Malaria Journal Volume 7
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 ResearchSpatial analysis of malaria in Anhui province, ChinaWenyi Zhang* 1 , Liping Wang* 2 , Liqun Fang* 1 , Jiaqi Ma2 , Youfu Xu1 , Jiafu Jiang1 , Fengming Hui1 , Jianjun Wang3 , Song Liang4 , Hong Yang1 and Wuchun Cao1  1Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing, PR China 2Center for Public Health Information, National Center for Disease Control and Prevention, Beijing, PR China 3Anhui Center for Disease Control and Prevention, Hefei, PR China 4College of Public Health, The Ohio State University, Columbus, Ohio, USA author email corresponding author email* Contributed equally
Malaria Journal 2008,
7:206doi:10.1186/1475-2875-7-206
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| Published: |
10 October 2008 |
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. |