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目的探讨血吸虫病流行区钉螺感染率与气候因素之间的关系,为控制钉螺提供科学依据。方法收集2009年湖北省18个县(市、区)的螺情资料和气候因素资料,计算钉螺感染率和相关气候指标并拟合空间回归模型。结果多重线性回归分析结果显示,模型残差具有空间自相关性(Moran’s I=0.182 8,P<0.01),需拟合空间回归模型。根据空间依赖性检验结果,选择拟合空间滞后模型(SLM)。经检验,SLM模型拟合的空间回归系数有统计学意义(ρ=-0.151 5,P<0.05),拟合优度较好。SLM模型结果显示,钉螺感染率与年均温度呈正相关,且回归系数有统计学意义(P<0.05),与年均相对湿度、年均降雨量及年均日照时数无相关关系(P均>0.05)。结论空间回归分析在研究钉螺与气候因素的关系时分析效果较好。影响钉螺感染率的主要气候因素是年均温度。
Objective To investigate the relationship between snail infection and climatic factors in endemic areas of schistosomiasis so as to provide a scientific basis for controlling snails. Methods The data of snail and climatic factors in 18 counties (cities and districts) of Hubei Province in 2009 were collected to calculate the infection rates of snails and related climatic indices and fit the spatial regression model. Results Multiple linear regression analysis showed that the residuals of the model had spatial autocorrelation (Moran’s I = 0.182 8, P <0.01), and the spatial regression model was fitted. Based on the spatial dependence test result, the fitting space lag model (SLM) is chosen. After testing, SLM model fitting spatial regression coefficient was statistically significant (ρ = -0.151 5, P <0.05), better fitting goodness. The results of SLM showed that the infection rates of snails were positively correlated with the average annual temperature, and the regression coefficients were statistically significant (P <0.05), but not correlated with the annual average relative humidity, average annual rainfall and annual average sunshine duration > 0.05). Conclusion Spatial regression analysis is better in studying the relationship between snails and climatic factors. The main climatic factor affecting snail infection rate is the average annual temperature.