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Suitability of sentinel abattoirs for syndromic surveillance using provincially inspected bovine abattoir condemnation data

Overview of attention for article published in BMC Veterinary Research, February 2015
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Title
Suitability of sentinel abattoirs for syndromic surveillance using provincially inspected bovine abattoir condemnation data
Published in
BMC Veterinary Research, February 2015
DOI 10.1186/s12917-015-0349-1
Pubmed ID
Authors

Gillian D Alton, David L Pearl, Ken G Bateman, W Bruce McNab, Olaf Berke

Abstract

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. 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. 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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 3%
Switzerland 1 3%
Unknown 37 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 23%
Researcher 8 21%
Student > Master 7 18%
Professor > Associate Professor 3 8%
Other 3 8%
Other 2 5%
Unknown 7 18%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 12 31%
Agricultural and Biological Sciences 9 23%
Medicine and Dentistry 3 8%
Computer Science 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 2 5%
Unknown 10 26%