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Detecting new and emerging diseases on livestock farms using an early detection system.

Kosmider, Rowena Dawn and Kelly, Louise Anne and Simons, R.L. and Brouwer, A. and David, G. (2011) Detecting new and emerging diseases on livestock farms using an early detection system. Epidemiology and Infection, 139 (10). pp. 1476-1485.

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Abstract

SUMMARYThe monitoring and surveillance of animal diseases is becoming increasingly important to policy-makers in Great Britain particularly given recent incursions of avian influenza and the emergence of bovine spongiform encephalopathy. To meet this surveillance objective, data from British livestock is collected and analysed retrospectively on an ongoing basis. However, these data can also be analysed prospectively within an early detection system which raises alerts to significant increases in disease reporting soon after they occur in the field. The feasibility of such an approach has been examined previously for Salmonella. This paper applied the approach to a further subset of surveillance data to alert those monitoring disease to increases in potentially new and emerging diseases. Thus far, the analysis, conducted on a quarterly basis, has proved a useful additional tool in enhanced surveillance by raising alerts to significant increases in several syndromes in both sheep and cattle.

Item type: Article
ID code: 30363
Notes: DOI does not work.
Keywords: analysis of data, surveillance systems, emerging infections, Probabilities. Mathematical statistics, Public health. Hygiene. Preventive Medicine, Infectious Diseases, Epidemiology
Subjects: Science > Mathematics > Probabilities. Mathematical statistics
Medicine > Public aspects of medicine > Public health. Hygiene. Preventive Medicine
Department: Faculty of Science > Mathematics and Statistics > Statistics and Modelling Science
Faculty of Science > Mathematics and Statistics
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Depositing user: Pure Administrator
Date Deposited: 10 May 2011 13:34
Last modified: 27 Mar 2014 09:18
URI: http://strathprints.strath.ac.uk/id/eprint/30363

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