Literature DB >> 18552327

Use of laboratory data to reduce the time taken to detect new diseases: VIDA to FarmFile.

J C Gibbens1, S Robertson, J Willmington, A Milnes, J B M Ryan, J W Wilesmith, A J C Cook, G P David.   

Abstract

The analysis of laboratory data can provide information about the health of livestock populations; in Great Britain the Veterinary Investigation Diagnosis Analysis (VIDA) system has provided such data since 1975. However VIDA covers only known diagnoses, with limited epidemiological characterisation. The unexpected outbreak of bse showed that it was necessary to improve surveillance to detect new diseases, and a necessary update of the VIDA database for the millennium date change provided the opportunity. The information required to enhance the value of laboratory data was identified, a new form and database, 'FarmFile', were designed to record it, and they began to be used in 1999. The detection of new diseases depends on making comparisons with the expected or 'usual' levels of unexplained disease. The data are analysed quarterly to assess any changes in the levels of unexplained disease in different species, categorised in terms of clinical sign or body system, by comparison with previous years. No new diseases have been detected either through FarmFile or more traditional means since the new analyses started in earnest in 2004, but they have indicated that an unexplained event was not a new disease of concern, and developments continue to improve the system's sensitivity and specificity.

Mesh:

Year:  2008        PMID: 18552327     DOI: 10.1136/vr.162.24.771

Source DB:  PubMed          Journal:  Vet Rec        ISSN: 0042-4900            Impact factor:   2.695


  8 in total

1.  Use of spatiotemporal analysis of laboratory submission data to identify potential outbreaks of new or emerging diseases in cattle in Great Britain.

Authors:  Kieran Hyder; Alberto Vidal-Diez; Joanna Lawes; A Robin Sayers; Ailsa Milnes; Linda Hoinville; Alasdair J C Cook
Journal:  BMC Vet Res       Date:  2011-03-19       Impact factor: 2.741

2.  Unsupervised clustering of wildlife necropsy data for syndromic surveillance.

Authors:  Eva Warns-Petit; Eric Morignat; Marc Artois; Didier Calavas
Journal:  BMC Vet Res       Date:  2010-12-16       Impact factor: 2.741

3.  A focused ethnographic study of Alberta cattle veterinarians' decision making about diagnostic laboratory submissions and perceptions of surveillance programs.

Authors:  Kate Sawford; Ardene Robinson Vollman; Craig Stephen
Journal:  PLoS One       Date:  2013-05-31       Impact factor: 3.240

4.  Influences of farmer and veterinarian behaviour on emerging disease surveillance in England and Wales.

Authors:  W H Gilbert; B N Häsler; J Rushton
Journal:  Epidemiol Infect       Date:  2013-03-26       Impact factor: 4.434

Review 5.  Integrating novel data streams to support biosurveillance in commercial livestock production systems in developed countries: challenges and opportunities.

Authors:  M Carolyn Gates; Lindsey K Holmstrom; Keith E Biggers; Tammy R Beckham
Journal:  Front Public Health       Date:  2015-04-28

6.  Potential and Challenges of Community-Based Surveillance in Animal Health: A Pilot Study Among Equine Owners in Switzerland.

Authors:  Ranya Özçelik; Franziska Remy-Wohlfender; Susanne Küker; Vivianne Visschers; Daniela Hadorn; Salome Dürr
Journal:  Front Vet Sci       Date:  2021-06-04

7.  Identifying an outbreak of a novel swine disease using test requests for porcine reproductive and respiratory syndrome as a syndromic surveillance tool.

Authors:  Terri L O'Sullivan; Robert M Friendship; David L Pearl; Beverly McEwen; Catherine E Dewey
Journal:  BMC Vet Res       Date:  2012-10-16       Impact factor: 2.741

8.  Pig Abattoir Inspection Data: Can It Be Used for Surveillance Purposes?

Authors:  Carla Correia-Gomes; Richard P Smith; Jude I Eze; Madeleine K Henry; George J Gunn; Susanna Williamson; Sue C Tongue
Journal:  PLoS One       Date:  2016-08-26       Impact factor: 3.240

  8 in total

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