Research

Spatial analysis of malaria in Anhui province, China

Wenyi 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

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.