关键词: 血吸虫病；空间统计分析；GIS；热点区域；南昌县

Abstract:

istosome infection cases and population，the spatial analysis technology，global autocorrelation and hotspot detection methods in ArcGIS 9.2 software were used to render the spatial autocorrelation coefficient graph. The autocorrelation index change trend of schistosome infection rates in different spatial scales was described. In addition，the hotspot area of schistosome infection rates in study area was detected by using the representative distance for pace parameters combined with actual situation. Results The spatial distribution of schistosome infection in study area was characteristic of clusters in 2009. The spatial autocorrelation coefficient graph indicated that the peak of wave happened in the distances of 1 900 m，2 600 m，3 800 m and 5 000 m，respectively. Comparing with the geographical conditions，the hotspots in 5 000 m spatial scale were more realistic than other distances. In this scale，2 hotspots and 2 second hotspots were explored. Conclusion The spatial clustering analysis combined with the spatial autocorrelation analysis can explore the schistosomiasis gathering area more precisely.

Key words: Schistosomiasis；Spatial statistics analysis；GIS；Hotspot；Nanchang County