王超, 高燕琳, 史芸萍, 刘洋, 虎霄, 谢春艳, 周滢, 李伟, 李刚. 2017-2020年北京市流行性感冒多次感染病例特征分析[J]. 疾病监测, 2022, 37(5): 598-602. DOI: 10.3784/jbjc.202108230462
引用本文: 王超, 高燕琳, 史芸萍, 刘洋, 虎霄, 谢春艳, 周滢, 李伟, 李刚. 2017-2020年北京市流行性感冒多次感染病例特征分析[J]. 疾病监测, 2022, 37(5): 598-602. DOI: 10.3784/jbjc.202108230462
Wang Chao, Gao Yanlin, Shi Yunping, Liu Yang, Hu Xiao, Xie Chunyan, Zhou Ying, Li Wei, Li Gang. Characteristics of multiple infections of influenza in Beijing during 2017–2020 influenza seasons[J]. Disease Surveillance, 2022, 37(5): 598-602. DOI: 10.3784/jbjc.202108230462
Citation: Wang Chao, Gao Yanlin, Shi Yunping, Liu Yang, Hu Xiao, Xie Chunyan, Zhou Ying, Li Wei, Li Gang. Characteristics of multiple infections of influenza in Beijing during 2017–2020 influenza seasons[J]. Disease Surveillance, 2022, 37(5): 598-602. DOI: 10.3784/jbjc.202108230462

2017-2020年北京市流行性感冒多次感染病例特征分析

Characteristics of multiple infections of influenza in Beijing during 2017–2020 influenza seasons

  • 摘要:
      目的  了解北京市2017—2020年流行性感冒(流感)病例中多次感染者所占比例及其特征。
      方法  使用北京市2017—2020年的流感监测数据分析研究期间及各流感季多次感染病例的构成及三间分布情况。
      结果  2017—2020流感季北京市共有18637例流感病例为多次感染的流感病例(占病例数的4.13%),单个流感季中多次感染者所占比例在0.10%~0.93%之间。 多次感染病例的变化趋势与流感总报告病例数的变化一致。 在初次感染的第120天、第285天、第375天、第450天和第725天出现5个再次感染的高峰。 单因素分析发现性别、年龄、职业(人群分类)和各行政区的人群之间出现多次感染的比例存在统计学差异,其中男性,12岁及以下,幼托儿童、散居儿童、医务人员和学生,朝阳区、海淀区、昌平区、西城区和通州区出现多次感染的比例较高。
      结论  北京市流感报告病例中多次感染的病例占比较高,且不同时间、地区和人群多次感染的情况存在较大差异。

     

    Abstract:
      Objective  To analyze the proportion and epidemiological characteristics of multiple infections of influenza in Beijing during 2017−2020 influenza seasons.
      Methods  The composition and distribution of multiple infection cases were analyzed by using the surveillance data of influenza in Beijing from 2017 to 2020.
      Results  During 2017−2020 influenza seasons, 18637 multiple infections were reported (accounting for 4.13%), and the proportion of multiple infections in a single influenza season ranged from 0.10% to 0.93%. The trend of multiple infection cases was consistent with the change of the total number of influenza. There were five peaks of reinfection on the 120th, 285th,375th,450th and 725th day since the first infection. Univariate analysis found that there were significant differences in the proportion of multiple infections among gender, age groups, occupation and living districts. And the proportion of multiple infections was higher in male, 12 years old and below, nursery children, scattered children, healthcare providers and students, Chaoyang, Haidian, Changping, Xicheng and Tongzhou districts.
      Conclusion  There were many multiple influenza infections in Beijing, and great differences in multiple infections could be found at different times, regions and populations.

     

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