Jiang Mingyue, Jia Mengmeng, Wang Qing, Sun Yanxia, Xu Yunshao, Dai Peixi, Yang Weizhong, Feng Luzhao
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Interact J Med Res. 2024 Oct 9;13:e47370. doi: 10.2196/47370.
There has been a global decrease in seasonal influenza activity since the onset of the COVID-19 pandemic.
We aimed to describe influenza activity during the 2021/2022 season and compare it to the trends from 2012 to 2023. We also explored the influence of social and public health prevention measures during the COVID-19 pandemic on influenza activity.
We obtained influenza data from January 1, 2012, to February 5, 2023, from publicly available platforms for China, the United States, and Australia. Mitigation measures were evaluated per the stringency index, a composite index with 9 measures. A general additive model was used to assess the stringency index and the influenza positivity rate correlation, and the deviance explained was calculated.
We used over 200,000 influenza surveillance data. Influenza activity remained low in the United States and Australia during the 2021/2022 season. However, it increased in the United States with a positive rate of 26.2% in the 49th week of 2022. During the 2021/2022 season, influenza activity significantly increased compared with the previous year in southern and northern China, with peak positivity rates of 28.1% and 35.1% in the second week of 2022, respectively. After the COVID-19 pandemic, the dominant influenza virus genotype in China was type B/Victoria, during the 2021/2022 season, and accounted for >98% (24,541/24,908 in the South and 20,543/20,634 in the North) of all cases. Influenza virus type B/Yamagata was not detected in all these areas after the COVID-19 pandemic. Several measures individually significantly influence local influenza activity, except for influenza type B in Australia. When combined with all the measures, the deviance explained values for influenza A and B were 87.4% (P<.05 for measures of close public transport and restrictions on international travel) and 77.6% in southern China and 83.4% (P<.05 for measures of school closing and close public transport) and 81.4% in northern China, respectively. In the United States, the association was relatively stronger, with deviance-explained values of 98.6% for influenza A and 99.1% (P<.05 for measures of restrictions on international travel and public information campaign) for influenza B. There were no discernible effects on influenza B activity in Australia between 2020 and 2022 due to the incredibly low positive rate of influenza B. Additionally, the deviance explained values were 95.8% (P<.05 for measures of restrictions on gathering size and restrictions on international travel) for influenza A and 72.7% for influenza B.
Influenza activity has increased gradually since 2021. Mitigation measures for COVID-19 showed correlations with influenza activity, mainly driven by the early stage of the pandemic. During late 2021 and 2022, the influence of mitigation management for COVID-19 seemingly decreased gradually, as the activity of influenza increased compared to the 2020/2021 season.
自新冠疫情爆发以来,全球季节性流感活动呈下降趋势。
我们旨在描述2021/2022年流感季的流感活动情况,并将其与2012年至2023年的趋势进行比较。我们还探讨了新冠疫情期间社会和公共卫生预防措施对流感活动的影响。
我们从中国、美国和澳大利亚的公开平台获取了2012年1月1日至2023年2月5日的流感数据。根据严格指数评估缓解措施,该指数是一个包含9项措施的综合指数。使用广义相加模型评估严格指数与流感阳性率的相关性,并计算可解释偏差。
我们使用了超过20万份流感监测数据。在2021/2022年流感季,美国和澳大利亚的流感活动仍然较低。然而,美国的流感活动有所增加,在2022年第49周阳性率达到26.2%。在2021/2022年流感季,中国南方和北方的流感活动与上一年相比显著增加,2022年第二周的峰值阳性率分别为28.1%和35.1%。新冠疫情后,2021/2022年流感季中国的主要流感病毒基因型为B/Victoria型,占所有病例的比例均超过98%(南方为24541/24908,北方为20543/20634)。新冠疫情后,所有这些地区均未检测到B/山形流感病毒。除澳大利亚的B型流感外,多项措施单独对当地流感活动有显著影响。当所有措施综合起来时,中国南方甲型和乙型流感的可解释偏差值分别为87.4%(公共交通封闭和国际旅行限制措施P<.05)和77.6%,北方分别为83.4%(学校关闭和公共交通封闭措施P<.05)和81.4%。在美国,这种关联相对更强,甲型流感的可解释偏差值为98.6%,乙型流感为99.1%(国际旅行限制和公共信息宣传措施P<.05)。2020年至2022年期间,由于B型流感的阳性率极低,澳大利亚对B型流感活动没有明显影响。此外,甲型流感的可解释偏差值为95.8%(聚集规模限制和国际旅行限制措施P<.05),乙型流感为72.7%。
自2021年以来,流感活动逐渐增加。新冠疫情的缓解措施与流感活动存在相关性,主要受疫情早期阶段驱动。在2021年末和2022年,与2020/2021年流感季相比,随着流感活动增加,新冠疫情缓解管理的影响似乎逐渐减弱。