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非药物干预措施、疫苗接种和 SARS-CoV-2 德尔塔变异株在英国:一项数学建模研究。

Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study.

机构信息

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK.

MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, UK; National Institute for Health Research Health Protection Research Unit in Modelling Methodology, Imperial College London, Public Health England, London School of Hygiene & Tropical Medicine, London, UK; Modelling and Economics Unit, National Infection Service, Public Health England, London, UK.

出版信息

Lancet. 2021 Nov 13;398(10313):1825-1835. doi: 10.1016/S0140-6736(21)02276-5. Epub 2021 Oct 28.

DOI:10.1016/S0140-6736(21)02276-5
PMID:34717829
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC8550916/
Abstract

BACKGROUND

England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories.

METHODS

This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions.

FINDINGS

The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness.

INTERPRETATION

Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures.

FUNDING

National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.

摘要

背景

随着疫苗接种的推进,英国 COVID-19 封锁政策路线图规定了逐步取消非药物干预(NPIs)的时间表和条件,第一阶段于 2021 年 3 月 8 日开始。本研究评估了路线图、SARS-CoV-2 德尔塔(B.1.617.2)变异株的影响以及潜在的未来流行轨迹。

方法

本数学建模研究旨在评估英国政府在英格兰放松封锁限制的四步过程。我们扩展了以前描述的 SARS-CoV-2 传播模型,纳入了疫苗接种和多株动力学,以明确捕捉到德尔塔变异株的出现。我们使用贝叶斯证据综合框架对模型进行了校准,该模型纳入了英国监测数据,包括住院人数、医院占用率、血清阳性率数据和人群水平的 PCR 检测数据,然后针对不同的 NPI 放松时间表对流行的潜在轨迹进行建模。我们估计了每日感染和住院人数、每日和累积死亡人数。研究了三种情况,涵盖了从乐观到悲观的疫苗有效性、自然免疫减弱和既往感染交叉保护的范围。我们还考虑了限制解除后的三种混合水平。

发现

路线图政策成功地抵消了 2021 年 3 月 8 日开始取消 NPIs 导致的传播增加,通过疫苗接种提高了人群免疫力。然而,由于德尔塔变异株的出现,其传播优势估计为 76%(95%可信区间[95%CrI]69-83),超过了阿尔法,因此按照原计划于 2021 年 6 月 21 日完全取消 NPIs,可能会导致我们的中心参数情景下每日住院人数达到 3900 人峰值(95%CrI 1500-5700)。推迟到 2021 年 7 月 19 日,每日住院人数减少三分之二至 1400 人(95%CrI 700-1700)。流行轨迹存在很大的不确定性,特别是对德尔塔的传染性、混合水平和疫苗有效性的估计非常敏感。

解释

我们的研究结果表明,如果 NPI 放松的时间与疫苗接种覆盖率仔细平衡,那么由于取消 NPIs 导致的 COVID-19 住院人数大幅增加的风险可以大大减轻。然而,即使疫苗接种覆盖率很高,由于德尔塔变异株的出现,也可能无法完全取消 NPIs 而不出现第三波住院和死亡人数。关注的变异株、其传染性、疫苗接种率和疫苗有效性必须作为国家放松大流行控制措施的一部分进行仔细监测。

资助

英国国家卫生研究院、英国医学研究理事会、惠康信托基金会和英国外交、联邦和发展办公室。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/d0aa8e3f4199/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/a55d39eea5ba/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/5db949d61c03/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/d0aa8e3f4199/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/a55d39eea5ba/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/5db949d61c03/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c070/8585670/d0aa8e3f4199/gr3.jpg

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