中国(大陆地区)结核病动态监测大数据分析

Big data analysis of tuberculosis dynamic surveillance in China

目的探索结核病传播和扩散的动态流行规律。方法集成2005~2014年全国结核病报告病例个案数据,利用大数据分析技术,对病例的空间点分布进行核密度估计,采用局部空间统计方法进行统计学检验;应用R语言对病例的流动就诊情况进行分析。结果 2005~2014年报告病例空间聚集热点区域基本集中于我国东南部地区,东北及新疆维吾尔自治区等部分地区也存在一些高发热点区域。仍有部分病例流动就诊,且流动就诊病例所占比例逐年升高;流动就诊的流向在省内主要以省会城市为主,在省间主要以从中西部省份流向北京、广东、浙江、上海等东部一线发达省/市为主,以邻近省份居多。结论结核病的流行在空间上存在明显的聚集性高发热点区域,须加强防控干预,研究制订更具有针对性的防控策略;主要的病例流入地区,应重点加强对流动病例的监管,邻近地区需加强联防联控。

Objective To explore the dynamic epidemic rules of TB broadcast and spread. MethodsCollecting reported cases data of TB in China between 2005 and 2014 and analyzing with big data methods. To estimate kernel density of spatial point distribution of TB cases and then test with statistical method of local spatial autocorrelation. To describe cases flow situation of TB with R software. ResultsMost hotspots are in the southeast of China and several hotspots in northeast and Xin Jiang increased from 2005 to 2014. The direction of cases flow is mainly to provincial capital in province, and from midwestern china to eastern big cities between provinces. Cases flow is mostly among neighboring province. Conclusion Spatial hotspots regions should put forward specific prevention and control measures to resolve TB cluster problem. Monitoring and regulation of cases flow input regions have to be enforced, cooperation of neighboring areas should be promoted.