveillance / Q000662:veterinary*