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Epidemiology and infection2016; 145(5); 1044-1057; doi: 10.1017/S0950268816002946

Early detection of West Nile virus in France: quantitative assessment of syndromic surveillance system using nervous signs in horses.

Abstract: West Nile virus (WNV) is a growing public health concern in Europe and there is a need to develop more efficient early detection systems. Nervous signs in horses are considered to be an early indicator of WNV and, using them in a syndromic surveillance system, might be relevant. In our study, we assessed whether or not data collected by the passive French surveillance system for the surveillance of equine diseases can be used routinely for the detection of WNV. We tested several pre-processing methods and detection algorithms based on regression. We evaluated system performances using simulated and authentic data and compared them to those of the surveillance system currently in place. Our results show that the current detection algorithm provided similar performances to those tested using simulated and real data. However, regression models can be easily and better adapted to surveillance objectives. The detection performances obtained were compatible with the early detection of WNV outbreaks in France (i.e. sensitivity 98%, specificity >94%, timeliness 2·5 weeks and around four false alarms per year) but further work is needed to determine the most suitable alarm threshold for WNV surveillance in France using cost-efficiency analysis.
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Publication Date: 2016-12-12 PubMed ID: 27938434PubMed Central: PMC9507807DOI: 10.1017/S0950268816002946Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research evaluates the French surveillance system for equine diseases in early detection of West Nile virus (WNV), using horses’ nervous signs, and suggests that regression models yield better surveillance results.

Objectives of the Research

  • To evaluate the French surveillance system for detecting West Nile virus (WNV).
  • The focus is on nervous symptoms in horses, as these are considered early indicators of WNV.
  • To compare the effectiveness of various pre-processing methods and detection algorithms, particularly those based on regression.
  • To assess if the data gathered by the French equine diseases surveillance system can be used routinely for WNV detection.

Methods Employed in the Research

  • For the assessment, both simulated data and real-world data were used.
  • Different pre-processing methods were tested along with detection algorithms based on regression.
  • The results were compared with those of the currently existing surveillance system.

Findings of the Study

  • The study found that the algorithm currently in use for detection provided similar performances to those tested using simulated and real data.
  • However, it was seen that regression models can be adapted more easily and better to meet surveillance requirements.
  • The research revealed that the sensitivity was at 98% and specificity was over 94% with timeliness around 2.5 weeks and about four false alarms per year, which signifies that the detection performances can support early detection of WNV outbreaks in France.

Implications and Suggestions for Future Research

  • Although the initial results were promising, the study indicates the need for additional research to determine the most suitable alarm threshold for WNV surveillance in France.
  • This could be achieved through a cost-efficiency analysis which would help in enhancing the effectiveness of the surveillance system and reduce the number of false alarms.

Cite This Article

APA
Faverjon C, Vial F, Andersson MG, Lecollinet S, Leblond A. (2016). Early detection of West Nile virus in France: quantitative assessment of syndromic surveillance system using nervous signs in horses. Epidemiol Infect, 145(5), 1044-1057. https://doi.org/10.1017/S0950268816002946

Publication

Epidemiology and infection
ISSN: 1469-4409
NlmUniqueID: 8703737
Country: England
Language: English
Volume: 145
Issue: 5
Pages: 1044-1057

Researcher Affiliations

Faverjon, C
  • INRA UR0346 Animal Epidemiology,VetagroSup, Marcy l'Etoile,France.
Vial, F
  • Epi-Connect, Djupdalsvägen Skogås,Sweden.
Andersson, M G
  • Department of Chemistry,Environment and Feed Hygiene. The National Veterinary Institute,Uppsala,Sweden.
Lecollinet, S
  • UPE, ANSES,Animal Health Laboratory,UMR1161 Virologie, INRA, ANSES, ENVA,Maisons-Alfort,France.
Leblond, A
  • Réseau d'EpidémioSurveillance en Pathologie Equine (RESPE),Caen,France.

MeSH Terms

  • Animals
  • France / epidemiology
  • Horse Diseases / etiology
  • Horse Diseases / pathology
  • Horses
  • Nervous System Diseases / epidemiology
  • Nervous System Diseases / pathology
  • Nervous System Diseases / veterinary
  • Sensitivity and Specificity
  • Sentinel Surveillance
  • West Nile Fever / epidemiology
  • West Nile Fever / pathology
  • West Nile Fever / veterinary
  • West Nile virus / isolation & purification

Conflict of Interest Statement

None

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