Cargando…

Environmental predictors of West Nile fever risk in Europe

BACKGROUND: West Nile virus (WNV) is a mosquito-borne pathogen of global public health importance. Transmission of WNV is determined by abiotic and biotic factors. The objective of this study was to examine environmental variables as predictors of WNV risk in Europe and neighboring countries, consid...

Descripción completa

Detalles Bibliográficos
Autores principales: Tran, Annelise, Sudre, Bertrand, Paz, Shlomit, Rossi, Massimiliano, Desbrosse, Annie, Chevalier, Véronique, Semenza, Jan C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118316/
https://www.ncbi.nlm.nih.gov/pubmed/24986363
http://dx.doi.org/10.1186/1476-072X-13-26
_version_ 1782328822333440000
author Tran, Annelise
Sudre, Bertrand
Paz, Shlomit
Rossi, Massimiliano
Desbrosse, Annie
Chevalier, Véronique
Semenza, Jan C
author_facet Tran, Annelise
Sudre, Bertrand
Paz, Shlomit
Rossi, Massimiliano
Desbrosse, Annie
Chevalier, Véronique
Semenza, Jan C
author_sort Tran, Annelise
collection PubMed
description BACKGROUND: West Nile virus (WNV) is a mosquito-borne pathogen of global public health importance. Transmission of WNV is determined by abiotic and biotic factors. The objective of this study was to examine environmental variables as predictors of WNV risk in Europe and neighboring countries, considering the anomalies of remotely sensed water and vegetation indices and of temperature at the locations of West Nile fever (WNF) outbreaks reported in humans between 2002 and 2013. METHODS: The status of infection by WNV in relationship to environmental and climatic risk factors was analyzed at the district level using logistic regression models. Temperature, remotely sensed Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) anomalies, as well as population, birds’ migratory routes, and presence of wetlands were considered as explanatory variables. RESULTS: The anomalies of temperature in July, of MNDWI in early June, the presence of wetlands, the location under migratory routes, and the occurrence of a WNF outbreak the previous year were identified as risk factors. The best statistical model according to the Akaike Information Criterion was used to map WNF risk areas in 2012 and 2013. Model validations showed a good level of prediction: area under Receiver Operator Characteristic curve = 0.854 (95% Confidence Interval 0.850-0.856) for internal validation and 0.819 (95% Confidence Interval 0.814-0.823) (2012) and 0.853 (95% Confidence Interval 0.850-0.855) (2013) for external validations, respectively. CONCLUSIONS: WNF incidence is increasing in Europe and WNV is expanding into new areas where it had never been observed before. Our model can be used to direct surveillance activities and public health interventions for the upcoming WNF season.
format Online
Article
Text
id pubmed-4118316
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-41183162014-08-05 Environmental predictors of West Nile fever risk in Europe Tran, Annelise Sudre, Bertrand Paz, Shlomit Rossi, Massimiliano Desbrosse, Annie Chevalier, Véronique Semenza, Jan C Int J Health Geogr Research BACKGROUND: West Nile virus (WNV) is a mosquito-borne pathogen of global public health importance. Transmission of WNV is determined by abiotic and biotic factors. The objective of this study was to examine environmental variables as predictors of WNV risk in Europe and neighboring countries, considering the anomalies of remotely sensed water and vegetation indices and of temperature at the locations of West Nile fever (WNF) outbreaks reported in humans between 2002 and 2013. METHODS: The status of infection by WNV in relationship to environmental and climatic risk factors was analyzed at the district level using logistic regression models. Temperature, remotely sensed Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) anomalies, as well as population, birds’ migratory routes, and presence of wetlands were considered as explanatory variables. RESULTS: The anomalies of temperature in July, of MNDWI in early June, the presence of wetlands, the location under migratory routes, and the occurrence of a WNF outbreak the previous year were identified as risk factors. The best statistical model according to the Akaike Information Criterion was used to map WNF risk areas in 2012 and 2013. Model validations showed a good level of prediction: area under Receiver Operator Characteristic curve = 0.854 (95% Confidence Interval 0.850-0.856) for internal validation and 0.819 (95% Confidence Interval 0.814-0.823) (2012) and 0.853 (95% Confidence Interval 0.850-0.855) (2013) for external validations, respectively. CONCLUSIONS: WNF incidence is increasing in Europe and WNV is expanding into new areas where it had never been observed before. Our model can be used to direct surveillance activities and public health interventions for the upcoming WNF season. BioMed Central 2014-07-01 /pmc/articles/PMC4118316/ /pubmed/24986363 http://dx.doi.org/10.1186/1476-072X-13-26 Text en Copyright © 2014 Tran et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Tran, Annelise
Sudre, Bertrand
Paz, Shlomit
Rossi, Massimiliano
Desbrosse, Annie
Chevalier, Véronique
Semenza, Jan C
Environmental predictors of West Nile fever risk in Europe
title Environmental predictors of West Nile fever risk in Europe
title_full Environmental predictors of West Nile fever risk in Europe
title_fullStr Environmental predictors of West Nile fever risk in Europe
title_full_unstemmed Environmental predictors of West Nile fever risk in Europe
title_short Environmental predictors of West Nile fever risk in Europe
title_sort environmental predictors of west nile fever risk in europe
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118316/
https://www.ncbi.nlm.nih.gov/pubmed/24986363
http://dx.doi.org/10.1186/1476-072X-13-26
work_keys_str_mv AT tranannelise environmentalpredictorsofwestnilefeverriskineurope
AT sudrebertrand environmentalpredictorsofwestnilefeverriskineurope
AT pazshlomit environmentalpredictorsofwestnilefeverriskineurope
AT rossimassimiliano environmentalpredictorsofwestnilefeverriskineurope
AT desbrosseannie environmentalpredictorsofwestnilefeverriskineurope
AT chevalierveronique environmentalpredictorsofwestnilefeverriskineurope
AT semenzajanc environmentalpredictorsofwestnilefeverriskineurope