Assessment of Several Algorithms for Outbreak Detection using Bovine Meat Inspection Data for Syndromic Surveillance: A Pilot Study on Whole Carcass Condemnation Rate
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How to Cite

Dupuy, C., Morignat, E., DóreaF. C., Ducrot, C., Calavas, D., & Gay, E. (2015). Assessment of Several Algorithms for Outbreak Detection using Bovine Meat Inspection Data for Syndromic Surveillance: A Pilot Study on Whole Carcass Condemnation Rate. Online Journal of Public Health Informatics, 7(1). https://doi.org/10.5210/ojphi.v7i1.5791

Abstract

Slaughterhouses are a potential source of data which is under-used for cattle health monitoring. The objective of this work was to assess the performance of several algorithms for outbreak detection based on weekly proportions of whole carcass condemnation. Data from 177,098 cattle slaughtered in one French slaughterhouse from 2005 to 2009 were used. The Shewart p chart, one-sided confidence interval of a negative binomial regression model, and EWMA and CUSUM on residuals of a negative binomial model were investigated. The highest sensitivity was obtained using negative binomial regression and the highest specificity using CUSUM or EWMA.

https://doi.org/10.5210/ojphi.v7i1.5791
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