目的 探究社会经济与自然环境要素对登革热疫情空间分布的影响，为有效防控登革热提供依据。方法 以蚊媒监测点周围0.5～6.0 km范围内的土地利用、人口密度和道路密度等社会环境要素作为土地利用回归（LUR）模型的输入变量，分析广州市社会经济因素对登革热疫情空间分布的影响。采用留一交叉检验法对模型进行检验，即用n－1个样本建立回归方程，计算剩余1个样本的预测值，并与该样本的实测病例数进行比较。结果 监测点不同范围内的社会环境变量对登革热疫情空间分布的贡献程度存在差异，半径为6、2、1、1和2 km缓冲区内的人口密度、道路密度、耕地、林地和农村居民用地的面积分别对登革热1 km有明显影响（R2=0.567、0.512、0.275、0.106和0.041），而整体LUR模型调整R2为0.648（F=55.944，P < 0.01），预测值与实测值间的拟合精度达0.728 8，总体水平较好。结论 社会经济要素在不同研究范围下对登革热疫情空间分布的影响不同，LUR模型可较好地预测登革热病例空间分布，从而为当地卫生部门防控登革热提供方法支持。
Objective Exploring the influence of socioeconomic factors and environmental conditions on the spatial distribution of dengue fever epidemic is an important basis for effective prevention and control of dengue fever. Methods Predictive variables, included land use data, road density and population density, were involved in modeling within different buffer zone ranges from 0.5 km to 6.0 km, which were established and verified on 150 mosquito monitoring sites. The effects of social and economic factors on the distribution of dengue fever in Guangzhou area were analyzed. Results The results found that dengue fever was significantly correlated with human population density (R2=0.567), road density (R2=0.512), farmland area (R2=0.275), forest area (R2=0.106), and village area (R2=0.041)within the buffer zones of 6, 2, 1, 1, and 2 km. The land use regression (LUR)model with these five variables possessed satisfactory capability of predicting the spatial distribution of dengue fever with the adjusted R2 (0.648)and an appropriate F value 55.944 (P < 0.01). The overall result of the model is good with the fitting accuracy between the predicted value and the measured value (0.728 8). Conclusion The socioeconomic factors have different effects on the spatial distribution of dengue fever epidemics in different ranges. LUR has good ability to predict the spatial distribution of dengue fever and provide an effective method for local public health authorities to allocate precise preventing and control measures.
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