title: Detecting new and emerging diseases on livestock farms using an early detection system.
abstract: The 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.
authors.affiliation: Centre for Epidemiology and Risk Analysis, Veterinary Laboratories Agency, Addlestone, Surrey, UK. r.kosmider@vla.defra.gsi.gov.uk
authors.forename: R D
authors.initials: RD
authors.lastname: Kosmider
authors.forename: L
authors.initials: L
authors.lastname: Kelly
authors.forename: R L
authors.initials: RL
authors.lastname: Simons
authors.forename: A
authors.initials: A
authors.lastname: Brouwer
authors.forename: G
authors.initials: G
authors.lastname: David
mesh_terms: D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000175:diagnosis / Q000453:epidemiology; D021821:Communicable Diseases, Emerging / Q000175:diagnosis / Q000453:epidemiology / Q000662:veterinary*; D018563:Disease Notification / Q000379:methods*; D058751:Livestock; D018571:Sentinel Surveillance / Q000662:veterinary*; D012756:Sheep; D012757:Sheep Diseases / Q000175:diagnosis / Q000453:epidemiology; D006113:United Kingdom / Q000453:epidemiology