14天是COVID-19合理的隔离时间吗?以COVID-19潜伏期为例探讨相关问题。

IF 0.4 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Statistics in Biosciences Pub Date : 2022-01-01 Epub Date: 2021-09-09 DOI:10.1007/s12561-021-09320-8
Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He
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引用次数: 5

摘要

为了限制传染病的传播,设定合理的隔离时间至关重要。为此,必须充分了解疾病潜伏期的分布情况。对于正在发生的新冠肺炎大流行,为了平衡新冠病毒对公共卫生、经济、人文等社会各方面的影响,通常将14天作为隔离时间。然而,设定合理的隔离时间并非易事,它取决于各种潜在因素。在本文中,我们采用基于似然的方法来检查COVID-19潜伏期分布的角度。我们对2020年1月20日至2020年2月29日的178例COVID-19病例进行了研究,收集了暴露时间和症状出现日期的信息。为了更好地理解可能的情况,我们采用了不同的模型来描述COVID-19的潜伏期。我们的研究结果表明,从统计上看,14天的隔离时间可能不够长,不足以控制感染者提前释放的可能性很小。虽然研究数据的规模不足以为我们提供一个明确可接受的隔离时间,而且在实践中,决策者可能会考虑与社会和经济问题相关的其他因素来设定一个实际可接受的隔离时间,但我们的研究展示了从统计角度确定合理隔离时间的有用方法。此外,它揭示了一些相关的复杂性,以充分了解COVID-19的潜伏期分布。补充资料:在线版本提供补充资料,网址为10.1007/s12561-021-09320-8。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.

Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.

Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.

Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.

To confine the spread of an infectious disease, setting a sensible quarantine time is crucial. To this end, it is imperative to well understand the distribution of incubation times of the disease. Regarding the ongoing COVID-19 pandemic, 14-days is commonly taken as a quarantine time to curb the virus spread in balancing the impacts of COVID-19 on diverse aspects of the society, including public health, economy, and humanity perspectives, etc. However, setting a sensible quarantine time is not trivial and it depends on various underlying factors. In this article, we take an angle of examining the distribution of the COVID-19 incubation time using likelihood-based methods. Our study is carried out on a dataset of 178 COVID-19 cases dated from January 20, 2020 to February 29, 2020, with the information of exposure periods and dates of symptom onset collected. To gain a good understanding of possible scenarios, we employ different models to describe incubation times of COVID-19. Our findings suggest that statistically, the 14-day quarantine time may not be long enough to control the probability of an early release of infected individuals to be small. While the size of the study data is not large enough to offer us a definitely acceptable quarantine time, and further in practice, the decision-makers may take account of other factors related to social and economic concerns to set up a practically acceptable quarantine time, our study demonstrates useful methods to determine a reasonable quarantine time from a statistical standpoint. Further, it reveals some associated complexity for fully understanding the COVID-19 incubation time distribution.

Supplementary information: The online version contains supplementary material available at 10.1007/s12561-021-09320-8.

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来源期刊
Statistics in Biosciences
Statistics in Biosciences MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.00
自引率
0.00%
发文量
28
期刊介绍: Statistics in Biosciences (SIBS) is published three times a year in print and electronic form. It aims at development and application of statistical methods and their interface with other quantitative methods, such as computational and mathematical methods, in biological and life science, health science, and biopharmaceutical and biotechnological science. SIBS publishes scientific papers and review articles in four sections, with the first two sections as the primary sections. Original Articles publish novel statistical and quantitative methods in biosciences. The Bioscience Case Studies and Practice Articles publish papers that advance statistical practice in biosciences, such as case studies, innovative applications of existing methods that further understanding of subject-matter science, evaluation of existing methods and data sources. Review Articles publish papers that review an area of statistical and quantitative methodology, software, and data sources in biosciences. Commentaries provide perspectives of research topics or policy issues that are of current quantitative interest in biosciences, reactions to an article published in the journal, and scholarly essays. Substantive science is essential in motivating and demonstrating the methodological development and use for an article to be acceptable. Articles published in SIBS share the goal of promoting evidence-based real world practice and policy making through effective and timely interaction and communication of statisticians and quantitative researchers with subject-matter scientists in biosciences.
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