湖沼型血吸虫病流行区气候因素与钉螺分布的空间回归分析

Spatial regression analysis on climatic factors and snail distribution in marshland schistosomiasis transmission areas

目的探讨湖沼型血吸虫病流行区钉螺分布与气候因素之间的关系,为有效控制钉螺及预防钉螺扩散提供科学依据。方法收集2009年湖北省18个县(市、区)的螺情资料和相关气候因素资料。以活螺平均密度为因变量,以年平均温度、年均最低温度、年均相对湿度、年均降雨量、年均日照时数为自变量建立回归模型。运用空间回归模型分析气候因素与活螺平均密度的关系。结果空间回归模型分析中,根据Lagrange乘数检验统计量选择空间滞后模型(spatial lag model,SLM)进行拟合。SLM模型拟合的空间回归系数有统计学意义(ρ=-0.44,P<0.001)。结果表明,活螺平均密度与年平均温度和年均降雨量呈正相关,且回归系数均有统计学意义(均有P<0.001)。结论空间回归分析在研究具有空间自相关和异质性的钉螺数据与气候影响因素关系时,较经典线性回归分析效果好。影响活螺平均密度的主要气候因素是年平均温度和年均降雨量。

Objective To analyze the relationship between snail distribution and climate in marshland schistosomiasis endemic areas,and to provide scientific evidence to control the snail vectors. Methods Data of snail destribution and climatic factors of 18 counties in Hubei province in 2009 were collected. The average densities of living snails were used as response variables. The mean annual temperature,annual minimum temperature,annual relative humidity,annual rainfall,and annual sunshine hours were used as independent variables. The relationship between climatic factors and the average density of living snails was analyzed by spatial regression models. Results The spatial regression analysis was employed,and Lagrange multiplier statistic results suggested that the spatial lag model( SLM) should be employed. The spatial parameter ρ of SLM model was statistically significant( ρ =- 0. 44,P < 0. 001). The results showed that the average density of living snails was positively correlated with annual average temperature and rainfall( both P < 0. 001). Conclusions When comparied the relationship between the climate factors and snails data with spatial autocorrelation and heterogeneity,the results derived from spatial regression analysis are superior to those of classical linear regression analysis. The major climatic factors which affect live snail average density are annual average temperature and rainfall.