Evidence map›Paper›PMID 34467932›Full record

ArticleThe Science of the total environment2021

Wastewater SARS-CoV-2 monitoring as a community-level COVID-19 trend tracker and variants in Ohio, United States.

Yuehan Ai, Angela Davis, Dan Jones, Stanley Lemeshow, Huolin Tu, Fan He, Peng Ru, Xiaokang Pan, Zuzana Bohrerova, Jiyoung Lee

Open access · greenAbstract read
In one paragraph

Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
96citing papers in PubMed, 3 pooled it
9.8field-weighted citation impact, top 1% 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

96 citing papers in PubMed, 3 syntheses or guidelines pooled it, 173 citations in OpenAlex.

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  14. Coupling wastewater-based epidemiology with data-driven machine learning for managing public health risks.Risk analysis : an official publication of the Society for Risk Analysis · 2025
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  16. Dynamics of SARS-CoV-2 variants in southwest Ohio municipal wastewater.Environmental science : water research & technology · 2025
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36 more citing papers are in PubMed but not listed here.

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

10 authors at 3 institutions in 1 country.

Yuehan AiDepartment of Food Science and Technology, The Ohio State University, Columbus, OH, USA.
Angela DavisDivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA.
Dan JonesThe Ohio State University Comprehensive Cancer Center and James Cancer Center, Columbus, OH, USA; James Molecular Laboratory, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Stanley LemeshowDivision of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA.
Huolin TuThe Ohio State University Comprehensive Cancer Center and James Cancer Center, Columbus, OH, USA.
Fan HeDepartment of Food Science and Technology, The Ohio State University, Columbus, OH, USA.
Peng RuThe Ohio State University Comprehensive Cancer Center and James Cancer Center, Columbus, OH, USA.
Xiaokang PanJames Molecular Laboratory, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Zuzana BohrerovaDepartment of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.
Jiyoung LeeDepartment of Food Science and Technology, The Ohio State University, Columbus, OH, USA; Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA. Electronic address: lee.3598@osu.edu.
The Ohio State University · USThe Ohio State University Wexner Medical Center · USThe Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 129 million confirm cases. Many health authorities around the world have implemented wastewater-based epidemiology as a rapid and complementary tool for the COVID-19 surveillance system and more recently for variants of concern emergence tracking. In this study, three SARS-CoV-2 target genes (N1 and N2 gene regions, and E gene) were quantified from wastewater influent samples (n = 250) obtained from the capital city and 7 other cities in various size in central Ohio from July 2020 to January 2021. To determine human-specific fecal strength in wastewater samples more accurately, two human fecal viruses (PMMoV and crAssphage) were quantified to normalize the SARS-CoV-2 gene concentrations in wastewater. To estimate the trend of new case numbers from SARS-CoV-2 gene levels, different statistical models were built and evaluated. From the longitudinal data, SARS-CoV-2 gene concentrations in wastewater strongly correlated with daily new confirmed COVID-19 cases (average Spearman's r = 0.70, p < 0.05), with the N2 gene region being the best predictor of the trend of confirmed cases. Moreover, average daily case numbers can help reduce the noise and variation from the clinical data. Among the models tested, the quadratic polynomial model performed best in correlating and predicting COVID-19 cases from the wastewater surveillance data, which can be used to track the effectiveness of vaccination in the later stage of the pandemic. Interestingly, neither of the normalization methods using PMMoV or crAssphage significantly enhanced the correlation with new case numbers, nor improved the estimation models. Viral sequencing showed that shifts in strain-defining variants of SARS-CoV-2 in wastewater samples matched those in clinical isolates from the same time periods. The findings from this study support that wastewater surveillance is effective in COVID-19 trend tracking and provide sentinel warning of variant emergence and transmission within various types of communities.

Indexed as

COVID-19SARS-CoV-2HumansOhioWastewaterWastewater-Based Epidemiological MonitoringWastewaterB.1.427/429crAssphageD614GN501YPMMoVQuadratic polynomial modelWastewater-based epidemiology

Identifiers

PMID34467932
PMCPMC8373851
OpenAlexW3195042195

What OpenQuestion holds

Textmetadata
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.