Evidence map›Paper›PMID 38675989›Full record

ArticleViruses2024

Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China.

Lin Qu, Chunyan Xie, Ming Qiu, Lina Yi, Zhe Liu, Lirong Zou, Pei Hu, Huimin Jiang, Huimin Lian, Mingda Yang and 11 more

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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  5. Review
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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

21 authors at 4 institutions in 1 country.

Lin QuSchool of Public Health, Sun Yat-sen University, Guangzhou 510080, China.ORCID 0000-0001-5957-2132
Chunyan XieGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Ming QiuSchool of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Lina YiGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Zhe LiuGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Lirong ZouGuangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
Pei HuGuangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
Huimin JiangGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Huimin LianGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Mingda YangGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Haiyi YangSchool of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Huiling ZengGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Huimin ChenGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Jianguo ZhaoGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Jianpeng XiaoGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Jianfeng HeGuangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
Ying YangGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Liang ChenGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Baisheng LiGuangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
Jiufeng SunGuangdong Provincial Institution of Public Health, Guangzhou 511430, China.
Jing LuSchool of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Guangdong Provincial Center for Disease Control and Prevention · CNSun Yat-sen University · CNJinan University · CNGuangdong Pharmaceutical University · CN

Funding

Guangdong Science and Technology Department 2021B1212030007Guangdong Science and Technology Department 2023A1515011927Guangzhou Science, Technology and Innovation Commission 202102080590
6 · The paper itself

Abstract

backgroundAfter the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive.

methodsWe launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited.

results90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection.

conclusionsThe rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.

Indexed as

Antibodies, NeutralizingAntibodies, ViralCOVID-19SARS-CoV-2Viral LoadAdultAgedChinaCohort StudiesFemaleHumansMaleMiddle AgedProspective StudiesYoung AdultAntibodies, NeutralizingAntibodies, Viralcohort studyneutralizing antibodiesOmicron variantSARS-CoV-2viral trajectories

Identifiers

PMID38675989
PMCPMC11053513
OpenAlexW4394999315

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.