Evidence map›Paper›PMID 40082681›Full record

ArticleCommunications medicine2025

Age- and vaccination status-dependent isolation guidelines based on simulation of SARS-CoV-2 Delta cases in Singapore.

Keisuke Ejima, Marco Ajelli, Ananya Singh, Hoong Kai Chua, Luis Ponce, Yuqian Wang, Yong Dam Jeong, Shingo Iwami, Kenji Shibuya, Kiyosu Taniguchi and 6 more

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

16 authors.

Keisuke EjimaLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. keisuke.ejima@ntu.edu.sg.ORCID http://orcid.org/0000-0002-1185-3987
Marco AjelliLaboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
Ananya SinghLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0009-0003-9501-1721
Hoong Kai ChuaSchool of Biological Sciences, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0009-0000-2988-7766
Luis PonceLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.ORCID http://orcid.org/0000-0002-8102-1393
Yuqian WangLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Yong Dam JeongInterdisciplinary Biology Laboratory (iBLab), Division of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Japan.ORCID http://orcid.org/0000-0002-3970-7690
Shingo IwamiInterdisciplinary Biology Laboratory (iBLab), Division of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Japan.
Kenji ShibuyaThe Tokyo Foundation for Policy Research, Tokyo, Japan.
Kiyosu TaniguchiNational Mie Hospital, Mie, Japan.
Norio OhmagariDisease Control and Prevention Center, National Center for Global Health and Medicine Hospital, Tokyo, Japan.
Po Ying ChiaNational Centre for Infectious Diseases, Singapore, Singapore.ORCID http://orcid.org/0000-0002-8797-9527
Sean W X OngNational Centre for Infectious Diseases, Singapore, Singapore.
Kelvin Bryan TanLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
David Chien LyeLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Barnaby E YoungLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. barnaby_young@ncid.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the absence of effective pharmaceutical interventions early in an infectious disease outbreak, non-pharmaceutical measures, especially isolating infected individuals, critically limit its impact. The ongoing COVID-19 pandemic has sparked debates on optimal isolation guidelines. This study proposes a variable isolation period approach (variable-period approach), tailoring isolation durations for distinct population groups with varied viral load dynamics.

methodsTo compare our variable-period approach with a fixed-period strategy, we developed a simulation model generating synthetic longitudinal SARS-CoV-2 viral load data. The data was generated from the viral dynamics model parameterized using SARS-CoV-2 Delta patient data in Singapore, accounting for age and vaccination status.

resultsFindings show that age and vaccination status significantly influence viral dynamics, with younger age and vaccination linked to shorter viral shedding durations. The variable-period framework suggests longer isolation lengths for older and unvaccinated individuals. By setting the leaking risk (risk of remaining infectious at the end of isolation) below 10%, the optimal fixed-period isolation is 14 days, with an average excess isolation burden of 7.4 unnecessary days. In contrast, the variable-period guideline reduces the excess isolation burden to 6.0 days, with the optimal isolation periods ranging from 9 to 16 days, depending on the population group. We confirmed similar results when we used the effective reproduction number as an alternative to the leaking risk.

conclusionsIn this case, study using the SARS-CoV-2 Delta variant, our analysis demonstrates that unnecessary time spent in isolation can be reduced by adopting variable-period guidelines based on patient characteristics.

Identifiers

PMID40082681
PMCPMC11906760

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.