Limits...
Spatial analysis of malaria in Anhui province, China.

Zhang W, Wang L, Fang L, Ma J, Xu Y, Jiang J, Hui F, Wang J, Liang S, Yang H, Cao W - Malar. J. (2008)

Bottom Line: The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing, PR China. zwy0419@126.com

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.

Show MeSH

Related in: MedlinePlus

Spatial distribution of clusters of malaria with significant higher incidence using the maximum cluster size < 50% of the total population in Anhui province, China, 2000–2006.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2572066&req=5

Figure 4: Spatial distribution of clusters of malaria with significant higher incidence using the maximum cluster size < 50% of the total population in Anhui province, China, 2000–2006.

Mentions: Analysis of cases of malaria in 2000–2006 in Anhui Province showed that malaria was not distributed randomly. Using the maximum spatial cluster size of < 50% of the total population, the spatial cluster analysis identified a most likely cluster that included eight counties and two cities, which all located in the north of Huai River (Figure 4). The identified cluster contained 8.31% of the area's total population. The overall RR within the cluster was 39.75, with an observed number of cases of 43,182 compared with 2,443 expected cases. This elevated risk within a non-random pattern of disease distribution was significant (P < 0.001) (Table 1).


Spatial analysis of malaria in Anhui province, China.

Zhang W, Wang L, Fang L, Ma J, Xu Y, Jiang J, Hui F, Wang J, Liang S, Yang H, Cao W - Malar. J. (2008)

Spatial distribution of clusters of malaria with significant higher incidence using the maximum cluster size < 50% of the total population in Anhui province, China, 2000–2006.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2572066&req=5

Figure 4: Spatial distribution of clusters of malaria with significant higher incidence using the maximum cluster size < 50% of the total population in Anhui province, China, 2000–2006.
Mentions: Analysis of cases of malaria in 2000–2006 in Anhui Province showed that malaria was not distributed randomly. Using the maximum spatial cluster size of < 50% of the total population, the spatial cluster analysis identified a most likely cluster that included eight counties and two cities, which all located in the north of Huai River (Figure 4). The identified cluster contained 8.31% of the area's total population. The overall RR within the cluster was 39.75, with an observed number of cases of 43,182 compared with 2,443 expected cases. This elevated risk within a non-random pattern of disease distribution was significant (P < 0.001) (Table 1).

Bottom Line: The annual average incidence at the county level was calculated using malaria cases reported between 2000 and 2006 in Anhui Province.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing, PR China. zwy0419@126.com

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.

Show MeSH
Related in: MedlinePlus