Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He
{"title":"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。","authors":"Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He","doi":"10.1007/s12561-021-09320-8","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s12561-021-09320-8.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":" ","pages":"175-190"},"PeriodicalIF":0.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428508/pdf/","citationCount":"5","resultStr":"{\"title\":\"Is 14-Days a Sensible Quarantine Length for COVID-19? 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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. 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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.
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.