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Predicting the spatio-temporal spread of West Nile virus in Europe

West Nile virus is a widely spread arthropod-born virus, which has mosquitoes as vectors and birds as reservoirs. Humans, as dead-end hosts of the virus, may suffer West Nile Fever (WNF), which sometimes leads to death. In Europe, the first large-scale epidemic of WNF occurred in 1996 in Romania. Si...

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Autores principales: García-Carrasco, José-María, Muñoz, Antonio-Román, Olivero, Jesús, Segura, Marina, Real, Raimundo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790247/
https://www.ncbi.nlm.nih.gov/pubmed/33411739
http://dx.doi.org/10.1371/journal.pntd.0009022
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author García-Carrasco, José-María
Muñoz, Antonio-Román
Olivero, Jesús
Segura, Marina
Real, Raimundo
author_facet García-Carrasco, José-María
Muñoz, Antonio-Román
Olivero, Jesús
Segura, Marina
Real, Raimundo
author_sort García-Carrasco, José-María
collection PubMed
description West Nile virus is a widely spread arthropod-born virus, which has mosquitoes as vectors and birds as reservoirs. Humans, as dead-end hosts of the virus, may suffer West Nile Fever (WNF), which sometimes leads to death. In Europe, the first large-scale epidemic of WNF occurred in 1996 in Romania. Since then, human cases have increased in the continent, where the highest number of cases occurred in 2018. Using the location of WNF cases in 2017 and favorability models, we developed two risk models, one environmental and the other spatio-environmental, and tested their capacity to predict in 2018: 1) the location of WNF; 2) the intensity of the outbreaks (i.e. the number of confirmed human cases); and 3) the imminence of the cases (i.e. the Julian week in which the first case occurred). We found that climatic variables (the maximum temperature of the warmest month and the annual temperature range), human-related variables (rain-fed agriculture, the density of poultry and horses), and topo-hydrographic variables (the presence of rivers and altitude) were the best environmental predictors of WNF outbreaks in Europe. The spatio-environmental model was the most useful in predicting the location of WNF outbreaks, which suggests that a spatial structure, probably related to bird migration routes, has a role in the geographical pattern of WNF in Europe. Both the intensity of cases and their imminence were best predicted using the environmental model, suggesting that these features of the disease are linked to the environmental characteristics of the areas. We highlight the relevance of river basins in the propagation dynamics of the disease, as outbreaks started in the lower parts of the river basins, from where WNF spread towards the upper parts. Therefore, river basins should be considered as operational geographic units for the public health management of the disease.
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spelling pubmed-77902472021-01-14 Predicting the spatio-temporal spread of West Nile virus in Europe García-Carrasco, José-María Muñoz, Antonio-Román Olivero, Jesús Segura, Marina Real, Raimundo PLoS Negl Trop Dis Research Article West Nile virus is a widely spread arthropod-born virus, which has mosquitoes as vectors and birds as reservoirs. Humans, as dead-end hosts of the virus, may suffer West Nile Fever (WNF), which sometimes leads to death. In Europe, the first large-scale epidemic of WNF occurred in 1996 in Romania. Since then, human cases have increased in the continent, where the highest number of cases occurred in 2018. Using the location of WNF cases in 2017 and favorability models, we developed two risk models, one environmental and the other spatio-environmental, and tested their capacity to predict in 2018: 1) the location of WNF; 2) the intensity of the outbreaks (i.e. the number of confirmed human cases); and 3) the imminence of the cases (i.e. the Julian week in which the first case occurred). We found that climatic variables (the maximum temperature of the warmest month and the annual temperature range), human-related variables (rain-fed agriculture, the density of poultry and horses), and topo-hydrographic variables (the presence of rivers and altitude) were the best environmental predictors of WNF outbreaks in Europe. The spatio-environmental model was the most useful in predicting the location of WNF outbreaks, which suggests that a spatial structure, probably related to bird migration routes, has a role in the geographical pattern of WNF in Europe. Both the intensity of cases and their imminence were best predicted using the environmental model, suggesting that these features of the disease are linked to the environmental characteristics of the areas. We highlight the relevance of river basins in the propagation dynamics of the disease, as outbreaks started in the lower parts of the river basins, from where WNF spread towards the upper parts. Therefore, river basins should be considered as operational geographic units for the public health management of the disease. Public Library of Science 2021-01-07 /pmc/articles/PMC7790247/ /pubmed/33411739 http://dx.doi.org/10.1371/journal.pntd.0009022 Text en © 2021 García-Carrasco et al 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 author and source are credited.
spellingShingle Research Article
García-Carrasco, José-María
Muñoz, Antonio-Román
Olivero, Jesús
Segura, Marina
Real, Raimundo
Predicting the spatio-temporal spread of West Nile virus in Europe
title Predicting the spatio-temporal spread of West Nile virus in Europe
title_full Predicting the spatio-temporal spread of West Nile virus in Europe
title_fullStr Predicting the spatio-temporal spread of West Nile virus in Europe
title_full_unstemmed Predicting the spatio-temporal spread of West Nile virus in Europe
title_short Predicting the spatio-temporal spread of West Nile virus in Europe
title_sort predicting the spatio-temporal spread of west nile virus in europe
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790247/
https://www.ncbi.nlm.nih.gov/pubmed/33411739
http://dx.doi.org/10.1371/journal.pntd.0009022
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