Literature DB >> 22107890

Structuring the passive surveillance network improves epizootic detection and control efficacy: a simulation study on foot-and-mouth disease in France.

S Rautureau1, B Dufour, B Durand.   

Abstract

Rapid detection of infection is critical to the containment and control of contagious pathogens. Passive surveillance, based on the detection of clinical signs through farmers' observations and subsequent veterinarian notification, is the primary means of initially detecting an epizootic and for implementing control measures. The objective of this study was to analyse how the composition and structure of passive surveillance networks may impact epizootic spread and control. Three compositions of passive surveillance network were considered: (i) A veterinarian-based surveillance network composed of farmers and veterinarians (the common passive surveillance network where each veterinarian follows up a group of holdings), (ii) a farmer-based surveillance network composed of farmers only (the farmer plays the same role as in the preceding network as well as that of the veterinarian but his point of view is limited to his animals) and (iii) a hierarchical surveillance network composed of farmers, veterinarians and district-level veterinarian specialists (in case of doubt, the local veterinarian calls the specialist veterinarian). We compared the efficacy of these different network types where actors have successively a structurally wider perspective than the preceding ones using a specific stochastic model for the spread of foot-and-mouth disease (FMD). The model was forced by actual data to generate realistic simulated FMD epizootics in France. Our results show that maintaining the presence of field veterinarians following-up several holdings in breeding areas is fundamental and adding veterinarian specialists to passive surveillance networks could greatly enhance surveillance network efficacy.
© 2011 Blackwell Verlag GmbH.

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Year:  2011        PMID: 22107890     DOI: 10.1111/j.1865-1682.2011.01271.x

Source DB:  PubMed          Journal:  Transbound Emerg Dis        ISSN: 1865-1674            Impact factor:   5.005


  4 in total

1.  Epidemic predictions in an imperfect world: modelling disease spread with partial data.

Authors:  Peter M Dawson; Marleen Werkman; Ellen Brooks-Pollock; Michael J Tildesley
Journal:  Proc Biol Sci       Date:  2015-06-07       Impact factor: 5.349

2.  Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak.

Authors:  Hachung Yoon; Soon-Seek Yoon; Han Kim; Youn-Ju Kim; Byounghan Kim; Sung-Hwan Wee
Journal:  Osong Public Health Res Perspect       Date:  2013-05-15

3.  Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records.

Authors:  Jean-Baptiste Perrin; Benoît Durand; Emilie Gay; Christian Ducrot; Pascal Hendrikx; Didier Calavas; Viviane Hénaux
Journal:  PLoS One       Date:  2015-11-04       Impact factor: 3.240

4.  Impact of stakeholders influence, geographic level and risk perception on strategic decisions in simulated foot and mouth disease epizootics in France.

Authors:  Maud Marsot; Séverine Rautureau; Barbara Dufour; Benoit Durand
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

  4 in total

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