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目的:了解2016—2019年北京市通州区流感聚集性疫情的病原学特征、疫情规模及流行特征，为流感聚集性疫情防控工作提供科学依据。方法:收集2016—2019年北京市通州区报告的流感聚集性疫情资料，运用SPSS 23.0统计软件进行分析，应用Mapinfo 10.0空间分布软件绘制流感聚集性疫情地理分布图。结果:2016—2019年，北京市通州区共报告流感聚集性疫情296起，涉及病例3 273例，平均罹患率为26.05%。流感聚集性疫情主要发生在冬春季，中心城区的发生数量高于农村地区，发生疫情最多的场所为小学（194起，占65.54％），其次为托幼机构（74起，占25.00%）和中学（28起，占9.46%）。2016—2019年流感聚集性疫情检出的流感病毒型别不断变化，且不同场所发生的流感聚集性疫情的流感亚型不同（n x2=72.863，n P<0.01）。发生疫情的班级平均接种率为21.81%。疫情规模以5~15例病例为主（255起，占86.15%）。疫情发生至报告的时间间隔与疫情持续时间呈正相关（n r=0.296，n P<0.01），疫情持续时间与规模呈正相关（n r=0.528，n P<0.01）。n 结论:流感聚集性疫情具有明显的季节性。应加强对学校等聚集场所的流感疫情监测，尽早发现和报告疫情，以减少疫情的扩散传播。“,”Objective:To understand etiological features, scale of the epidemics and epidemiological characteristics of clustered influenza epidemics in Tongzhou district of Beijing from 2016 to 2019, so as to provide a scientific basis for effective prevention and control of the influenza epidemics.Methods:The data of clustered influenza epidemics reported in Tongzhou district of Beijing from 2016 to 2019 were collected. SPSS 23.0 statistical software was used for analysis. Mapinfo 10.0 spatial distribution software was used to draw the geographic distribution map of clustered influenza epidemics.Results:From 2016 to 2019, 296 clustered influenza epidemics were reported in Tongzhou district of Beijing, involving 3 273 cases, with an average attack rate of 26.05%. Clustered influenza epidemics occurred mainly in winter and spring and the number of epidemics in the central urban area was higher than that in rural areas. The places with the most epidemics were primary schools (194 epidemics, accounting for 65.54%), followed by childcare institutions (74 epidemics, accounting for 25.00%) and secondary schools (28 epidemics, accounting for 9.46%). The subtypes of influenza virus detected in the clustered influenza epidemics from 2016 to 2019 changed constantly, and the dominant subtypes from the epidemics occurred in different locations were different (n x2=72.863, n P<0.01). The average vaccination rate of the school classes attacked by the epidemics was 21.81%. The scales of the epidemics ranged mainly 5-15 cases (255 epidemics, accounting for 86.15%). The time intervals between the start of epidemics and the reports were positively correlated with the duration of the epidemics (n r = 0.296, n P<0.01). The duration of the epidemics was positively correlated with the scale (n r = 0.528, n P<0.01).n Conclusions:The influenza epidemic showed obvious seasonality. Surveillance of influenza epidemics in schools should be enhanced for early detection and report of epidemics, so as to reduce the spreading of epidemics.