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SARS-CoV-2 的 Alpha、Delta 和奥密克戎变异株的替代动力学和发病机制。

Replacement dynamics and the pathogenesis of the Alpha, Delta and Omicron variants of SARS-CoV-2.

机构信息

UK Health Security Agency, London, UK.

The Flatiron Institute, Center for Computational Mathematics, New York, NY, USA.

出版信息

Epidemiol Infect. 2022 Dec 20;151:e32. doi: 10.1017/S0950268822001935.

DOI:10.1017/S0950268822001935
PMID:36535802
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9990386/
Abstract

New SARS-CoV-2 variants causing COVID-19 are a major risk to public health worldwide due to the potential for phenotypic change and increases in pathogenicity, transmissibility and/or vaccine escape. Recognising signatures of new variants in terms of replacing growth and severity are key to informing the public health response. To assess this, we aimed to investigate key time periods in the course of infection, hospitalisation and death, by variant. We linked datasets on contact tracing (Contact Tracing Advisory Service), testing (the Second-Generation Surveillance System) and hospitalisation (the Admitted Patient Care dataset) for the entire length of contact tracing in the England - from March 2020 to March 2022. We modelled, for England, time delay distributions using a Bayesian doubly interval censored modelling approach for the SARS-CoV-2 variants Alpha, Delta, Delta Plus (AY.4.2), Omicron BA.1 and Omicron BA.2. This was conducted for the incubation period, the time from infection to hospitalisation and hospitalisation to death. We further modelled the growth of novel variant replacement using a generalised additive model with a negative binomial error structure and the relationship between incubation period length and the risk of a fatality using a Bernoulli generalised linear model with a logit link. The mean incubation periods for each variant were: Alpha 4.19 (95% credible interval (CrI) 4.13-4.26) days; Delta 3.87 (95% CrI 3.82-3.93) days; Delta Plus 3.92 (95% CrI 3.87-3.98) days; Omicron BA.1 3.67 (95% CrI 3.61-3.72) days and Omicron BA.2 3.48 (95% CrI 3.43-3.53) days. The mean time from infection to hospitalisation was for Alpha 11.31 (95% CrI 11.20-11.41) days, Delta 10.36 (95% CrI 10.26-10.45) days and Omicron BA.1 11.54 (95% CrI 11.38-11.70) days. The mean time from hospitalisation to death was, for Alpha 14.31 (95% CrI 14.00-14.62) days; Delta 12.81 (95% CrI 12.62-13.00) days and Omicron BA.2 16.02 (95% CrI 15.46-16.60) days. The 95th percentile of the incubation periods were: Alpha 11.19 (95% CrI 10.92-11.48) days; Delta 9.97 (95% CrI 9.73-10.21) days; Delta Plus 9.99 (95% CrI 9.78-10.24) days; Omicron BA.1 9.45 (95% CrI 9.23-9.67) days and Omicron BA.2 8.83 (95% CrI 8.62-9.05) days. Shorter incubation periods were associated with greater fatality risk when adjusted for age, sex, variant, vaccination status, vaccination manufacturer and time since last dose with an odds ratio of 0.83 (95% confidence interval 0.82-0.83) ( value < 0.05). Variants of SARS-CoV-2 that have replaced previously dominant variants have had shorter incubation periods. Conversely co-existing variants have had very similar and non-distinct incubation period distributions. Shorter incubation periods reflect generation time advantage, with a reduction in the time to the peak infectious period, and may be a significant factor in novel variant replacing growth. Shorter times for admission to hospital and death were associated with variant severity - the most severe variant, Delta, led to significantly earlier hospitalisation, and death. These measures are likely important for future risk assessment of new variants, and their potential impact on population health.

摘要

新型 SARS-CoV-2 变种导致的 COVID-19 对全球公共卫生构成重大风险,因为它们可能会导致表型改变和增加致病性、传染性和/或疫苗逃逸的可能性。识别新变种在生长和严重程度方面的特征是为公共卫生应对提供信息的关键。为了评估这一点,我们旨在通过变种来研究感染、住院和死亡的关键时间段。我们将接触者追踪(接触者追踪咨询服务)、检测(第二代监测系统)和住院(住院患者护理数据集)的数据进行了链接,这些数据涵盖了英格兰接触追踪的整个时间段——从 2020 年 3 月到 2022 年 3 月。我们使用贝叶斯双重区间 censored 建模方法对 SARS-CoV-2 的 Alpha、Delta、Delta Plus (AY.4.2)、Omicron BA.1 和 Omicron BA.2 变种进行了时间延迟分布建模。这是针对潜伏期、从感染到住院和从住院到死亡的时间进行的。我们进一步使用具有负二项式误差结构的广义加性模型来建模新型变种的替代增长率,使用具有对数链接的伯努利广义线性模型来建模潜伏期长度与致死风险之间的关系。每个变种的平均潜伏期分别为:Alpha 4.19(95%可信区间(CrI)4.13-4.26)天;Delta 3.87(95% CrI 3.82-3.93)天;Delta Plus 3.92(95% CrI 3.87-3.98)天;Omicron BA.1 3.67(95% CrI 3.61-3.72)天和 Omicron BA.2 3.48(95% CrI 3.43-3.53)天。从感染到住院的平均时间分别为:Alpha 11.31(95% CrI 11.20-11.41)天,Delta 10.36(95% CrI 10.26-10.45)天和 Omicron BA.1 11.54(95% CrI 11.38-11.70)天。从住院到死亡的平均时间分别为:Alpha 14.31(95% CrI 14.00-14.62)天;Delta 12.81(95% CrI 12.62-13.00)天和 Omicron BA.2 16.02(95% CrI 15.46-16.60)天。潜伏期的第 95 个百分位数分别为:Alpha 11.19(95% CrI 10.92-11.48)天;Delta 9.97(95% CrI 9.73-10.21)天;Delta Plus 9.99(95% CrI 9.78-10.24)天;Omicron BA.1 9.45(95% CrI 9.23-9.67)天和 Omicron BA.2 8.83(95% CrI 8.62-9.05)天。当调整年龄、性别、变种、疫苗接种状态、疫苗制造商和最后一剂疫苗的时间后,较短的潜伏期与更高的致死风险相关,优势比为 0.83(95%置信区间 0.82-0.83)(<0.05)。取代以前占主导地位的变种的 SARS-CoV-2 变种潜伏期较短。相反,共存的变种潜伏期分布非常相似且没有区别。较短的潜伏期反映了代时优势,缩短了到达高峰传染期的时间,可能是新型变种生长的重要因素。住院和死亡的时间较短与变种的严重程度相关——最严重的变种 Delta 导致更早的住院和死亡。这些措施可能对未来新变种的风险评估及其对人群健康的潜在影响非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/9ef5d06757a8/S0950268822001935_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/21914db7aa9c/S0950268822001935_fig1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/d00a93de1e76/S0950268822001935_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/9ef5d06757a8/S0950268822001935_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/21914db7aa9c/S0950268822001935_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/ee7383a1ab46/S0950268822001935_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/c0986c32ea13/S0950268822001935_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2260/9990386/5ddf5c4b33c3/S0950268822001935_fig4.jpg
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