姚汶伶, 马蒙蒙, 刘艳慧, 景钦隆, 罗雷, 杨智聪. 移动流行区间法在广东省广州市冬夏两季流行性感冒流行阈值及强度分级中的应用[J]. 疾病监测, 2024, 39(2): 235-240. DOI: 10.3784/jbjc.202304110159
引用本文: 姚汶伶, 马蒙蒙, 刘艳慧, 景钦隆, 罗雷, 杨智聪. 移动流行区间法在广东省广州市冬夏两季流行性感冒流行阈值及强度分级中的应用[J]. 疾病监测, 2024, 39(2): 235-240. DOI: 10.3784/jbjc.202304110159
Yao Wenling, Ma Mengmeng, Liu Yanhui, Jing Qinlong, Luo Lei, Yang Zhicong. Application of moving epidemic method in establishing epidemic and intensity thresholds of influenza in winter and summer seasons in Guangzhou, Guangdong[J]. Disease Surveillance, 2024, 39(2): 235-240. DOI: 10.3784/jbjc.202304110159
Citation: Yao Wenling, Ma Mengmeng, Liu Yanhui, Jing Qinlong, Luo Lei, Yang Zhicong. Application of moving epidemic method in establishing epidemic and intensity thresholds of influenza in winter and summer seasons in Guangzhou, Guangdong[J]. Disease Surveillance, 2024, 39(2): 235-240. DOI: 10.3784/jbjc.202304110159

移动流行区间法在广东省广州市冬夏两季流行性感冒流行阈值及强度分级中的应用

Application of moving epidemic method in establishing epidemic and intensity thresholds of influenza in winter and summer seasons in Guangzhou, Guangdong

  • 摘要:
    目的  建立广东省广州市流行性感冒(流感)监测阈值,评估该市流感流行强度,为分级防控提供科学依据。
    方法  收集中国疾病预防控制信息系统中2014—2022年广州市每周流感报告病例数,利用移动流行区间法(MEM),分别纳入冬夏两季流行高峰为研究对象,选取约登指数最大时的δ值作为最优δ参数进行MEM模型拟合,估计冬夏两季流感流行阈值和分级强度阈值,应用交叉验证法进行拟合效果评价,并对2014—2022年流感流行水平进行评价。
    结果  广州市冬季流行开始阈值为1 178例,流行结束阈值为1 103例,中等、高等、极高的流行强度阈值分别为3 653、10 722、18 959例。 夏季流感流行开始阈值为652例,流行结束阈值为267例,中等、高等、极高的流行强度阈值分别为1 400、3 076、4 666例。 冬夏季两模型拟合的灵敏度和特异度均≥0.90。 2019年冬季和2022年夏季达到极高流行水平,2015年夏季、2016年夏季和2017冬季达到中流行水平,2014年夏季达到低流行水平,2021年全年基线流行水平。
    结论  本研究将MEM方法应用于广州市夏季与冬季的流感流行强度阈值建立,具有较高的灵敏度和特异度,可利用该模型为监测流感流行水平以及指导流感防控工作提供科学依据。

     

    Abstract:
    Objective To establish the monitoring threshold of influenza in Guangzhou, Guangdong province, evaluate the incidence intensity of influenza, and provide scientific basis for the prevention and control of influenza at different levels.
    Methods The weekly number of reported influenza cases in Guangzhou from 2014 to2022 were obtained from National Disease Prevention and Control Information System. By using moving epidemic method (MEM), the incidence peaks in winter and summer were used in the study. The δ value of the maximum Youden’s index was selected as the optimal δ parameter. MEM was applied to calculate the influenza epidemic and intensity thresholds and its effectiveness was evaluated by cross-validation method. The epidemic level of influenza from 2014 to 2022 was also evaluated.
    Results  For winter, the pre-epidemic threshold and post-epidemic threshold were 1178 cases and 1103 cases, and the medium, high and very high intensity thresholds were 3653 cases, 10722 cases and 18959 cases. For summer, the pre-epidemic threshold and post-epidemic threshold were 652 cases and 267 cases, and the medium, high and very high intensity thresholds were 1400 cases, 3076 cases and 4666 cases. Sensitivity and specificity of two models for summer and winter were ≥0.90. The incidence intensity reached very high level in winter in 2019 and summer in 2022, medium level in summer in 2015, summer in 2016 and winter in 2017, low level in summer in 2014, but remained baseline level all the year round in 2021.
    Conclusion MEM model used to establish the epidemic and intensity threshold of influenza in summer and winter in Guangzhou has good sensitivity and specificity. It can provide scientific evidence for the surveillance for incidence level of influenza and the prevention and control of influenza.

     

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