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From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border

BACKGROUND: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination. The aim of this study is to investigate the epidemiology of malaria along the border, will identify challenges in the prog...

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Autores principales: Huang, Fang, Zhang, Li, Xue, Jing-Bo, Zhou, Hong-Ning, Thi, Aung, Zhang, Jun, Zhou, Shui-Sen, Xia, Zhi-Gui, Zhou, Xiao-Nong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676414/
https://www.ncbi.nlm.nih.gov/pubmed/33213516
http://dx.doi.org/10.1186/s40249-020-00777-1
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author Huang, Fang
Zhang, Li
Xue, Jing-Bo
Zhou, Hong-Ning
Thi, Aung
Zhang, Jun
Zhou, Shui-Sen
Xia, Zhi-Gui
Zhou, Xiao-Nong
author_facet Huang, Fang
Zhang, Li
Xue, Jing-Bo
Zhou, Hong-Ning
Thi, Aung
Zhang, Jun
Zhou, Shui-Sen
Xia, Zhi-Gui
Zhou, Xiao-Nong
author_sort Huang, Fang
collection PubMed
description BACKGROUND: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination. The aim of this study is to investigate the epidemiology of malaria along the border, will identify challenges in the progress from control to elimination. METHODS: National reported malaria cases from China and Myanmar, along with the data of 18 Chinese border counties and 23 townships in Myanmar were obtained from a web-based diseases information reporting system in China and the national malaria control program of Myanmar, respectively. Epidemiological data was analyzed, including the number of reported cases, annual parasite index and proportion of vivax infection. Spatial mapping of the annual parasite index (API) at county or township level in 2014 and 2018 was performed by ArcGIS. The relationship of malaria endemicity on both sides of the border was evaluated by regression analysis. RESULTS: The number of reported malaria cases and API declined in the border counties or townships. In 2014, 392 malaria cases were reported from 18 Chinese border counties, including 8.4% indigenous cases and 91.6% imported cases, while the highest API (0.11) was occurred in Yingjiang County. There have been no indigenous cases reported since 2017, but 164 imported cases were reported in 2018 and 97.6% were imported from Myanmar. The average API in 2014 in 23 Myanmar townships was significantly greater than that of 18 Chinese counties (P < 0.01). However, the API decreased significantly in Myanmar side from 2014 to 2018 (P < 0.01). The number of townships with an API between 0 and 1 increased to 15 in 2018, compared to only five in 2014, while still four townships had API > 10. Plasmodium vivax was the predominant species along the border. The number of reported malaria cases and the proportion of vivax infection in the 18 Chinese counties were strongly correlated with those of the 23 Myanmar townships (P < 0.05). CONCLUSIONS: Malaria elimination is approaching along the China-Myanmar border. However, in order to achieve the malaria elimination in this region and prevent the re-establishment of malaria in China after elimination, continued political, financial and scientific commitment is required.
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spelling pubmed-76764142020-11-19 From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border Huang, Fang Zhang, Li Xue, Jing-Bo Zhou, Hong-Ning Thi, Aung Zhang, Jun Zhou, Shui-Sen Xia, Zhi-Gui Zhou, Xiao-Nong Infect Dis Poverty Research Article BACKGROUND: Malaria cases have declined significantly along the China-Myanmar border in the past 10 years and this region is going through a process from control to elimination. The aim of this study is to investigate the epidemiology of malaria along the border, will identify challenges in the progress from control to elimination. METHODS: National reported malaria cases from China and Myanmar, along with the data of 18 Chinese border counties and 23 townships in Myanmar were obtained from a web-based diseases information reporting system in China and the national malaria control program of Myanmar, respectively. Epidemiological data was analyzed, including the number of reported cases, annual parasite index and proportion of vivax infection. Spatial mapping of the annual parasite index (API) at county or township level in 2014 and 2018 was performed by ArcGIS. The relationship of malaria endemicity on both sides of the border was evaluated by regression analysis. RESULTS: The number of reported malaria cases and API declined in the border counties or townships. In 2014, 392 malaria cases were reported from 18 Chinese border counties, including 8.4% indigenous cases and 91.6% imported cases, while the highest API (0.11) was occurred in Yingjiang County. There have been no indigenous cases reported since 2017, but 164 imported cases were reported in 2018 and 97.6% were imported from Myanmar. The average API in 2014 in 23 Myanmar townships was significantly greater than that of 18 Chinese counties (P < 0.01). However, the API decreased significantly in Myanmar side from 2014 to 2018 (P < 0.01). The number of townships with an API between 0 and 1 increased to 15 in 2018, compared to only five in 2014, while still four townships had API > 10. Plasmodium vivax was the predominant species along the border. The number of reported malaria cases and the proportion of vivax infection in the 18 Chinese counties were strongly correlated with those of the 23 Myanmar townships (P < 0.05). CONCLUSIONS: Malaria elimination is approaching along the China-Myanmar border. However, in order to achieve the malaria elimination in this region and prevent the re-establishment of malaria in China after elimination, continued political, financial and scientific commitment is required. BioMed Central 2020-11-19 /pmc/articles/PMC7676414/ /pubmed/33213516 http://dx.doi.org/10.1186/s40249-020-00777-1 Text en © The Author(s) 2020 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/. 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 in a credit line to the data.
spellingShingle Research Article
Huang, Fang
Zhang, Li
Xue, Jing-Bo
Zhou, Hong-Ning
Thi, Aung
Zhang, Jun
Zhou, Shui-Sen
Xia, Zhi-Gui
Zhou, Xiao-Nong
From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title_full From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title_fullStr From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title_full_unstemmed From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title_short From control to elimination: a spatial-temporal analysis of malaria along the China-Myanmar border
title_sort from control to elimination: a spatial-temporal analysis of malaria along the china-myanmar border
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676414/
https://www.ncbi.nlm.nih.gov/pubmed/33213516
http://dx.doi.org/10.1186/s40249-020-00777-1
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