Environmental predictors of West Nile fever risk in Europe

Autor: Véronique Chevalier, Annie Desbrosse, Annelise Tran, Bertrand Sudre, Massimiliano Rossi, Jan C. Semenza, Shlomit Paz
Rok vydání: 2014
Předmět:
Epidemiology
Business
Management and Accounting(all)
L73 - Maladies des animaux
Facteur climatique
terre humide
Logistic regression
Risk Factors
Analyse du risque
Facteur de risque
Arbovirus
education.field_of_study
Surveillance
Incidence (epidemiology)
Temperature
Facteur du milieu
Vegetation
Environmental exposure
West nile virus
Remote sensing
B10 - Géographie
Europe
Épidémiologie
Geography
L20 - Écologie animale
Modèle mathématique
Computer Science(all)
General Computer Science
P40 - Météorologie et climatologie
Distribution géographique
Télédétection
Population
Risk maps
Normalized Difference Vegetation Index
Birds
Animals
Humans
Surveillance épidémiologique
education
Paysage
Cartographie
Research
Flavivirus
Migration animale
Public Health
Environmental and Occupational Health
Outbreak
Modèle de simulation
Environmental Exposure
Oiseau
Température
General Business
Management and Accounting
Confidence interval
West nile fever
Wetlands
Environmental determinants
Écologie animale
U30 - Méthodes de recherche
Forecasting
Demography
Zdroj: International Journal of Health Geographics
ISSN: 1476-072X
Popis: 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.
Databáze: OpenAIRE
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