2004 - 2020年我国肾综合征出血热的时空特征分析

Spatiotemporal characteristics of hemorrhagic fever with renal syndrome in China from 2004 to 2020

目的分析2004-2020年我国肾综合征出血热(HFRS)发病的时空特点及空间聚集性,为HFRS防控提供科学依据。方法自公共卫生科学数据中心、《中国卫生健康统计年鉴》、全国法定传染病疫情概况报告,收集2004-2020年我国HFRS的疫情信息,采用Joinpoint模型分析年均发病率变化趋势,使用ArcGIS 10.5软件进行空间可视化分析,并应用全局空间自相关、局部空间自相关和时空扫描分析对热点和聚集区域进行探测。结果2004-2020年我国累计报告HFRS病例208441例,年均发病率为0.91/10万。Joinpoint模型分析显示,2004-2020年我国HFRS年均发病率总体呈下降趋势。高发省份发病多呈春季、秋冬季双峰分布,其中秋冬季峰更为显著。全局空间自相关分析结果显示,2004-2019年我国HFRS发病率的全局莫兰指数(Moran′s I)均为正值,除2012和2020年不排除随机分布模式外,其他年份均呈现空间聚集性(均Z>1.65,均P<0.05);分阶段局部空间自相关分析结果表明,黑龙江省、吉林省、辽宁省为高-高聚集区域。逐月时空扫描分析共探测出5个聚集区域,每个聚集区域均有统计学意义(均P<0.001)。结论2004-2020年我国HFRS疫情总体呈下降趋势,发病率具有明显的空间聚集性,高风险地区仍持续存在,需重点关注并采取针对性的防控措施。

Objective To analyze the spatiotemporal characteristics and spatial aggregation of the incidence of hemorrhagic fever with renal syndrome(HFRS)in China from 2004 to 2020,and to provide a scientific basis for prevention and control of HFRS.Methods The epidemic information of HFRS in China from 2004 to 2020 was collected from the Public Health Science Data Center,the China Health Statistics Yearbook,and the National Statutory Infectious Disease Epidemic Profile Report.The Joinpoint model was used to analyze the annual average incidence rate change trend,ArcGIS 10.5 software was used for spatial visualization analysis,and global spatial autocorrelation,local spatial autocorrelation and spatiotemporal scan analysis were applied to detect hot spots and aggregation areas.Results From 2004 to 2020,a total of 208441 cases of HFRS were reported in China,with an average annual incidence rate of 0.91/100000.Joinpoint model analysis showed that the average annual incidence rate of HFRS in China showed a decreasing trend from 2004 to 2020.In the provinces with high incidence,the disease was mostly distributed with multimodal distribution in spring,autumn and winter,especially in autumn and winter.The results of global spatial autocorrelation analysis showed that the global Moran's I of HFRS incidence rate in China from 2004 to 2019 were all positive.Except 2012 and 2020,the random distribution pattern was not excluded,other years showed spatial clustering(Z>1.65,P<0.05).The results of phased local spatial autocorrelation analysis indicated that Heilongjiang,Jilin and Liaoning provinces were high-high aggregation regions.A total of five aggregation regions were detected in the month-by-month spatiotemporal scan analysis,and the differences of each aggregation region were statistically significant(P<0.001).Conclusions From 2004 to 2020,the overall incidence of HFRS in China shows a downward trend,and the incidence rate has obvious spatial aggregation.High-risk areas still exist,and it is necessary to focus on and take targeted prevention and control measures.