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Factors associated with whole carcass condemnation rates in provincially-inspected abattoirs in Ontario 2001-2007: implications for food animal syndromic surveillance

Overview of attention for article published in BMC Veterinary Research, August 2010
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Title
Factors associated with whole carcass condemnation rates in provincially-inspected abattoirs in Ontario 2001-2007: implications for food animal syndromic surveillance
Published in
BMC Veterinary Research, August 2010
DOI 10.1186/1746-6148-6-42
Pubmed ID
Authors

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

Abstract

Ontario provincial abattoirs have the potential to be important sources of syndromic surveillance data for emerging diseases of concern to animal health, public health and food safety. The objectives of this study were to: (1) describe provincially inspected abattoirs processing cattle in Ontario in terms of the number of abattoirs, the number of weeks abattoirs process cattle, geographical distribution, types of whole carcass condemnations reported, and the distance animals are shipped for slaughter; and (2) identify various seasonal, secular, disease and non-disease factors that might bias the results of quantitative methods, such as cluster detection methods, used for food animal syndromic surveillance.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
United States 1 1%
Switzerland 1 1%
Unknown 65 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 20%
Student > Master 12 17%
Student > Ph. D. Student 8 12%
Student > Doctoral Student 5 7%
Other 4 6%
Other 11 16%
Unknown 15 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 32%
Veterinary Science and Veterinary Medicine 12 17%
Medicine and Dentistry 8 12%
Environmental Science 4 6%
Economics, Econometrics and Finance 2 3%
Other 5 7%
Unknown 16 23%