Integrating indicator-based and event-based surveillance data for risk mapping of West Nile virus, Europe, 2006 to 2021

BackgroundWest Nile virus (WNV) has an enzootic cycle between birds and mosquitoes, humans being incidental dead-end hosts. Circulation of WNV is an increasing public health threat in Europe. While detection of WNV is notifiable in humans and animals in the European Union, surveillance based on human case numbers presents some limitations, including reporting delays.AimWe aimed to perform risk mapping of WNV circulation leading to human infections in Europe by integrating two types of surveillance systems: indicator-based and event-based surveillance.MethodsFor indicator-based surveillance, we used data on human case numbers reported to the European Centre for Disease Prevention and Control (ECDC), and for event-based data, we retrieved information from news articles collected through an automated biosurveillance platform. In addition to these data sources, we also used environmental data to train ecological niche models to map the risk of local WNV circulation leading to human infections.ResultsThe ecological niche models based on both types of surveillance data highlighted new areas potentially at risk of WNV infection in humans, particularly in Spain, Italy, France and Greece.ConclusionAlthough event-based surveillance data do not constitute confirmed occurrence records, integrating both indicator-based and event-based surveillance data proved useful. These results underscore the potential for a more proactive and comprehensive strategy in managing the threat of WNV in Europe by combining indicator- and event-based and environmental data for effective surveillance and public health response.

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Publication Details

Journal
Eurosurveillance
Published
2024-10-31
DOI
https://doi.org/10.2807/1560-7917.es.2024.29.44.2400084
Citations
9
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
3.48

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article

Integrating indicator-based and event-based surveillance data for risk mapping of West Nile virus, Europe, 2006 to 2021

Wim Van Bortel, María F. Vincenti‐González, Diana Erazo, Elena Arsevska et al.
9 citations
Eurosurveillance
Data-Driven Disease Surveillance
3.48
article

Integrating indicator-based and event-based surveillance data for risk mapping of West Nile virus, Europe, 2006 to 2021

Wim Van Bortel, María F. Vincenti‐González, Diana Erazo, Elena Arsevska, Simon Dellicour, Kyla Serres, Garance Despréaux
article en
9 citations

Abstract

BackgroundWest Nile virus (WNV) has an enzootic cycle between birds and mosquitoes, humans being incidental dead-end hosts. Circulation of WNV is an increasing public health threat in Europe. While detection of WNV is notifiable in humans and animals in the European Union, surveillance based on human case numbers presents some limitations, including reporting delays.AimWe aimed to perform risk mapping of WNV circulation leading to human infections in Europe by integrating two types of surveillance systems: indicator-based and event-based surveillance.MethodsFor indicator-based surveillance, we used data on human case numbers reported to the European Centre for Disease Prevention and Control (ECDC), and for event-based data, we retrieved information from news articles collected through an automated biosurveillance platform. In addition to these data sources, we also used environmental data to train ecological niche models to map the risk of local WNV circulation leading to human infections.ResultsThe ecological niche models based on both types of surveillance data highlighted new areas potentially at risk of WNV infection in humans, particularly in Spain, Italy, France and Greece.ConclusionAlthough event-based surveillance data do not constitute confirmed occurrence records, integrating both indicator-based and event-based surveillance data proved useful. These results underscore the potential for a more proactive and comprehensive strategy in managing the threat of WNV in Europe by combining indicator- and event-based and environmental data for effective surveillance and public health response.

EurosurveillanceVol. 29(44)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Université Libre de Bruxelles (BE), Rega Institute for Medical Research (BE), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Animal, Santé, Territoires, Risques et Ecosystèmes (FR), Département Santé Animale (FR), Instituut voor Tropische Geneeskunde (BE), KU Leuven (BE)
European Commission, European Centre for Disease Prevention and Control, Fonds De La Recherche Scientifique - FNRS, Fonds Wetenschappelijk Onderzoek, Vlaamse regering, Departement Economie, Wetenschap en Innovatie
Good health and well-being
Openalex Percentile: Top 6%
Data-Driven Disease Surveillance
3.48
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