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SARS-CoV-2 的病毒传播性在冬季加速,类似于流感疫情。

Viral transmissibility of SARS-CoV-2 accelerates in the winter, similarly to influenza epidemics.

机构信息

Graduate School of Medicine, Kyoto University, Kyoto, Japan; Department of Environmental Medicine and Behavioral Science, Faculty of Medicine, Kindai University.

Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan.

出版信息

Am J Infect Control. 2022 Sep;50(9):1070-1076. doi: 10.1016/j.ajic.2022.05.009. Epub 2022 May 20.

Abstract

The transmissibility of SARS-CoV-2 is anticipated to increase in the winter because of increased viral survival in cold damp air and thus would exacerbate viral spread in community. Analysis to capture the seasonal trend is needed to be prepared for future epidemics. We compared regression models for the 5-week case prior to each epidemic peak week for both the COVID-19 and influenza epidemics in winter and summer. The weekly case increase ratio was compared, using non-paired t tests between seasons. In order to test the robustness of seasonal transmission patterns, the normalized weekly case numbers of COVID-19 and influenza case rates of all seasons were assessed in a combined quadratic regression analysis. In winter, the weekly case increase ratio accelerated before epidemic peaks, similarly, for both COVID-19 and influenza. The quadratic regression models of weekly cases were observed to be convex curves in the winter and concave curves in the spring/summer for both COVID-19 and influenza. A significant increase of case increase ratio (3.19 [95%CI:0.01-6.37, P = .049]) of the COVID-19 and influenza epidemics was observed in winter as compared to spring/summer before the epidemic peak. The epidemic of COVID-19 was found to mirror that of influenza, suggesting a strong underlying seasonal transmissibility. Influenza epidemics can potentially be a useful reference for the COVID-19 epidemics.

摘要

预计 SARS-CoV-2 的传染性会在冬季增加,因为病毒在寒冷潮湿的空气中更易存活,从而加剧社区中的病毒传播。为了应对未来的疫情,需要对季节性趋势进行分析。我们比较了 COVID-19 和流感在冬季和夏季每个疫情高峰期前 5 周的病例回归模型。使用非配对 t 检验比较了季节之间的每周病例增长率。为了检验季节性传播模式的稳健性,我们还评估了 COVID-19 和流感所有季节的归一化每周病例数的二次回归分析。在冬季,疫情高峰前的每周病例增长率加快,COVID-19 和流感的情况类似。对于 COVID-19 和流感,冬季的每周病例二次回归模型呈凸曲线,而春季/夏季呈凹曲线。与春季/夏季相比,COVID-19 和流感的疫情高峰前冬季的病例增长率显著增加(3.19 [95%CI:0.01-6.37,P =.049])。COVID-19 的流行情况与流感相似,表明其具有很强的季节性传播基础。流感疫情可能是 COVID-19 疫情的一个有用参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5197/9121648/dccca73c971a/gr1_lrg.jpg

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