Evidence map›Paper›PMID 40559737›Full record

ArticleTropical medicine and infectious disease2025

Epidemiological Analysis of the COVID-19 Clusters in the Early Stages of the Epidemic in Shanghai, China: Pandemic-to-Epidemic Response Shift.

Dechuan Kong, Qiwen Fang, Jian Chen, Linjie Hu, Yihan Lu, Yaxu Zheng, Yiyi Zhu, Bihong Jin, Wenjia Xiao, Shenghua Mao and 9 more

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

19 authors.

Dechuan KongDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Qiwen FangDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Jian ChenDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Linjie HuDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.
Yihan LuDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.ORCID 0000-0003-4651-9433
Yaxu ZhengDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Yiyi ZhuDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Bihong JinDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Wenjia XiaoDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Shenghua MaoDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Chenyan JiangDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Xiaohuan GongDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Sheng LinDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Ruobing HanDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Xiao YuDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Qi QiuDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Xiaodong SunOffice of the Director, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Hao PanDepartment of Infectious Diseases Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Huanyu WuOffice of the Director, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As COVID-19 transitions from pandemic to endemic, our prevention and control policies have shifted from broad, strict community interventions to focusing on the prevention of cluster outbreaks. Currently, information on the characteristics of cluster outbreaks remains limited. This study describes the features of COVID-19 clusters in Shanghai. It aims to provide valuable insights for managing localized outbreaks. We conducted a retrospective analysis of clusters of confirmed COVID-19 cases. Epidemiological descriptions, the transmission characteristics of clusters, and individual risk factors for contagiousness were analyzed. A total of 381 cases of COVID-19 were confirmed and 67 clusters were identified. Most clusters (58.21%, 39/67) only had two cases, with a declining proportion held by clusters of more cases. Familial transmission was predominant, accounting for 79.10% (53/67) of clusters. Although other types of cluster outbreaks, such as those in workplaces (1.49%, 1/67), occur less frequently compared to household clusters, they tend to involve larger scales and more cases. Workplaces and similar venues are more likely to experience large-scale cluster outbreaks. Contagiousness was higher among cases with runny nose (risk ratio [RR]: 4.8, 95% CI: 1.40-16.44,

Indexed as

clustersCOVID-19epidemiologyoutbreaktransmission

Identifiers

PMID40559737
PMCPMC12197515

What Socratic 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 Socratic graph.