Spatial analysis of malaria in Anhui province, China
Abstract Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resou...
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ftdoajarticles:oai:doaj.org/article:ee3fbd31da9a4a3eab6fc06608eb5b72 2023-05-15T15:07:16+02:00 Spatial analysis of malaria in Anhui province, China Wang Jianjun Hui Fengming Jiang Jiafu Xu Youfu Ma Jiaqi Fang Liqun Wang Liping Zhang Wenyi Liang Song Yang Hong Cao Wuchun 2008-10-01T00:00:00Z https://doi.org/10.1186/1475-2875-7-206 https://doaj.org/article/ee3fbd31da9a4a3eab6fc06608eb5b72 EN eng BMC http://www.malariajournal.com/content/7/1/206 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-7-206 1475-2875 https://doaj.org/article/ee3fbd31da9a4a3eab6fc06608eb5b72 Malaria Journal, Vol 7, Iss 1, p 206 (2008) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2008 ftdoajarticles https://doi.org/10.1186/1475-2875-7-206 2022-12-30T23:05:22Z Abstract Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria ( P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 7 1 206 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Wang Jianjun Hui Fengming Jiang Jiafu Xu Youfu Ma Jiaqi Fang Liqun Wang Liping Zhang Wenyi Liang Song Yang Hong Cao Wuchun Spatial analysis of malaria in Anhui province, China |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background Malaria has re-emerged in Anhui Province, China, and this province was the most seriously affected by malaria during 2005–2006. It is necessary to understand the spatial distribution of malaria cases and to identify highly endemic areas for future public health planning and resource allocation in Anhui Province. Methods The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province. GIS-based spatial analyses were conducted to detect spatial distribution and clustering of malaria incidence at the county level. Results The spatial distribution of malaria cases in Anhui Province from 2000 to 2006 was mapped at the county level to show crude incidence, excess hazard and spatial smoothed incidence. Spatial cluster analysis suggested 10 and 24 counties were at increased risk for malaria ( P < 0.001) with the maximum spatial cluster sizes at < 50% and < 25% of the total population, respectively. Conclusion The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit malaria risks and to further identify environmental factors responsible for the re-emerged malaria risks. Future public health planning and resource allocation in Anhui Province should be focused on the maximum spatial cluster region. |
format |
Article in Journal/Newspaper |
author |
Wang Jianjun Hui Fengming Jiang Jiafu Xu Youfu Ma Jiaqi Fang Liqun Wang Liping Zhang Wenyi Liang Song Yang Hong Cao Wuchun |
author_facet |
Wang Jianjun Hui Fengming Jiang Jiafu Xu Youfu Ma Jiaqi Fang Liqun Wang Liping Zhang Wenyi Liang Song Yang Hong Cao Wuchun |
author_sort |
Wang Jianjun |
title |
Spatial analysis of malaria in Anhui province, China |
title_short |
Spatial analysis of malaria in Anhui province, China |
title_full |
Spatial analysis of malaria in Anhui province, China |
title_fullStr |
Spatial analysis of malaria in Anhui province, China |
title_full_unstemmed |
Spatial analysis of malaria in Anhui province, China |
title_sort |
spatial analysis of malaria in anhui province, china |
publisher |
BMC |
publishDate |
2008 |
url |
https://doi.org/10.1186/1475-2875-7-206 https://doaj.org/article/ee3fbd31da9a4a3eab6fc06608eb5b72 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 7, Iss 1, p 206 (2008) |
op_relation |
http://www.malariajournal.com/content/7/1/206 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-7-206 1475-2875 https://doaj.org/article/ee3fbd31da9a4a3eab6fc06608eb5b72 |
op_doi |
https://doi.org/10.1186/1475-2875-7-206 |
container_title |
Malaria Journal |
container_volume |
7 |
container_issue |
1 |
container_start_page |
206 |
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1766338808409751552 |