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目的 通过地理信息系统 (GIS)分析江苏、安徽、江西 3省血吸虫病疫情空间分布规律。 方法 收集 3省近 2 0年的血吸虫病流行病学数据 ,建立 GIS空间数据库。在 Arc View3.x,S- PL U S及 Spatial Statistics软件 (模块 )支持下对建立的血吸虫病 GIS数据库进行空间自相关性分析。 结果 安徽及江西省血吸虫病患者总数及钉螺总面积不同代表年份中 ,均具有不同程度的空间自相关性。总体上钉螺分布的相关系数 (Moran′I )大于患者的相关系数 ,并具有非常显著性差异。江苏省钉螺总面积具有一定的空间自相关性 ,其空间聚集性显著高于血吸虫病患者数 ,两者间缺乏空间聚集性。 结论 空间自相关分析可用于血吸虫病患者、钉螺分布的地域聚集性的研究 ,以揭示该病的分布规律和流行态势
Objective To analyze the distribution of schistosomiasis epidemic distribution in Jiangsu, Anhui and Jiangxi provinces by using geographic information system (GIS). Methods Epidemiological data of schistosomiasis collected in 3 provinces in recent 20 years were collected to establish GIS spatial database. Spatial autocorrelation analysis of the established schistosomiasis GIS database with Arc View 3.x, S-PLUS and Spatial Statistics software (modules). Results The total number of schistosomiasis patients and the total area of snails in Anhui and Jiangxi Province in different representative years all had different degrees of spatial autocorrelation. In general, the correlation coefficient (Moran’I) of snail distribution is greater than the correlation coefficient of patients, and has very significant difference. The total area of Oncomelania snails in Jiangsu Province has a certain degree of spatial autocorrelation, and its spatial aggregation is significantly higher than that of schistosomiasis patients, with a lack of spatial aggregation between the two. Conclusion Spatial autocorrelation analysis can be used to study schistosomiasis patients and snail distribution in order to reveal the distribution and prevalence of the disease