Evidence map›Paper›PMID 40128516›Full record

ArticleScientific reports2025

Monitoring reported SARS-CoV-2 variants to assess the status of COVID-19 epidemics in the low epidemic state.

Bin Liu, Zhongliang Wang, Shanshan Lu, Zhongtian Qi, Zhijie Zhang, Jie Luan, Jianbo Ba

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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.

Bin Liu *Naval Medical Center, Naval Medical University, No.880 Xiangyin Road, Yangpu District, Shanghai, China.
Zhongliang Wang *Department of Mathematics and Physics, Faculty of Military Medical Services, Naval Medical University, Shanghai, China.
Shanshan LuNaval Medical Center, Naval Medical University, No.880 Xiangyin Road, Yangpu District, Shanghai, China.
Zhongtian QiDepartment of Microbiology, Shanghai Key Laboratory of Medical Biodefense, Naval Medical University, Shanghai, China.
Zhijie ZhangDepartment of Epidemiology and Health Statistics, Fudan University, Shanghai, China.
Jie LuanNaval Medical Center, Naval Medical University, No.880 Xiangyin Road, Yangpu District, Shanghai, China. jieluan@126.com.
Jianbo BaNaval Medical Center, Naval Medical University, No.880 Xiangyin Road, Yangpu District, Shanghai, China. bevon@126.com.

Funding

National Key Research and Development Program of China 2022YFC2602900
6 · The paper itself

Abstract

The reported new confirmed cases of Coronavirus Disease 2019 (COVID-19) nowadays have diminished in their usefulness for assessing the pandemic situation. This study aimed to discover the correlation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants recorded by Nextstrain clade and PANGO lineage and the number of new confirmed cases. Percent stacked area charts were utilized to display their development trends. 31 and 1452 variants were named according to Nextstrain clade and PANGO lineage, respectively. The branch step value maintained a stable increase by linear regression analysis. The changing trend in SARS-CoV-2 variants (PANGO lineage) correlated negatively with the number of new confirmed COVID-19 cases through Spearman rank correlation coefficient (17/06/2020-17/11/2021, ρ=-0.387, P < 0.01; 15/12/2021-11/01/2023, ρ=-0.458, P < 0.01). The proportion and composition of dominant virus variants had regional discrepancies, but some also fluctuated. The speed and quantity of SARS-CoV-2 variants objectively reflect the characteristics of the COVID-19 pandemic and viral dissemination in the population even without valuable data of reported new confirmed cases. The SARS-CoV-2 variation may be a better tool for epidemic monitoring and early-warning in the low epidemic state.

Indexed as

COVID-19SARS-CoV-2EpidemicsHumansPandemicsCOVID-19 pandemicMonitoringNextstrain cladePANGO lineageSARS-CoV-2 variation

Identifiers

PMID40128516
PMCPMC11933414

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.