广州市登革热疫情时空扩散趋势探究 Study on the Spatiotemporal Diffusion Trend of Dengue Fever in Guangzhou

[目的]分析广州市登革热疫情时空扩散趋势，为防治提供依据。[方法]选择广州市7大核心区县为研究对象。以天为单位，对2014年上报的登革热病例进行整理。采用多项式拟合方法，对每个区县的登革热发展趋势进行趋势拟合，再利用1阶求导与2阶求导，分别获取该区县发展趋势中的转折点、突变点。最后采用Spearman相关性分析方法，分析登革热发展趋势中的影响因素及各关键趋势节点之间的相互关系。[创新]时间上以天为单位，对2014年的广州市每天的登革热病例数据进行整理；空间上精确定位每一例登革热病例，分析结果更准确；结合数学上的趋势拟合与导数分析方法，对登革热扩散趋势进行分析，能够探究登革热疫情的生命周期以及扩散规律。[结果]登革热的发展共经历偶然出现、初期发展、疫情爆发以及疫情消亡等四个阶段；登革热初期发展阶段的开始时刻、开始时刻数量、突变时刻、突变时刻数量、转折时刻、转折时刻数量彼此间存在显著相关性；人口密度对登革热总量有显著影响，二者间的相关性高达0.893。[结论]广州市登革热的扩散具有明显的季节性；登革热的传播具有区域性；登革热初期发展阶段开始时刻越早，爆发的破坏力越强；登革热与人口密度具备明显的相关关系。 [Objective] To analyze the spatiotemporal diffusion trend of Dengue Fever (DF) in Guangzhou, and guide scientific prevention and control measures. [Methods] Totally 7 districts of Guangzhou city were chosen and investigated. Daily reported cases of DF in 2014 were collected. Using polynomial fitting method, 1 order derivative and 2 derivative methods to fit the development trend of DF in each district, we obtain the turning-point, mutational-point of the curve trend of DF respectively. Finally, using Spearman correlation analysis method, we analyze the relationship between the population and DF diffusion trends. [Innovation] In order to obtain more accurate results, we not only collected daily DF cases data of Guangzhou city in 2014, but also accurately located each case of DF in space; combining with the trend fitting and derivative analysis methods, we analyze the diffusion trend, life cycle and diffusion rule of DF. [Results] DF’s development process has expe-rienced four stages: the occasional stage, the development stage, the epidemic stage and the dis-appearance stage; there is a correlation between the various stages of DF development; In Guang-zhou, the population density has a significant impact on DF, correlation coefficient has reached 0.893. [Conclusion] The diffusion trend of DF in Guangzhou city has obvious seasonal and regional; the development stage started earlier, the destructive force is much stronger; DF and population density have obvious correlation.