Evidence map›Paper›PMID 33902695›Full record

ArticleInfectious diseases of poverty2021

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

Zhi-Yao Li, Yu Zhang, Liu-Qing Peng, Rong-Rong Gao, Jia-Rui Jing, Jia-Le Wang, Bin-Zhi Ren, Jian-Guo Xu, Tong Wang

Abstract readScoping Review
In one paragraph

Article in Infectious diseases of poverty, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. COVID-19 Infection in Academic Dental Hospital Personnel; A Cross-Sectional Survey in Saudi Arabia.International journal of environmental research and public health · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zhi-Yao LiDepartment 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.
Yu ZhangDepartment 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.
Liu-Qing PengDepartment 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.
Rong-Rong GaoDepartment 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.
Jia-Rui JingDepartment 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.
Jia-Le WangDepartment 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.
Bin-Zhi RenShanxi Provincial Center for Disease Control and Prevention, Taiyuan, 030001, People's Republic of China.
Jian-Guo XuState 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.
Tong WangDepartment 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. tongwang@sxmu.edu.cn.ORCID http://orcid.org/0000-0002-9403-7167

Funding

Shanxi health commission No.6Shanxi Provincial Key Research and Development Project 202005D121008
6 · The paper itself

Abstract

backgroundAs 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.

methodsAs 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.

resultsA 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).

conclusionsThere 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.

Indexed as

AdolescentAdultAgedAsymptomatic DiseasesAsymptomatic InfectionsCarrier StateChildChild, PreschoolCOVID-19FemaleHumansInfantInfant, NewbornInfectious Disease Incubation PeriodMaleMiddle AgedAsymptomatic infectionsCOVID-19Incubation periodPresymptomatic infectionQuarantine durationRecurrent positive

Identifiers

PMID33902695
PMCPMC8072089

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.