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      Demand for longer quarantine period among common and uncommon COVID-19 infections: a scoping review

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          Abstract

          Background

          As one of the non-pharmacological interventions to control the transmission of COVID-19, determining the quarantine duration is mainly based on the accurate estimates of the incubation period. However, patients with coarse information of the exposure date, as well as infections other than the symptomatic, were not taken into account in previously published studies. Thus, by using the statistical method dealing with the interval-censored data, we assessed the quarantine duration for both common and uncommon infections. The latter type includes the presymptomatic, the asymptomatic and the recurrent test positive patients.

          Methods

          As of 10 December 2020, information on cases have been collected from the English and Chinese databases, including Pubmed, Google scholar, CNKI (China National Knowledge Infrastructure) and Wanfang. Official websites and medias were also searched as data sources. All data were transformed into doubly interval-censored and the accelerated failure time model was applied. By estimating the incubation period and the time-to-event distribution of worldwide COVID-19 patients, we obtain the large percentiles for determining and suggesting the quarantine policies. For symptomatic and presymptomatic COVID-19 patients, the incubation time is the duration from exposure to symptom onset. For the asymptomatic, we substitute the date of first positive result of nucleic acid testing for that of symptom onset. Furthermore, the time from hospital discharge or getting negative test result to the positive recurrence has been calculated for recurrent positive patients.

          Results

          A total of 1920 laboratory confirmed COVID-19 cases were included. Among all uncommon infections, 34.1% ( n = 55) of them developed symptoms or were identified beyond fourteen days. Based on all collected cases, the 95th and 99th percentiles were estimated to be 16.2 days (95% CI 15.5–17.0) and 22.9 days (21.7‒24.3) respectively. Besides, we got similar estimates based on merely symptomatic and presymptomatic infections as 15.1 days (14.4‒15.7) and 21.1 days (20.0‒22.2).

          Conclusions

          There are a certain number of infected people who require longer quarantine duration. Our findings well support the current practice of the extended active monitoring. To further prevent possible transmissions induced and facilitated by such infectious outliers after the 14-days quarantine, properly prolonging the quarantine duration could be prudent for high-risk scenarios and in regions with insufficient test resources.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40249-021-00847-y.

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          Most cited references29

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          PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

          Scoping reviews, a type of knowledge synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. Although more scoping reviews are being done, their methodological and reporting quality need improvement. This document presents the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and explanation. The checklist was developed by a 24-member expert panel and 2 research leads following published guidance from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network. The final checklist contains 20 essential reporting items and 2 optional items. The authors provide a rationale and an example of good reporting for each item. The intent of the PRISMA-ScR is to help readers (including researchers, publishers, commissioners, policymakers, health care providers, guideline developers, and patients or consumers) develop a greater understanding of relevant terminology, core concepts, and key items to report for scoping reviews.
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            The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

            Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases. Primary Funding Source: U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.
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              The effect of human mobility and control measures on the COVID-19 epidemic in China

              The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
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                Author and article information

                Contributors
                tongwang@sxmu.edu.cn
                Journal
                Infect Dis Poverty
                Infect Dis Poverty
                Infectious Diseases of Poverty
                BioMed Central (London )
                2095-5162
                2049-9957
                26 April 2021
                26 April 2021
                2021
                : 10
                : 56
                Affiliations
                [1 ]GRID grid.263452.4, ISNI 0000 0004 1798 4018, Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, , Shanxi Medical University, ; 56 Xinjiannanlu Street, Yingze District, Taiyuan, 030001 Shanxi People’s Republic of China
                [2 ]Shanxi Provincial Center for Disease Control and Prevention, Taiyuan, 030001 People’s Republic of China
                [3 ]Shanxi Provincial Key Laboratory of Major Infectious Disease Pandemic Response, Taiyuan, 030001 People’s Republic of China
                [4 ]GRID grid.508381.7, ISNI 0000 0004 0647 272X, State Key Laboratory of Infectious Disease Prevention and Control, , National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, ; Beijing, 102206 People’s Republic of China
                [5 ]GRID grid.216938.7, ISNI 0000 0000 9878 7032, Institute of Public Health, , Nankai University, ; Tianjing, 300350 People’s Republic of China
                Author information
                http://orcid.org/0000-0002-9403-7167
                Article
                847
                10.1186/s40249-021-00847-y
                8072089
                33902695
                131a92a5-61a5-4f9a-99ec-0570f7734673
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 28 January 2021
                : 20 April 2021
                Funding
                Funded by: Shanxi health commission
                Award ID: No.6
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100013317, Shanxi Provincial Key Research and Development Project;
                Award ID: 202005D121008
                Award Recipient :
                Categories
                Scoping Review
                Custom metadata
                © The Author(s) 2021

                covid-19,quarantine duration,incubation period,asymptomatic infections,presymptomatic infection,recurrent positive

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