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量化佩戴口罩的预防效果。

Quantifying the preventive effect of wearing face masks.

作者信息

Britton Tom

机构信息

Department of Mathematics, Stockholm University, Stockholm, Sweden.

出版信息

Proc Math Phys Eng Sci. 2021 Jul;477(2251):20210151. doi: 10.1098/rspa.2021.0151. Epub 2021 Jul 7.

Abstract

An important task in combating the current Covid-19 pandemic lies in estimating the effect of different preventive measures. Here, we focus on the preventive effect of enforcing the use of face masks. Several publications study this effect, however, often using different measures such as: the relative attack rate in case-control studies, the effect on incidence growth/decline in a specific time frame and the effect on the number of infected in a given time frame. These measures all depend on community-specific features and are hence not easily transferred to other community settings. We argue that a more universal measure is the relative reduction in the reproduction number, which we call the , . It is shown how to convert the other measures to . We also apply the methodology to four empirical studies using different effect-measures. When converted to estimates of , all estimates lie between 15 and 40%, suggesting that mandatory face masks reduce the reproduction number by an amount in this range, when compared with no individuals wearing face masks.

摘要

抗击当前新冠疫情的一项重要任务在于评估不同预防措施的效果。在此,我们聚焦于强制使用口罩的预防效果。有若干出版物研究了这一效果,然而,它们常常采用不同的衡量指标,比如:病例对照研究中的相对发病率、特定时间段内对发病率增长/下降的影响以及给定时间段内对感染人数的影响。这些指标均取决于特定社区的特征,因此不易推广至其他社区环境。我们认为,一个更具通用性的指标是繁殖数的相对降低,我们将其称为 。文中展示了如何将其他指标转换为 。我们还将该方法应用于四项使用不同效果衡量指标的实证研究。当转换为 的估计值时,所有估计值都在15%至40%之间,这表明与无人佩戴口罩相比,强制佩戴口罩可使繁殖数降低这一范围内的数值。

相似文献

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Quantifying the preventive effect of wearing face masks.量化佩戴口罩的预防效果。
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本文引用的文献

1
Face masks considerably reduce COVID-19 cases in Germany.口罩大大减少了德国的 COVID-19 病例。
Proc Natl Acad Sci U S A. 2020 Dec 22;117(51):32293-32301. doi: 10.1073/pnas.2015954117. Epub 2020 Dec 3.
5
Fundamental protective mechanisms of face masks against droplet infections.口罩预防飞沫感染的基本保护机制。
J Aerosol Sci. 2020 Oct;148:105617. doi: 10.1016/j.jaerosci.2020.105617. Epub 2020 Jun 28.
7
Estimation in emerging epidemics: biases and remedies.新兴传染病中的估计:偏差及纠正。
J R Soc Interface. 2019 Jan 31;16(150):20180670. doi: 10.1098/rsif.2018.0670.

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