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Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination

BACKGROUND: Myanmar has targeted elimination of malaria by 2030. In three targeted townships of Rakhine state of Myanmar, a project is being piloted to eliminate malaria by 2025. The comprehensive case investigation (CCI) and geotagging of cases by health workers is a core activity under the project...

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Autores principales: Khine, San Kyawt, Kyaw, Nang Thu Thu, Thekkur, Pruthu, Lin, Zaw, Thi, Aung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921393/
https://www.ncbi.nlm.nih.gov/pubmed/31889888
http://dx.doi.org/10.1186/s41182-019-0184-3
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author Khine, San Kyawt
Kyaw, Nang Thu Thu
Thekkur, Pruthu
Lin, Zaw
Thi, Aung
author_facet Khine, San Kyawt
Kyaw, Nang Thu Thu
Thekkur, Pruthu
Lin, Zaw
Thi, Aung
author_sort Khine, San Kyawt
collection PubMed
description BACKGROUND: Myanmar has targeted elimination of malaria by 2030. In three targeted townships of Rakhine state of Myanmar, a project is being piloted to eliminate malaria by 2025. The comprehensive case investigation (CCI) and geotagging of cases by health workers is a core activity under the project. However, the CCI data is not analyzed for obtaining information on geospatial distribution of cases and timeliness of diagnosis. In this regard, we aimed to depict geospatial distribution and assess the proportion with delayed diagnosis among diagnosed malaria cases residing in three targeted townships during April 2018 to March 2019. METHODS: This was a cross sectional analysis of CCI data routinely collected by national malaria control programme. The geocode (latitude and longitude) of the address was analysed using Quantum Geographic Information System software to deduce spot maps and hotspots of cases. The EpiData analysis software was used to summarize the proportion with delay in diagnosis (diagnosed ≥24 hours after the fever onset). RESULTS: Of the 171 malaria cases diagnosed during study period, the CCI was conducted in 157 (92%) cases. Of them, 127 (81%) cases reported delay in diagnosis, 138 (88%) cases were indigenous who got infection within the township and 13 (8%) were imported from outside the township. Malaria hotspots were found along the foothills with increase in cases during the rainy season. The indigenous cases were concentrated over the foothills in the northern and southern borders of Toungup township. CONCLUSION: In the targeted townships for malaria elimination, the high proportion of the cases was indigenous and clustered at the foothill areas during rainy season. The programme should strengthen case surveillance and healthcare services in the areas with aggregation of cases to eliminate the malaria in the township. As high majority of patients have delayed diagnosis, the reasons for delay has to be explored and corrective measures needs to be taken.
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spelling pubmed-69213932019-12-30 Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination Khine, San Kyawt Kyaw, Nang Thu Thu Thekkur, Pruthu Lin, Zaw Thi, Aung Trop Med Health Research BACKGROUND: Myanmar has targeted elimination of malaria by 2030. In three targeted townships of Rakhine state of Myanmar, a project is being piloted to eliminate malaria by 2025. The comprehensive case investigation (CCI) and geotagging of cases by health workers is a core activity under the project. However, the CCI data is not analyzed for obtaining information on geospatial distribution of cases and timeliness of diagnosis. In this regard, we aimed to depict geospatial distribution and assess the proportion with delayed diagnosis among diagnosed malaria cases residing in three targeted townships during April 2018 to March 2019. METHODS: This was a cross sectional analysis of CCI data routinely collected by national malaria control programme. The geocode (latitude and longitude) of the address was analysed using Quantum Geographic Information System software to deduce spot maps and hotspots of cases. The EpiData analysis software was used to summarize the proportion with delay in diagnosis (diagnosed ≥24 hours after the fever onset). RESULTS: Of the 171 malaria cases diagnosed during study period, the CCI was conducted in 157 (92%) cases. Of them, 127 (81%) cases reported delay in diagnosis, 138 (88%) cases were indigenous who got infection within the township and 13 (8%) were imported from outside the township. Malaria hotspots were found along the foothills with increase in cases during the rainy season. The indigenous cases were concentrated over the foothills in the northern and southern borders of Toungup township. CONCLUSION: In the targeted townships for malaria elimination, the high proportion of the cases was indigenous and clustered at the foothill areas during rainy season. The programme should strengthen case surveillance and healthcare services in the areas with aggregation of cases to eliminate the malaria in the township. As high majority of patients have delayed diagnosis, the reasons for delay has to be explored and corrective measures needs to be taken. BioMed Central 2019-12-18 /pmc/articles/PMC6921393/ /pubmed/31889888 http://dx.doi.org/10.1186/s41182-019-0184-3 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Research
Khine, San Kyawt
Kyaw, Nang Thu Thu
Thekkur, Pruthu
Lin, Zaw
Thi, Aung
Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title_full Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title_fullStr Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title_full_unstemmed Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title_short Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
title_sort malaria hot spot along the foothills of rakhine state, myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921393/
https://www.ncbi.nlm.nih.gov/pubmed/31889888
http://dx.doi.org/10.1186/s41182-019-0184-3
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