Evidence map›Paper›PMID 39735751›Full record

ArticleFrontiers in public health2024

COVID-19 outbreaks caused by different SARS-CoV-2 variants: a descriptive, comparative study from China.

Cao Chen, Yenan Feng, Zeyuan Yin, Mingfan Pang, Qi Shi, Xuejun Ma, Xiao-Ping Dong

Abstract readComparative Study
In one paragraph

Article in Frontiers in public health, 2024. 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

7 authors.

Cao ChenNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yenan FengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zeyuan YinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Mingfan PangCenter for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Qi ShiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xuejun MaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiao-Ping DongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To understand the epidemic characteristics of various SARS-CoV-2 variants, we mainly focus on analyzing general epidemic profiles, viral mutation, and evolution of COVID-19 outbreaks caused by different SARS-CoV-2 variants of concern (VOCs) in China as of August 2022. Methods: We systematically sorted out the general epidemic profiles of outbreaks caused by various SARS-CoV-2 VOCs in China, compared the differences of outbreaks caused by Delta and Omicron VOCs, and analyzed the mutational changes of subvariants between the same outbreak and different outbreaks. Findings: By 15 August 2022, a total of 2, 33, and 124 COVID-19 outbreaks caused by Alpha, Delta, and Omicron VOCs, respectively, were reported in different regions of China. In terms of the number of outbreaks, the extent of affected areas, and the total number of confirmed cases, Omicron VOCs were more widespread than the other variants. The most frequently circulating PANGO lineages in China were B.1.617.2 and AY.122 in Delta VOCs, and BA.2.2.1, BA.2, BA.2.2, and BA.5 for Omicron VOCs. Additional mutations in the genome of the SARS-CoV-2 strain were frequently observed in outbreaks with longer duration and higher numbers of infections. Conclusion: Through the comprehensive analysis of the COVID-19 outbreaks, the influences, and the evolution of the SARS-CoV-2 variants in China, we found differences between outbreaks caused by Delta and Omicron VOCs. The genome of SARS-CoV-2 continued to evolve within the same outbreak and across outbreaks occurring in different locations or at different times. These findings suggest that rapidly containing an Omicron virus outbreak can not only reduce the spread of the virus but also delay the virus's mutation frequency.

Indexed as

COVID-19Disease OutbreaksMutationSARS-CoV-2ChinaHumansCOVID-19omicronoutbreakSARS-CoV-2variants

Identifiers

PMID39735751
PMCPMC11672794

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.