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Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018

The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early...

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Autores principales: Hossain, M. Pear, Zhou, Wen, Ren, Chao, Marshall, John, Yuan, Hsiang-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021868/
https://www.ncbi.nlm.nih.gov/pubmed/36962108
http://dx.doi.org/10.1371/journal.pgph.0000047
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author Hossain, M. Pear
Zhou, Wen
Ren, Chao
Marshall, John
Yuan, Hsiang-Yu
author_facet Hossain, M. Pear
Zhou, Wen
Ren, Chao
Marshall, John
Yuan, Hsiang-Yu
author_sort Hossain, M. Pear
collection PubMed
description The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early warning of future outbreaks. We developed a generalized linear model to predict the number of annual dengue cases based on monthly minimum temperature, rainfall and sunshine prior to dengue season. Variable selection and leave-one-out cross-validation were performed to identify the best prediction model and to evaluate the model’s performance. Our model successfully predicted the largest outbreak in 2018, with 10,077 cases (95% CI: [9,912–10,276]), in addition to smaller outbreaks in five different years (2003, 2006, 2010, 2012 and 2014) and successfully identified the increasing trend in cases between 2010 and 2018. We found that temperature was positively associated with the annual incidence during the late winter months (between January and March) but negatively associated during the early summer (between April and June). Our results might be suggest an optimal minimum temperature for mosquito growth of 21–23°C. This study has implications for understanding how climate variability has affected recent dengue expansion in neighbours of Bangladesh (such as northern India and Southeast Asia).
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spelling pubmed-100218682023-03-17 Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018 Hossain, M. Pear Zhou, Wen Ren, Chao Marshall, John Yuan, Hsiang-Yu PLOS Glob Public Health Research Article The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early warning of future outbreaks. We developed a generalized linear model to predict the number of annual dengue cases based on monthly minimum temperature, rainfall and sunshine prior to dengue season. Variable selection and leave-one-out cross-validation were performed to identify the best prediction model and to evaluate the model’s performance. Our model successfully predicted the largest outbreak in 2018, with 10,077 cases (95% CI: [9,912–10,276]), in addition to smaller outbreaks in five different years (2003, 2006, 2010, 2012 and 2014) and successfully identified the increasing trend in cases between 2010 and 2018. We found that temperature was positively associated with the annual incidence during the late winter months (between January and March) but negatively associated during the early summer (between April and June). Our results might be suggest an optimal minimum temperature for mosquito growth of 21–23°C. This study has implications for understanding how climate variability has affected recent dengue expansion in neighbours of Bangladesh (such as northern India and Southeast Asia). Public Library of Science 2022-05-09 /pmc/articles/PMC10021868/ /pubmed/36962108 http://dx.doi.org/10.1371/journal.pgph.0000047 Text en © 2022 Hossain et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Hossain, M. Pear
Zhou, Wen
Ren, Chao
Marshall, John
Yuan, Hsiang-Yu
Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title_full Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title_fullStr Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title_full_unstemmed Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title_short Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018
title_sort prediction of dengue annual incidence using seasonal climate variability in bangladesh between 2000 and 2018
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021868/
https://www.ncbi.nlm.nih.gov/pubmed/36962108
http://dx.doi.org/10.1371/journal.pgph.0000047
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