Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination
Abstract 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...
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doaj-95170dbc07c64034b38d6bd83cab46cc2020-12-20T12:20:35ZengBMCTropical Medicine and Health1349-41472019-12-0147111010.1186/s41182-019-0184-3Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria eliminationSan Kyawt Khine0Nang Thu Thu Kyaw1Pruthu Thekkur2Zaw Lin3Aung Thi4Vector Borne Diseases Control Programme, Ministry of Health and SportsInternational Union against Tuberculosis and Lung disease, Centre for Operational ResearchCentre for Operational Research, The Union South-East Asia OfficeVector Borne Diseases Control Programme, Ministry of Health and SportsVector Borne Diseases Control Programme, Ministry of Health and SportsAbstract 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.https://doi.org/10.1186/s41182-019-0184-3Malaria eliminationGeospatial distributionRakhine State |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
San Kyawt Khine Nang Thu Thu Kyaw Pruthu Thekkur Zaw Lin Aung Thi |
spellingShingle |
San Kyawt Khine Nang Thu Thu Kyaw Pruthu Thekkur Zaw Lin Aung Thi Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination Tropical Medicine and Health Malaria elimination Geospatial distribution Rakhine State |
author_facet |
San Kyawt Khine Nang Thu Thu Kyaw Pruthu Thekkur Zaw Lin Aung Thi |
author_sort |
San Kyawt Khine |
title |
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_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_sort |
malaria hot spot along the foothills of rakhine state, myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination |
publisher |
BMC |
series |
Tropical Medicine and Health |
issn |
1349-4147 |
publishDate |
2019-12-01 |
description |
Abstract 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. |
topic |
Malaria elimination Geospatial distribution Rakhine State |
url |
https://doi.org/10.1186/s41182-019-0184-3 |
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