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West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis
An intensified and continuous West Nile virus (WNV) spread across northern Italy has been observed since 2008, which caused more than one hundred reported human infections until 2016. Veneto is one of the Italian regions where WNV is considered endemic, and the greatest intensity of circulation was...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6143586/ https://www.ncbi.nlm.nih.gov/pubmed/30228340 http://dx.doi.org/10.1038/s41598-018-32401-6 |
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author | Marini, Giovanni Rosà, Roberto Pugliese, Andrea Rizzoli, Annapaola Rizzo, Caterina Russo, Francesca Montarsi, Fabrizio Capelli, Gioia |
author_facet | Marini, Giovanni Rosà, Roberto Pugliese, Andrea Rizzoli, Annapaola Rizzo, Caterina Russo, Francesca Montarsi, Fabrizio Capelli, Gioia |
author_sort | Marini, Giovanni |
collection | PubMed |
description | An intensified and continuous West Nile virus (WNV) spread across northern Italy has been observed since 2008, which caused more than one hundred reported human infections until 2016. Veneto is one of the Italian regions where WNV is considered endemic, and the greatest intensity of circulation was observed during 2013 and 2016. By using entomological data collected across the region in those years, we calibrated a temperature-driven mathematical model through a Bayesian approach that simulates the WNV infection in an avian population with seasonal demography. We considered two alternative routes of life cycle re-activation of the virus at the beginning of each vector breeding season: in the first one the virus is maintained by infected birds, in the other by diapausing mosquitoes previously infected. Afterwards, we computed seasonal risk curves for human infection and quantified how they translate into reported symptomatic cases. According to our results, WNV is more likely to be re-activated each year via previously infected mosquitoes. The highest probability of human infection is expected to occur in August, consistently with observations. Our epidemiological estimates can be of particular interest for public health authorities, to support decisions in term of designing efficient surveillance plans and preventive measures. |
format | Online Article Text |
id | pubmed-6143586 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61435862018-09-24 West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis Marini, Giovanni Rosà, Roberto Pugliese, Andrea Rizzoli, Annapaola Rizzo, Caterina Russo, Francesca Montarsi, Fabrizio Capelli, Gioia Sci Rep Article An intensified and continuous West Nile virus (WNV) spread across northern Italy has been observed since 2008, which caused more than one hundred reported human infections until 2016. Veneto is one of the Italian regions where WNV is considered endemic, and the greatest intensity of circulation was observed during 2013 and 2016. By using entomological data collected across the region in those years, we calibrated a temperature-driven mathematical model through a Bayesian approach that simulates the WNV infection in an avian population with seasonal demography. We considered two alternative routes of life cycle re-activation of the virus at the beginning of each vector breeding season: in the first one the virus is maintained by infected birds, in the other by diapausing mosquitoes previously infected. Afterwards, we computed seasonal risk curves for human infection and quantified how they translate into reported symptomatic cases. According to our results, WNV is more likely to be re-activated each year via previously infected mosquitoes. The highest probability of human infection is expected to occur in August, consistently with observations. Our epidemiological estimates can be of particular interest for public health authorities, to support decisions in term of designing efficient surveillance plans and preventive measures. Nature Publishing Group UK 2018-09-18 /pmc/articles/PMC6143586/ /pubmed/30228340 http://dx.doi.org/10.1038/s41598-018-32401-6 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Marini, Giovanni Rosà, Roberto Pugliese, Andrea Rizzoli, Annapaola Rizzo, Caterina Russo, Francesca Montarsi, Fabrizio Capelli, Gioia West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title | West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title_full | West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title_fullStr | West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title_full_unstemmed | West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title_short | West Nile virus transmission and human infection risk in Veneto (Italy): a modelling analysis |
title_sort | west nile virus transmission and human infection risk in veneto (italy): a modelling analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6143586/ https://www.ncbi.nlm.nih.gov/pubmed/30228340 http://dx.doi.org/10.1038/s41598-018-32401-6 |
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