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基于季节性分解在广州市2015 — 2022年流感季节性及病原变迁分析中的应用

姚汶伶 马蒙蒙 刘艳慧 殷尚晖 景钦隆 罗雷 杨智聪

姚汶伶, 马蒙蒙, 刘艳慧, 殷尚晖, 景钦隆, 罗雷, 杨智聪. 基于季节性分解在广州市2015 — 2022年流感季节性及病原变迁分析中的应用[J]. 中国公共卫生, 2023, 39(7): 823-829. doi: 10.11847/zgggws1141618
引用本文: 姚汶伶, 马蒙蒙, 刘艳慧, 殷尚晖, 景钦隆, 罗雷, 杨智聪. 基于季节性分解在广州市2015 — 2022年流感季节性及病原变迁分析中的应用[J]. 中国公共卫生, 2023, 39(7): 823-829. doi: 10.11847/zgggws1141618
YAO Wenling, MA Mengmeng, LIU Yanhui, YIN Shanghui, JING Qinlong, LUO Lei, YANG Zhicong. Seasonal characteristics and virus strain variation of influenza epidemics in Guangzhou city, 2015 – 2022: seasonal-trend decomposition-based analysis[J]. Chinese Journal of Public Health, 2023, 39(7): 823-829. doi: 10.11847/zgggws1141618
Citation: YAO Wenling, MA Mengmeng, LIU Yanhui, YIN Shanghui, JING Qinlong, LUO Lei, YANG Zhicong. Seasonal characteristics and virus strain variation of influenza epidemics in Guangzhou city, 2015 – 2022: seasonal-trend decomposition-based analysis[J]. Chinese Journal of Public Health, 2023, 39(7): 823-829. doi: 10.11847/zgggws1141618

基于季节性分解在广州市2015 — 2022年流感季节性及病原变迁分析中的应用

doi: 10.11847/zgggws1141618
基金项目: 广州市重点实验室基础研究计划(202102100001)
详细信息
    作者简介:

    姚汶伶(1997 – ),硕士在读,研究方向: 流行病学

    通信作者:

    罗雷,E-mail:llyeyq@163.com

    杨智聪,E-mail:yangzc@gzcdc.org.cn

Seasonal characteristics and virus strain variation of influenza epidemics in Guangzhou city, 2015 – 2022: seasonal-trend decomposition-based analysis

More Information
  • 摘要:   目的  分析广东省广州市流行性感冒(流感)病毒季节性流行特征和各病原型别的变迁规律,为制定适宜本地流行病学的防控措施提供依据。  方法   选取中国流感监测信息系统中2015 — 2022年广州市每周流感病原学监测数据,利用基于局部加权回归的季节性分解将流感病毒总阳性率及各型别阳性率序列分解成趋势分量、季节分量及剩余分量,通过计算协方差,分析所得分量序列对阳性率序列波动的贡献率。  结果  共检测样本39198份,流感病毒核酸阳性3632份,总体阳性率9.27%。趋势序列显示2015 — 2019年总阳性率呈轻微波动上升(4.57%~16.07%),2020 — 2022年经历“U”形低谷后趋水平。季节性序列显示流行高峰有冬春季和春夏季。剩余序列显示2022年剩余分量波动峰值达48.96%,较以往年份有明显增大。A(H3N2)型流行峰型与B(Victoria)型相似,可有冬季和夏季高峰,但夏季高峰晚于B(Victoria)型。A(H1N1) pdm09型与B(Yamagata)型峰型和流行时间相似,呈单峰流行,集中在冬春季。剩余成分是总阳性率波动的主要贡献因素,占59.16%(80.81/136.60),其次是季节成分和趋势成分,分别占25.19%(34.41/136.60)和15.65%(21.38/136.60)。  结论  流感季节性高峰和持续时间与流行的病原型别有关,不同亚型流感具有型别特异的流行特征和变化趋势。流感流行模式不仅受长期趋势和季节效应影响,随机波动效应起着更重要作用。
  • 图  1  2015 — 2022年广州市流感总阳性率季节性分解结果

    Figure  1.  Variation in influenza virus nucleic acid positivity among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022: seasonal decomposition analysis

    图  2  2015 — 2022年A(H1N1)pdm09型流感阳性率季节性分解结果

    Figure  2.  Variation in nucleic acid positivity for influenza virus A (H1N1) pdm09 among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022: seasonal deposition analysis

    图  5  2015 — 2022年B(Yamagata)型流感阳性率季节性分解结果

    Figure  5.  Variation in nucleic acid positivity for influenza virus B (Yamagata) among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022: seasonal deposition analysis

    图  3  2015 — 2022年A(H3N2)型流感阳性率季节性分解结果

    Figure  3.  Variation in nucleic acid positivity for influenza virus A (H3N2) among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022: seasonal deposition analysis

    图  4  2015 — 2022年B(Victoria)型流感阳性率季节性分解结果

    Figure  4.  Variation in nucleic acid positivity for influenza virus B (Victoria) among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022: seasonal deposition analysis

    表  1  2015 — 2022年广州市流感样病例病流感病毒核酸检测情况

    Table  1.   Year-specific nucleic acid positivity by influenza virus types among 39 198 influenza-like illness cases in Guangzhou city, 2015 – 2022

    年份检测数总阳性数总阳性率(%)病原型别
    A(H1N1)pdm09A(H3N2)B(Victoria)B(Yamagata)
    201535743088.62141105179
    2016355943312.172334412234
    2017477657312.001273673148
    2018522560311.54
    351

    4
    55193
    2019530080715.233891622560
    202066611762.645511740
    202148881152.35001150
    2022521561711.8304092080
    合计3919836329.2711691213796454
    下载: 导出CSV

    表  2  新冠疫情前后各分量对流感病毒总阳性率波动的贡献率

    Table  2.   Contribution of trend, seasonal and remaining component to overall fluctuation of influenza virus nucleic acid positivity among 39 198 influenza-like illness cases before and after COVID-19 epidemic in Guangzhou city

    年度原始序列Cov$({{Y}}_{{t}},{{Y}}_{{t}})$趋势分量季节分量剩余分量
    $\mathrm{C}\mathrm{o}\mathrm{v}({{T} }_{{t} },{{Y} }_{{t} })$%$\mathrm{C}\mathrm{o}\mathrm{v}\left({{S} }_{{t} },{{Y} }_{{t} }\right)$%$\mathrm{C}\mathrm{o}\mathrm{v}({{R} }_{{t} },{{Y} }_{{t} })$%
    2015 — 2019126.217.315.7940.7332.2778.1761.94
    202059.899.0715.1418.5130.9132.3153.95
    202121.239.8546.402.4611.588.9242.02
    2022261.202.440.9352.0419.92206.7279.14
    2015 — 2022136.6021.3815.6534.4125.1980.8159.16
    下载: 导出CSV
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  • 接收日期:  2023-02-28
  • 录用日期:  2023-05-05
  • 修回日期:  2023-03-17
  • 网络出版日期:  2023-07-17
  • 刊出日期:  2023-07-10

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