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Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study

BACKGROUND: Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observi...

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Autores principales: Chien, Lung-Chang, Lin, Ro-Ting, Liao, Yunqi, Sy, Francisco S., Pérez, Adriana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905128/
https://www.ncbi.nlm.nih.gov/pubmed/29665783
http://dx.doi.org/10.1186/s12879-018-3085-x
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author Chien, Lung-Chang
Lin, Ro-Ting
Liao, Yunqi
Sy, Francisco S.
Pérez, Adriana
author_facet Chien, Lung-Chang
Lin, Ro-Ting
Liao, Yunqi
Sy, Francisco S.
Pérez, Adriana
author_sort Chien, Lung-Chang
collection PubMed
description BACKGROUND: Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. METHODS: This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015–December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. RESULTS: Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. CONCLUSION: Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3085-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-59051282018-04-24 Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study Chien, Lung-Chang Lin, Ro-Ting Liao, Yunqi Sy, Francisco S. Pérez, Adriana BMC Infect Dis Research Article BACKGROUND: Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. METHODS: This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015–December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. RESULTS: Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. CONCLUSION: Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3085-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-17 /pmc/articles/PMC5905128/ /pubmed/29665783 http://dx.doi.org/10.1186/s12879-018-3085-x Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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 Article
Chien, Lung-Chang
Lin, Ro-Ting
Liao, Yunqi
Sy, Francisco S.
Pérez, Adriana
Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title_full Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title_fullStr Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title_full_unstemmed Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title_short Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study
title_sort surveillance on the endemic of zika virus infection by meteorological factors in colombia: a population-based spatial and temporal study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905128/
https://www.ncbi.nlm.nih.gov/pubmed/29665783
http://dx.doi.org/10.1186/s12879-018-3085-x
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