Application of syndromic surveillance on routinely collected cattle reproduction and milk production data for the early detection of outbreaks of Bluetongue and Schmallenberg viruses

Anouk Veldhuis*, Henriëtte Brouwer-Middelesch, Alexis Marceau, Aurélien Madouasse, Yves Van der Stede, Christine Fourichon, Sarah Welby, Paul Wever, Gerdien van Schaik

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    This study aimed to evaluate the use of routinely collected reproductive and milk production data for the early detection of emerging vector-borne diseases in cattle in the Netherlands and the Flanders region of Belgium (i.e., the northern part of Belgium). Prospective space-time cluster analyses on residuals from a model on milk production were carried out to detect clusters of reduced milk yield. A CUSUM algorithm was used to detect temporal aberrations in model residuals of reproductive performance models on two indicators of gestation length. The Bluetongue serotype-8 (BTV-8) epidemics of 2006 and 2007 and the Schmallenberg virus (SBV) epidemic of 2011 were used as case studies to evaluate the sensitivity and timeliness of these methods. The methods investigated in this study did not result in a more timely detection of BTV-8 and SBV in the Netherlands and BTV-8 in Belgium given the surveillance systems in place when these viruses emerged. This could be due to (i) the large geographical units used in the analyses (country, region and province level), and (ii) the high level of sensitivity of the surveillance systems in place when these viruses emerged. Nevertheless, it might be worthwhile to use a syndromic surveillance system based on non-specific animal health data in real-time alongside regular surveillance, to increase the sense of urgency and to provide valuable quantitative information for decision makers in the initial phase of an emerging disease outbreak.

    Original languageEnglish
    Pages (from-to)15-24
    Number of pages10
    JournalPreventive Veterinary Medicine
    Volume124
    DOIs
    Publication statusPublished - 1 Feb 2016

    Funding

    This study was funded by the Dutch Ministry of Economic Affairs (EZ) and the Belgian Federal Agency for Safety of the Food Chain (FASFC) in the framework of the European project EMIDA ERA-NET Early Detection Data.

    Keywords

    • Cattle
    • Early-warning
    • Syndromic surveillance
    • Vector-borne

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