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[Lancet Infect Dis发表论文]:隔离、检测、追踪密切接触者以及社交距离对限制新冠病毒在不同场合下传播的作用:数学模型研究
2020年11月21日 时讯速递, 进展交流 暂无评论

ARTICLES| VOLUME 20, ISSUE 10, P1151-1160, OCTOBER 01, 2020

Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study

Adam J Kucharski, Petra Klepac, Andrew J K Conlan, et al

Lancet Infect Dis 2020; 20: 1151-1160

Summary 摘要

Background 背景

The isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures—including novel digital tracing approaches and less intensive physical distancing—might be required to reduce transmission. We aimed to estimate the reduction in transmission under different control measures across settings and how many contacts would be quarantined per day in different strategies for a given level of symptomatic case incidence.

有症状病例的隔离和密切接触者的追踪在很多国家已经作为早期控制COVID-19的措施。而且,随着疫情爆发,也采取了额外的物理距离措施。为维持感染控制且减少对人群的影响,有必要了解联合采取哪些措施(包括新的数字追踪技术及较宽松的物理距离)能够减少传播。我们旨在评估不同场景下各种控制措施减少传播的作用,以及在一定的有症状病例发病率下,采用不同策略时每日需要隔离多少密切接触者。

Methods 方法

For this mathematical modelling study, we used a model of individual-level transmission stratified by setting (household, work, school, or other) based on BBC Pandemic data from 40 162 UK participants. We simulated the effect of a range of different testing, isolation, tracing, and physical distancing scenarios. Under optimistic but plausible assumptions, we estimated reduction in the effective reproduction number and the number of contacts that would be newly quarantined each day under different strategies.

在这项数学模型研究中,我们根据BBC源于40162名英国人的数据,采用了不同场景(家庭,工作单位,学校或其他)分层的个体水平传播模型。我们模拟了不同检测、隔离、追踪和物理距离场景下的效果。基于乐观且可信的假设,我们对不同策略下的有效再生数及每日需要隔离的密切接触者数目进行了估算。

Results 结果

We estimated that combined isolation and tracing strategies would reduce transmission more than mass testing or self-isolation alone: mean transmission reduction of 2% for mass random testing of 5% of the population each week, 29% for self-isolation alone of symptomatic cases within the household, 35% for self-isolation alone outside the household, 37% for self-isolation plus household quarantine, 64% for self-isolation and household quarantine with the addition of manual contact tracing of all contacts, 57% with the addition of manual tracing of acquaintances only, and 47% with the addition of app-based tracing only. If limits were placed on gatherings outside of home, school, or work, then manual contact tracing of acquaintances alone could have an effect on transmission reduction similar to that of detailed contact tracing. In a scenario where 1000 new symptomatic cases that met the definition to trigger contact tracing occurred per day, we estimated that, in most contact tracing strategies, 15 000–41 000 contacts would be newly quarantined each day.

我们估计,与单纯群体检测或自我隔离相比,联合隔离及追踪策略能够更有效地减少传播:每周群体随机检测5%的人群,平均传播减少2%,有症状病例在家中自我隔离减少传播29%,在家庭外自我隔离减少传播35%,自我隔离联合居家隔离减少传播37%,自我隔离及居家隔离联合对所有密切接触者手工追踪,减少传播64%,仅对熟人进行手工追踪减少传播57%,基于app的追踪减少传播47%。在限制户外、学校或工作场所的人群聚集的情况下,对熟人进行手工追踪减少传播的效果与更详细密切接触者追踪的效果相似。每日出现1000个新发有症状病例即开始密切接触者追踪的情况下,我们估算多数追踪策略要求每日新隔离15000-41000名密切接触者。

Interpretation 结论

Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimated that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number lower than 1 in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control of severe acute respiratory syndrome coronavirus 2 transmission.

与既往模型研究及各过COVID-19应对策略一致,我们的分析估计,在不采取其他措施的情况下,需要很大比例的病例进行自我隔离,并成功追踪很大比例的密切接触者,才能保证有效再生数低于1。如果联合中等程度的物理距离措施,自我隔离及密切接触者追踪能够更有效的控制疫情传播。

Funding 资助

Wellcome Trust, UK Engineering and Physical Sciences Research Council, European Commission, Royal Society, Medical Research Council.

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