Evidence map›Paper›PMID 35279413›Full record

ArticleVirologica Sinica2022

Characteristics of SARS-CoV-2 transmission in a medium-sized city with traditional communities during the early COVID-19 epidemic in China.

Yang Li, Hao-Rui Si, Yan Zhu, Nan Xie, Bei Li, Xiang-Ping Zhang, Jun-Feng Han, Hong-Hong Bao, Yong Yang, Kai Zhao and 5 more

Abstract read
In one paragraph

Article in Virologica Sinica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

15 authors.

Yang LiCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China; Anyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China; University of Chinese Academy of Sciences, Beijing, 101409, China.
Hao-Rui SiCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China; University of Chinese Academy of Sciences, Beijing, 101409, China.
Yan ZhuCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China.
Nan XieAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Bei LiCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China.
Xiang-Ping ZhangAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Jun-Feng HanAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Hong-Hong BaoAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Yong YangCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China; University of Chinese Academy of Sciences, Beijing, 101409, China.
Kai ZhaoCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China; University of Chinese Academy of Sciences, Beijing, 101409, China.
Zi-Yuan HouAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Si-Jia ChengAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China.
Shuan-Hu ZhangAnyang Municipal Center for Disease Control and Prevention, Anyang, 455000, China. Electronic address: ayzshlx@163.com.
Zheng-Li ShiCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China. Electronic address: zlshi@wh.iov.cn.
Peng ZhouCAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China. Electronic address: peng.zhou@wh.iov.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The nationwide COVID-19 epidemic ended in 2020, a few months after its outbreak in Wuhan, China at the end of 2019. Most COVID-19 cases occurred in Hubei Province, with a few local outbreaks in other provinces of China. A few studies have reported the early SARS-CoV-2 epidemics in several large cities or provinces of China. However, information regarding the early epidemics in small and medium-sized cities, where there are still traditionally large families and community culture is more strongly maintained and thus, transmission profiles may differ, is limited. In this study, we characterized 60 newly sequenced SARS-CoV-2 genomes from Anyang as a representative of small and medium-sized Chinese cities, compared them with more than 400 reference genomes from the early outbreak, and studied the SARS-CoV-2 transmission profiles. Genomic epidemiology revealed multiple SARS-CoV-2 introductions in Anyang and a large-scale expansion of the epidemic because of the large family size. Moreover, our study revealed two transmission patterns in a single outbreak, which were attributed to different social activities. We observed the complete dynamic process of single-nucleotide polymorphism development during community transmission and found that intrahost variant analysis was an effective approach to studying cluster infections. In summary, our study provided new SARS-CoV-2 transmission profiles representative of small and medium-sized Chinese cities as well as information on the evolution of SARS-CoV-2 strains during the early COVID-19 epidemic in China.

Indexed as

COVID-19EpidemicsChinaCitiesCulture MediaHumansSARS-CoV-2Culture MediaCommunity transmissionEpidemiologyIntrahost variantSARS-CoV-2Single-nucleotide polymorphism

Identifiers

PMID35279413
PMCPMC8786408

What OpenQuestion holds

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Registered trials

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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.