肾综合征出血热与气象因子相关性分析及其预报研究  

The Correlation Analysis Between Hemorrhagic Fever with Renal Syndrome(HFRS) and Meteorological Factors and Forcast of HFRS

作　　者：吴荣军[1] 胡晓抒[2] 郑有飞[1] 刘光中[2] 李亮[2] 

机构地区：[1]南京气象学院环境科学系,南京210044 [2]江苏省疾病预防控制中心

出　　处：《中国媒介生物学及控制杂志》2005年第2期118-120,共3页Chinese Journal of Vector Biology and Control

基　　金：江苏省卫生厅"135工程"医学重点学科流行病学项目;南京气象学院科研基金(Y307)联合资助

摘　　要：目的根据连云港赣榆县1990～2002年的气象资料及肾综合征出血热(HFRS)的发病情况,探讨气象因子对HFRS高发区发病率的影响及其相关性,并建立基于气象因子的HFRS发生的预测预报模型。方法用数据处理软件SAS的相关性分析工具和多重线性回归模型。结果以湿度(x1)、日照(x2)、降水(x3)、平均温度(x4)和最低气温(x6)等气象因子为自变量,HFRS发病率为因变量,采用强迫引入法和逐步回归法,分别建立回归方程,y=8.766+0.148x1+0.015x2-0.028x3-0.567x4(①),复相关系数(r)=0.45及y=1.742-0.054x6(②),复相关系数(r)=0.44,经t检验,呈显著相关。结论方程②可作为HFRS的预测预报模型,同时进行了区间估计,证实可行。Objective The paper analyzes the correlation between HFRS and meteorological factors, and establishes the regression model of incidence of HFRS, based on the incidence of HFRS and the meteorological data in Ganyu county, Lianyungang from 1990 to 2002. Methods Utilizing the correlation analysis and multiple regression model of SAS software. Results According to enter and stepwise regression methods, humidity(x_1), sunlight(x_2), precipitation(x_3), average temperature(x_4) and lowest temperature(x_6) on independent variables, incidence of disease of HFRS on dependent variable, regression equations were established, ~y= ~8.766+ ~0.148x_1+ ~0.015x_2- ~0.028x_3- ~0.567x_4 (①), multiple r is ~0.45 , and ~y= ~1.742- ~0.054x_6 (②), multiple r is ~0.44 . At the same time. Significant test indicates the correlation is significant. Conclusion Equation ② can be become the forcast model of HFRS, and interval estimate was utilized to test the model in this paper and feasibility was suggested simultaneously.

关 键 词：肾综合征出血热 气象因子 相关性分析 预报研究 多重线性回归模型 预测预报模型 复相关系数 数据处理软件 2002年 逐步回归法 发病情况 气象资料 分析工具 最低气温 平均温度 回归方程 区间估计 发病率 赣榆县 连云港 SAS 

分 类 号：Q78[生物学—分子生物学] O212[理学—概率论与数理统计]