安徽省肾综合征出血热空间分布特征的研究

STUDIES ON THE SPATIAL PATTERN OF HEMORRHAGIC FEVER WITH RENAL SYNDROME (HFRS) IN ANHUI PROVINCE

本文利用R语言中DClsuster软件包作为工具对安徽省肾综合征出血热的空间分布特征及其影响因素进行了研究。文中所使用的数据包括：1994-1998年安徽省以县为单位的肾综合征出血热病例数、1999安徽省以县为单位的人口和1990年我国县级行政区划电子地图数据（1：1000 000）安徽省部分。结果发现卡方（P=0.594〉0.05）和Potthoff-Whittinghill（P=0.773〉0.05）检验病例数的空间分布符合负二项分布；空间自相关性检验（MoranI：P=0〈0.05，Gearyc：P=0.01〈0.05）具有显著差异；总体集聚性检验（Whittermore：P=0.003〈0.01，Tango：P=0.007〈0.01）差异显著；经验贝叶斯平滑（υ=0.3181535，α=0.389 820 5）的相对风险最高为9.52；Opgam、Kulldorff＆Nagarwalla和Besag＆Newell扫描统计分析发现2个局部集聚区。据此得出的初步结论：安徽省肾综合征出血热具有负二项分布的空间特征，存在自相关性和总体集聚性，相对风险呈北高南低趋势，扫描分析发现在北部的凤台县周围及南部的郎溪县周围存在明显的集聚性。

R and the DCluster package were exploited in the paper to evaluate the distribution and related factors of relative risks of Hemorrhagic Fever with Renal Syndrome （HFRS） in Anhui province by analyzing the spatial pattern of the disease. The data, based on county or the similar administrative unit of Anhui province, of reported case number of HFRS from 1994 to 1998, the population census of 1999 and the 1 ： 1 000 000 digital map of 1990 were used. The results showed that the hypothesis of the disease data coming from Negative Binomial distribution was supported by Chi-square Test （P = 0.594 〉 0.05） and Potthoff- Whittinghill＇s Test （ P = 0.773 〉 0.05）. The significantly spatial auto-correlation was found by Moran＇s I Statistic （ P = 0 〈 0.05） and Geary＇s c Statistic （ P = 0.01 〈 0.05）. The general clustering was detected by Whittermore＇s Statistic （ P = 0.003 〈 0.01 ） and Tango＇s Statistic （P = 0.007 〈 0.01 ）. The Empirical Bayesian Smoothed Relative Risks （EBSRR） were calculated for each regions with the estimated parameters u = 0.3181535 and a = 0.3898205. And the maximum of EBSRR is about 9.52. Two local clusters were showed by Opgam, Kulldorff ＆ Nagarwalla and Besag ＆ Newell Scan statistics. From details above, the primary conclusions could be drawn as follows： the spatial pattern of HFRS in Anhui province was characterized by Negative Binomial distribution, accompanied with the features of spatial autocorrelation and general clustering. The relative risks of the disease showed higher in north-west and lower in south-east in general. Two clusters were showed around Fengtai county and Langxi county.