Evidence map›Paper›PMID 38075856›Full record

ArticleFrontiers in microbiology2023

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage.

Ye Li, Kurt T Ash, Dominique C Joyner, Daniel E Williams, Isabella Alamilla, Peter J McKay, Chris Iler, Terry C Hazen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Wastewater Metavirome Diversity: Exploring Replicate Inconsistencies and Bioinformatic Tool Disparities.International journal of environmental research and public health · 2025
    Article
  5. Article
  6. Article
  7. 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

8 authors at 2 institutions in 1 country.

Ye LiDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
Kurt T AshDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
Dominique C JoynerDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
Daniel E WilliamsDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
Isabella AlamillaDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
Peter J McKayStudent Health Center, University of Tennessee, Knoxville, Knoxville, TN, United States.
Chris IlerDepartment of Facilities Services, University of Tennessee, Knoxville, Knoxville, TN, United States.
Terry C HazenDepartment of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States.
University of Tennessee at Knoxville · USOak Ridge National Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

Indexed as

PMMoV RNAraw sewagesampling durationsampling modessampling timingSARS-CoV-2 RNA

Identifiers

PMID38075856
PMCPMC10702244
OpenAlexW4388945559

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.