Re-emerging West Nile virus in horses from South Eastern France, 2015

Lecollinet, Sylvie; Beck, Cécile; Leblond, Agnès; Marcillaud-Pitel, Christel; Lowenski, Steeve; Hary, C.; Keck, Nicolas; Béfort, Jean-Claude; Durand, Benoı̂t; Bournez, Laure; Cavalerie, Lisa; Zientara, Stéphan

doi:10.1016/j.jevs.2016.02.057

Journal of Equine Veterinary Science

2016

DOI: 10.1016/j.jevs.2016.02.057

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Re-emerging West Nile virus in horses from South Eastern France, 2015

Sylvie Lecollinet

Cécile Beck

Agnès Leblond

et al.

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“…We focused on the French Mediterranean coast, which is a particularly high-risk area for WNV outbreaks. Indeed, in France, WNV has only ever been identified in this area according to the last outbreaks occurring in , 2004, and 2015(Murgue et al 2001, Autorino et al 2002, Anonymous 2007, Leblond et al 2007a, Kutasi et al 2011, Lecollinet et al 2016. This French region is especially at risk because mammalian and avian hosts, bridging vectors, and large protected wetlands with numerous migratory birds are all present.…”

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Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus

Faverjon

Andersson

Decors

et al. 2016

Vector-Borne and Zoonotic Diseases

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Background: Various methods are currently used for the early detection of West Nile virus (WNV) but their outputs are not quantitative and/or do not take into account all available information. Our study aimed to test a multivariate syndromic surveillance system to evaluate if the sensitivity and the specificity of detection of WNV could be improved. Methods: Weekly time series data on nervous syndromes in horses and mortality in both horses and wild birds were used. Baselines were fitted to the three time series and used to simulate 100 years of surveillance data. WNV outbreaks were simulated and inserted into the baselines based on historical data and expert opinion. Univariate and multivariate syndromic surveillance systems were tested to gauge how well they detected the outbreaks; detection was based on an empirical Bayesian approach. The systems' performances were compared using measures of sensitivity, specificity, and area under receiver operating characteristic curve (AUC). Results: When data sources were considered separately (i.e., univariate systems), the best detection performance was obtained using the data set of nervous symptoms in horses compared to those of bird and horse mortality (AUCs equal to 0.80, 0.75, and 0.50, respectively). A multivariate outbreak detection system that used nervous symptoms in horses and bird mortality generated the best performance (AUC = 0.87). Conclusions: The proposed approach is suitable for performing multivariate syndromic surveillance of WNV outbreaks. This is particularly relevant, given that a multivariate surveillance system performed better than a univariate approach. Such a surveillance system could be especially useful in serving as an alert for the possibility of human viral infections. This approach can be also used for other diseases for which multiple sources of evidence are available.

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mentioning

confidence: 99%

Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus

Faverjon

Andersson

Decors

et al. 2016

Vector-Borne and Zoonotic Diseases

View full text Add to dashboard Cite

show abstract

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Re-emerging West Nile virus in horses from South Eastern France, 2015

Cited by 1 publication

References 0 publications

Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus

Evaluation of a Multivariate Syndromic Surveillance System for West Nile Virus

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