Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction

Dengue is a major public health problem in Myanmar. The country aims to reduce morbidity by 50% and mortality by 90% by 2025 based on 2015 data. To support efforts to reach these goals it is important to have a detailed picture of the epidemiology of dengue, its relationship to meteorological factor...

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Autores principales: Zaw, Win, Lin, Zaw, Ko Ko, July, Rotejanaprasert, Chawarat, Pantanilla, Neriza, Ebener, Steeve, Maude, Richard James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270578/
https://www.ncbi.nlm.nih.gov/pubmed/37276226
http://dx.doi.org/10.1371/journal.pntd.0011331
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author Zaw, Win
Lin, Zaw
Ko Ko, July
Rotejanaprasert, Chawarat
Pantanilla, Neriza
Ebener, Steeve
Maude, Richard James
author_facet Zaw, Win
Lin, Zaw
Ko Ko, July
Rotejanaprasert, Chawarat
Pantanilla, Neriza
Ebener, Steeve
Maude, Richard James
author_sort Zaw, Win
collection PubMed
description Dengue is a major public health problem in Myanmar. The country aims to reduce morbidity by 50% and mortality by 90% by 2025 based on 2015 data. To support efforts to reach these goals it is important to have a detailed picture of the epidemiology of dengue, its relationship to meteorological factors and ideally to predict ahead of time numbers of cases to plan resource allocations and control efforts. Health facility-level data on numbers of dengue cases from 2012 to 2017 were obtained from the Vector Borne Disease Control Unit, Department of Public Health, Myanmar. A detailed analysis of routine dengue and dengue hemorrhagic fever (DHF) incidence was conducted to examine the spatial and temporal epidemiology. Incidence was compared to climate data over the same period. Dengue was found to be widespread across the country with an increase in spatial extent over time. The temporal pattern of dengue cases and fatalities was episodic with annual outbreaks and no clear longitudinal trend. There were 127,912 reported cases and 632 deaths from 2012 and 2017 with peaks in 2013, 2015 and 2017. The case fatality rate was around 0.5% throughout. The peak season of dengue cases was from May to August in the wet season but in 2014 peak dengue season continued until November. The strength of correlation of dengue incidence with different climate factors (total rainfall, maximum, mean and minimum temperature and absolute humidity) varied between different States and Regions. Monthly incidence was forecasted 1 month ahead using the Auto Regressive Integrated Moving Average (ARIMA) method at country and subnational levels. With further development and validation, this may be a simple way to quickly generate short-term predictions at subnational scales with sufficient certainty to use for intervention planning.
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spelling pubmed-102705782023-06-16 Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction Zaw, Win Lin, Zaw Ko Ko, July Rotejanaprasert, Chawarat Pantanilla, Neriza Ebener, Steeve Maude, Richard James PLoS Negl Trop Dis Research Article Dengue is a major public health problem in Myanmar. The country aims to reduce morbidity by 50% and mortality by 90% by 2025 based on 2015 data. To support efforts to reach these goals it is important to have a detailed picture of the epidemiology of dengue, its relationship to meteorological factors and ideally to predict ahead of time numbers of cases to plan resource allocations and control efforts. Health facility-level data on numbers of dengue cases from 2012 to 2017 were obtained from the Vector Borne Disease Control Unit, Department of Public Health, Myanmar. A detailed analysis of routine dengue and dengue hemorrhagic fever (DHF) incidence was conducted to examine the spatial and temporal epidemiology. Incidence was compared to climate data over the same period. Dengue was found to be widespread across the country with an increase in spatial extent over time. The temporal pattern of dengue cases and fatalities was episodic with annual outbreaks and no clear longitudinal trend. There were 127,912 reported cases and 632 deaths from 2012 and 2017 with peaks in 2013, 2015 and 2017. The case fatality rate was around 0.5% throughout. The peak season of dengue cases was from May to August in the wet season but in 2014 peak dengue season continued until November. The strength of correlation of dengue incidence with different climate factors (total rainfall, maximum, mean and minimum temperature and absolute humidity) varied between different States and Regions. Monthly incidence was forecasted 1 month ahead using the Auto Regressive Integrated Moving Average (ARIMA) method at country and subnational levels. With further development and validation, this may be a simple way to quickly generate short-term predictions at subnational scales with sufficient certainty to use for intervention planning. Public Library of Science 2023-06-05 /pmc/articles/PMC10270578/ /pubmed/37276226 http://dx.doi.org/10.1371/journal.pntd.0011331 Text en © 2023 Zaw 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
Zaw, Win
Lin, Zaw
Ko Ko, July
Rotejanaprasert, Chawarat
Pantanilla, Neriza
Ebener, Steeve
Maude, Richard James
Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title_full Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title_fullStr Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title_full_unstemmed Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title_short Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction
title_sort dengue in myanmar: spatiotemporal epidemiology, association with climate and short-term prediction
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270578/
https://www.ncbi.nlm.nih.gov/pubmed/37276226
http://dx.doi.org/10.1371/journal.pntd.0011331
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