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Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar

BACKGROUND: Myanmar bears the heaviest malaria burden in the Greater Mekong Subregion (GMS). This study assessed the spatio-temporal dynamics and environmental predictors of Plasmodium falciparum and Plasmodium vivax malaria in Myanmar. METHODS: Monthly reports of malaria cases at primary health cen...

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Autores principales: Zhao, Yan, Aung, Pyae Linn, Ruan, Shishao, Win, Kyawt Mon, Wu, Zifang, Soe, Than Naing, Soe, Myat Thu, Cao, Yaming, Sattabongkot, Jetsumon, Kyaw, Myat Phone, Cui, Liwang, Menezes, Lynette, Parker, Daniel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883610/
https://www.ncbi.nlm.nih.gov/pubmed/36709318
http://dx.doi.org/10.1186/s40249-023-01055-6
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author Zhao, Yan
Aung, Pyae Linn
Ruan, Shishao
Win, Kyawt Mon
Wu, Zifang
Soe, Than Naing
Soe, Myat Thu
Cao, Yaming
Sattabongkot, Jetsumon
Kyaw, Myat Phone
Cui, Liwang
Menezes, Lynette
Parker, Daniel M.
author_facet Zhao, Yan
Aung, Pyae Linn
Ruan, Shishao
Win, Kyawt Mon
Wu, Zifang
Soe, Than Naing
Soe, Myat Thu
Cao, Yaming
Sattabongkot, Jetsumon
Kyaw, Myat Phone
Cui, Liwang
Menezes, Lynette
Parker, Daniel M.
author_sort Zhao, Yan
collection PubMed
description BACKGROUND: Myanmar bears the heaviest malaria burden in the Greater Mekong Subregion (GMS). This study assessed the spatio-temporal dynamics and environmental predictors of Plasmodium falciparum and Plasmodium vivax malaria in Myanmar. METHODS: Monthly reports of malaria cases at primary health centers during 2011–2017 were analyzed to describe malaria distribution across Myanmar at the township and state/region levels by spatial autocorrelation (Moran index) and spatio-temporal clustering. Negative binomial generalized additive models identified environmental predictors for falciparum and vivax malaria, respectively. RESULTS: From 2011 to 2017, there was an apparent reduction in malaria incidence in Myanmar. Malaria incidence peaked in June each year. There were significant spatial autocorrelation and clustering with extreme spatial heterogeneity in malaria cases and test positivity across the nation (P < 0.05). Areas with higher malaria incidence were concentrated along international borders. Primary clusters of P. falciparum persisted in western townships, while clusters of P. vivax shifted geographically over the study period. The primary cluster was detected from January 2011 to December 2013 and covered two states (Sagaing and Kachin). Annual malaria incidence was highest in townships with a mean elevation of 500‒600 m and a high variance in elevation (states with both high and low elevation). There was an apparent linear relationship between the mean normalized difference vegetative index and annual P. falciparum incidence (P < 0.05). CONCLUSION: The decreasing trends reflect the significant achievement of malaria control efforts in Myanmar. Prioritizing the allocation of resources to high-risk areas identified in this study can achieve effective disease control. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01055-6.
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spelling pubmed-98836102023-01-29 Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar Zhao, Yan Aung, Pyae Linn Ruan, Shishao Win, Kyawt Mon Wu, Zifang Soe, Than Naing Soe, Myat Thu Cao, Yaming Sattabongkot, Jetsumon Kyaw, Myat Phone Cui, Liwang Menezes, Lynette Parker, Daniel M. Infect Dis Poverty Research Article BACKGROUND: Myanmar bears the heaviest malaria burden in the Greater Mekong Subregion (GMS). This study assessed the spatio-temporal dynamics and environmental predictors of Plasmodium falciparum and Plasmodium vivax malaria in Myanmar. METHODS: Monthly reports of malaria cases at primary health centers during 2011–2017 were analyzed to describe malaria distribution across Myanmar at the township and state/region levels by spatial autocorrelation (Moran index) and spatio-temporal clustering. Negative binomial generalized additive models identified environmental predictors for falciparum and vivax malaria, respectively. RESULTS: From 2011 to 2017, there was an apparent reduction in malaria incidence in Myanmar. Malaria incidence peaked in June each year. There were significant spatial autocorrelation and clustering with extreme spatial heterogeneity in malaria cases and test positivity across the nation (P < 0.05). Areas with higher malaria incidence were concentrated along international borders. Primary clusters of P. falciparum persisted in western townships, while clusters of P. vivax shifted geographically over the study period. The primary cluster was detected from January 2011 to December 2013 and covered two states (Sagaing and Kachin). Annual malaria incidence was highest in townships with a mean elevation of 500‒600 m and a high variance in elevation (states with both high and low elevation). There was an apparent linear relationship between the mean normalized difference vegetative index and annual P. falciparum incidence (P < 0.05). CONCLUSION: The decreasing trends reflect the significant achievement of malaria control efforts in Myanmar. Prioritizing the allocation of resources to high-risk areas identified in this study can achieve effective disease control. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01055-6. BioMed Central 2023-01-28 /pmc/articles/PMC9883610/ /pubmed/36709318 http://dx.doi.org/10.1186/s40249-023-01055-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Zhao, Yan
Aung, Pyae Linn
Ruan, Shishao
Win, Kyawt Mon
Wu, Zifang
Soe, Than Naing
Soe, Myat Thu
Cao, Yaming
Sattabongkot, Jetsumon
Kyaw, Myat Phone
Cui, Liwang
Menezes, Lynette
Parker, Daniel M.
Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title_full Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title_fullStr Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title_full_unstemmed Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title_short Spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in Myanmar
title_sort spatio-temporal trends of malaria incidence from 2011 to 2017 and environmental predictors of malaria transmission in myanmar
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883610/
https://www.ncbi.nlm.nih.gov/pubmed/36709318
http://dx.doi.org/10.1186/s40249-023-01055-6
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