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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ftdoajarticles:oai:doaj.org/article:566573d2d27d44968f7893291745c461 2023-07-16T03:57:13+02:00 Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction. Win Zaw Zaw Lin July Ko Ko Chawarat Rotejanaprasert Neriza Pantanilla Steeve Ebener Richard James Maude 2023-06-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0011331 https://doaj.org/article/566573d2d27d44968f7893291745c461 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0011331 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0011331 https://doaj.org/article/566573d2d27d44968f7893291745c461 PLoS Neglected Tropical Diseases, Vol 17, Iss 6, p e0011331 (2023) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2023 ftdoajarticles https://doi.org/10.1371/journal.pntd.0011331 2023-06-25T00:34:55Z 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 17 6 e0011331 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Win Zaw Zaw Lin July Ko Ko Chawarat Rotejanaprasert Neriza Pantanilla Steeve Ebener Richard James Maude Dengue in Myanmar: Spatiotemporal epidemiology, association with climate and short-term prediction. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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. |
format |
Article in Journal/Newspaper |
author |
Win Zaw Zaw Lin July Ko Ko Chawarat Rotejanaprasert Neriza Pantanilla Steeve Ebener Richard James Maude |
author_facet |
Win Zaw Zaw Lin July Ko Ko Chawarat Rotejanaprasert Neriza Pantanilla Steeve Ebener Richard James Maude |
author_sort |
Win Zaw |
title |
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_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_sort |
dengue in myanmar: spatiotemporal epidemiology, association with climate and short-term prediction. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2023 |
url |
https://doi.org/10.1371/journal.pntd.0011331 https://doaj.org/article/566573d2d27d44968f7893291745c461 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 17, Iss 6, p e0011331 (2023) |
op_relation |
https://doi.org/10.1371/journal.pntd.0011331 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0011331 https://doaj.org/article/566573d2d27d44968f7893291745c461 |
op_doi |
https://doi.org/10.1371/journal.pntd.0011331 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
17 |
container_issue |
6 |
container_start_page |
e0011331 |
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