Evidence map›Paper›PMID 40904683›Full record

ArticleFrontiers in microbiology2025

Beyond clinical data: the role of sewage monitoring in tracking pandemic trends of SARS-CoV-2.

Zhenlu Sun, Yulou Sun, Kai Guo, Lili Zhao, Cong Li, Yi Zhang, Shi Cui Yan, Jian Yang, Guifang Zhang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Zhenlu Sun *Yantai Center for Disease Control and Prevention, Yantai, China.
Yulou Sun *Yantai Center for Disease Control and Prevention, Yantai, China.
Kai GuoYantai Center for Disease Control and Prevention, Yantai, China.
Lili ZhaoYantai Center for Disease Control and Prevention, Yantai, China.
Cong LiYantai Center for Disease Control and Prevention, Yantai, China.
Yi ZhangYantai Center for Disease Control and Prevention, Yantai, China.
Shi Cui YanYantai Center for Disease Control and Prevention, Yantai, China.
Jian YangYantai Center for Disease Control and Prevention, Yantai, China.
Guifang ZhangYantai Center for Disease Control and Prevention, Yantai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The SARS-CoV-2 pandemic has caused a global crisis that has impacted not only health care systems, but also economies and societies. The constraints in clinical testing provide challenges in reliably assessing the prevalence of variations, particularly in regions with limited resources, testing, and sequencing capabilities. Sewage-based epidemiology uses SARS-CoV-2 in sewage as an indicator, can monitor and provide early warning of viral transmission in communities, thereby informing response strategies. Methods: In this study, sewage samples and clinical patient samples were collected in Yantai City, Shandong Province. RT-qPCR and high-throughput sequencing techniques were employed to identify and analyze SARS-CoV-2, respectively. Results: Our results showed that the dynamic trend of SARS-CoV-2 RNA concentration in sewage samples coincided with the positive rate of clinical surveillance cases (Spearman's Discussion: Our study demonstrates that effluent genomic surveillance is a rapid, sensitive, and scalable method. It enables the timely identification of SARS-CoV-2 variants and the detection of hidden transmission. It can be applied to SARS-CoV-2 early warning as well as epidemiologic surveillance. However, this study has certain limitations. First, due to financial constraints, only a limited number of clinical samples were analyzed, which may have underestimated the diversity of SARS-CoV-2 lineages in the patient population. Second, the absence of information on the physicochemical characteristics of sewage may have limited our understanding of environmental factors affecting viral stability and detection efficiency.

Indexed as

genomic surveillancehigh-throughput sequencingRT-qPCRSARS-CoV-2sewage

Identifiers

PMID40904683
PMCPMC12402065

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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.