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静默传播对控制 COVID-19 疫情的影响。

The implications of silent transmission for the control of COVID-19 outbreaks.

机构信息

Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada.

Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510.

出版信息

Proc Natl Acad Sci U S A. 2020 Jul 28;117(30):17513-17515. doi: 10.1073/pnas.2008373117. Epub 2020 Jul 6.

Abstract

Since the emergence of coronavirus disease 2019 (COVID-19), unprecedented movement restrictions and social distancing measures have been implemented worldwide. The socioeconomic repercussions have fueled calls to lift these measures. In the absence of population-wide restrictions, isolation of infected individuals is key to curtailing transmission. However, the effectiveness of symptom-based isolation in preventing a resurgence depends on the extent of presymptomatic and asymptomatic transmission. We evaluate the contribution of presymptomatic and asymptomatic transmission based on recent individual-level data regarding infectiousness prior to symptom onset and the asymptomatic proportion among all infections. We found that the majority of incidences may be attributable to silent transmission from a combination of the presymptomatic stage and asymptomatic infections. Consequently, even if all symptomatic cases are isolated, a vast outbreak may nonetheless unfold. We further quantified the effect of isolating silent infections in addition to symptomatic cases, finding that over one-third of silent infections must be isolated to suppress a future outbreak below 1% of the population. Our results indicate that symptom-based isolation must be supplemented by rapid contact tracing and testing that identifies asymptomatic and presymptomatic cases, in order to safely lift current restrictions and minimize the risk of resurgence.

摘要

自 2019 年冠状病毒病(COVID-19)出现以来,全球范围内实施了前所未有的行动限制和社会距离措施。这些社会经济影响引发了取消这些措施的呼声。在没有全民限制的情况下,隔离感染者是遏制传播的关键。然而,基于症状的隔离在预防疫情复发方面的有效性取决于无症状和有症状传播的程度。我们根据最近关于发病前传染性和所有感染中无症状比例的个体水平数据,评估了无症状和有症状传播的贡献。我们发现,大多数病例可能是由于无症状感染和潜伏期感染的混合而导致的隐性传播。因此,即使所有有症状的病例都被隔离,仍可能爆发大规模疫情。我们进一步量化了除了隔离有症状病例之外,隔离隐性感染的效果,发现必须隔离超过三分之一的隐性感染,才能将未来的疫情爆发控制在人口的 1%以下。我们的研究结果表明,基于症状的隔离必须辅以快速的接触者追踪和检测,以识别无症状和有症状的病例,从而安全地取消当前的限制措施,并最大限度地降低疫情复发的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/952b/7395516/29af7ed08fd9/pnas.2008373117fig01.jpg

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