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从先前研究、广泛的检测和接触者追踪数据中构建和调整对 SARS-CoV-2 家庭传播的估计。

Constructing and adjusting estimates for household transmission of SARS-CoV-2 from prior studies, widespread-testing and contact-tracing data.

机构信息

Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, California, USA.

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Massachusetts, USA.

出版信息

Int J Epidemiol. 2021 Nov 10;50(5):1444-1457. doi: 10.1093/ije/dyab108.

Abstract

BACKGROUND

With reduced community mobility, household infections may become increasingly important in SARS-CoV-2 transmission dynamics.

METHODS

We investigate the intra-household transmission of COVID-19 through the secondary-attack rate (SAR) and household reproduction number (Rh). We estimate these using (i) data from 29 prior studies (February-August 2020), (ii) epidemiologically linked confirmed cases from Singapore (January-April 2020) and (iii) widespread-testing data from Vo' (February-March 2020). For (i), we use a Bayesian random-effects model that corrects for reverse transcription-polymerase chain reaction (RT-PCR) test sensitivity and asymptomatic cases. We investigate the robustness of Rh with respect to community transmission rates and mobility patterns.

RESULTS

The corrected pooled estimates from prior studies for SAR and Rh are 24% (20-28%) and 0.34 (0.30-0.38), respectively. Without corrections, the pooled estimates are: SAR = 18% (14-21%) and Rh = 0.28 (0.25-0.32). The corrected estimates line up with direct estimates from contact-tracing data from Singapore [Rh = 0.32 (0.22-0.42)] and population testing data from Vo' [SAR = 31% (28-34%) and Rh = 0.37 (0.34-0.40)]. The analysis of Singapore data further suggests that the value of Rh (0.22-0.42) is robust to community-spread dynamics; our estimate of Rh stays constant whereas the fraction of infections attributable to household transmission (Rh/Reff) is lowest during outbreaks (5-7%) and highest during lockdowns and periods of low community spread (25-30%).

CONCLUSIONS

The three data-source types yield broadly consistent estimates for SAR and Rh. Our study suggests that household infections are responsible for a large fraction of infections and so household transmission may be an effective target for intervention.

摘要

背景

随着社区流动性的降低,家庭内感染在 SARS-CoV-2 传播动力学中可能变得越来越重要。

方法

我们通过二次攻击率(SAR)和家庭繁殖数(Rh)来研究 COVID-19 的家庭内传播。我们使用以下方法进行估计:(i)来自 29 项先前研究的数据(2020 年 2 月至 8 月);(ii)来自新加坡的具有流行病学关联的确诊病例(2020 年 1 月至 4 月);以及(iii)Vo'的广泛检测数据(2020 年 2 月至 3 月)。对于(i),我们使用贝叶斯随机效应模型来校正逆转录-聚合酶链反应(RT-PCR)检测的灵敏度和无症状病例。我们研究了 Rh 对社区传播率和流动模式的稳健性。

结果

先前研究中校正后的 SAR 和 Rh 的汇总估计值分别为 24%(20-28%)和 0.34(0.30-0.38)。未经校正的汇总估计值分别为 SAR=18%(14-21%)和 Rh=0.28(0.25-0.32)。校正后的估计值与来自新加坡接触者追踪数据的直接估计值[Rh=0.32(0.22-0.42)]和 Vo'人口检测数据相吻合[SAR=31%(28-34%)和 Rh=0.37(0.34-0.40)]。对新加坡数据的进一步分析表明,Rh 的值(0.22-0.42)对社区传播动态具有稳健性;我们的 Rh 估计值保持不变,而家庭传播导致的感染比例(Rh/Reff)在疫情爆发时(5-7%)最低,在封锁和社区传播率低的时期(25-30%)最高。

结论

这三种数据源类型为 SAR 和 Rh 提供了大致一致的估计值。我们的研究表明,家庭内感染是导致大量感染的原因之一,因此家庭传播可能是干预的有效目标。

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本文引用的文献

1
Estimating the false-negative test probability of SARS-CoV-2 by RT-PCR.
Euro Surveill. 2020 Dec;25(50). doi: 10.2807/1560-7917.ES.2020.25.50.2000568.
2
Household Transmission of SARS-CoV-2: A Systematic Review and Meta-analysis.
JAMA Netw Open. 2020 Dec 1;3(12):e2031756. doi: 10.1001/jamanetworkopen.2020.31756.
3
Infection fatality rate of SARS-CoV2 in a super-spreading event in Germany.
Nat Commun. 2020 Nov 17;11(1):5829. doi: 10.1038/s41467-020-19509-y.
4
Epidemiology and transmission dynamics of COVID-19 in two Indian states.
Science. 2020 Nov 6;370(6517):691-697. doi: 10.1126/science.abd7672. Epub 2020 Sep 30.
5
Analysis of SARS-CoV-2 Transmission in Different Settings, Brunei.
Emerg Infect Dis. 2020 Nov;26(11):2598-2606. doi: 10.3201/eid2611.202263. Epub 2020 Oct 9.
8
Using a real-world network to model localized COVID-19 control strategies.
Nat Med. 2020 Oct;26(10):1616-1622. doi: 10.1038/s41591-020-1036-8. Epub 2020 Aug 7.
9
Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19.
Nat Hum Behav. 2020 Sep;4(9):964-971. doi: 10.1038/s41562-020-0931-9. Epub 2020 Aug 5.
10
[The role of children in the transmission of SARS-CoV-2].
Ned Tijdschr Geneeskd. 2020 Jun 3;164:D5140.

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