2015—2020年贵州省肺结核时空分布特征分析

目的 分析2015—2020年贵州省肺结核发病的时空分布和聚集情况，为进一步优化贵州省结核病防控策略提供科学依据。方法 基于中国疾病预防控制信息系统传染病报告系统中贵州省88个县（区）2015—2020年肺结核发病数、发病率和常住人口资料，在ArcGIS软件中与贵州省矢量化电子地图关联，建立贵州省肺结核发病率地理信息数据库，然后进行全局和局部自相关分析，再采用SaTScan进行时空扫描分析。结果 2015—2020年贵州省肺结核报告发病率以年均5.53%的速率下降，差异具有统计学意义（趋势χ2 = 3 369.487，P＜0.05）；年均发病率为114.41/10万，88个县区年均发病率为54.47/10万～254.83/10万。2018—2020年贵州省肺结核发病整体呈空间聚集性，Moran’s I指数分别为0.163、0.289和0.294（P＜0.05）。2015—2020年“高-高”聚集区主要集中在黔西南部，呈现向中西部扩展的趋势；同时“低-低”聚集区整体呈现增加趋势。时空扫描结果发现，2015—2020年肺结核一级可能聚集区发生以望谟为中心的西南部等地，二级聚集区主要集中在以汇川为中心的北部地区。结论 2015—2020年贵州省肺结核报告发病率明显下降，近年全省整体存在时空聚集性，聚集区主要集中在望谟等地的西南部，呈现向中西部扩展的趋势，防控工作应统筹兼顾，重视聚集区同时加强巩固非聚集区防控工作。

Spatial and temporal distribution characteristics of pulmonary tuberculosis in Guizhou Province from 2015 to 2020

To analyze the temporal, spatial distribution and aggregation of tuberculosis incidence in GuizhouProvince from 2015 to 2020, so as to provide scientific basis for further optimization and adjustment of tuberculosis prevention and control strategy. Methods Based on the number of tuberculosis incidence, incidence rate and resident population information of 88 counties (districts) in Guizhou Province from 2015-2020 in the Infectious Disease Reporting System of theChinese Disease Prevention and Control Information System, the data were correlated with the vectorized electronic maps ofGuizhou Province in ArcGIS software to establish a geographic information database of tuberculosis incidence in GuizhouProvince. Global and local autocorrelation analysis was performed, and SaTScan was used for spatial and temporal scan analysis. Results The reported incidence rate of TB in Guizhou Province decreased at an average annual rate of 5.53% from 2015to 2020, with statistically significant differences (trend χ2=3 369.487, P<0.05); the average annual incidence rate was 114.41/100 000, and the average annual incidence rate in 88 counties ranged from 54.47/100 000 to 254.83/100 000. In 2018-2020, There was overall spatial clustering of TB incidence in Guizhou Province, with Moran’s I indexes of 0.163, 0.289 and0.294, respectively (P<0.05). From 2015 to 2020, the “high-high” agglomeration area was mainly concentrated in the southof Qianxi, showing a trend of expansion to the central and west; meanwhile, the “low-low” agglomeration area showed anoverall increasing trend. The results of the spatial and temporal scans showed that the primary aggregation area of tuberculosis in 2015-2020 was mainly in the southwestern part of Wangmu, and the secondary aggregation area was mainly in thenorthern part of Huichuan. Conclusion The reported incidence of pulmonary tuberculosis in Guizhou province decreased significantly from 2015 to 2020, and there was overall spatio-temporal aggregation existed in recent years, with the aggregationareas mainly concentrated in the southwestern part of Wangmu and other places, showing a trend of expansion to the centraland western parts of the province. The prevention and control should be integrated, with special attention to the aggregationareas while consolidating of the prevention and control in the non-aggregation areas