Evidence map›Paper›PMID 35872187›Full record

ArticleThe Science of the total environment2022

Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR.

Nicholas W West, Adrian A Vasquez, Azadeh Bahmani, Mohammed F Khan, James Hartrick, Carrie L Turner, William Shuster, Jeffrey L Ram

Open access · greenAbstract read
In one paragraph

Article in The Science of the total environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Nicholas W WestDepartment of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Adrian A VasquezDepartment of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA. Electronic address: avasque@med.wayne.edu.
Azadeh BahmaniDepartment of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Mohammed F KhanDepartment of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
James HartrickLimnoTech, 501 Avis Dr., Ann Arbor, MI 48108, USA.
Carrie L TurnerLimnoTech, 501 Avis Dr., Ann Arbor, MI 48108, USA.
William ShusterDepartment of Civil and Environmental Engineering, Wayne State University, Detroit, MI 48202, USA.
Jeffrey L RamDepartment of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Wayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher.

Indexed as

COVID-19SARS-CoV-2BiomarkersCOVID-19 TestingHumansPolymerase Chain ReactionRNA, ViralSodium ChlorideWastewaterBiomarkersRNA, ViralSodium ChlorideWastewaterAutomatedCOVID-19DetroitRNA purificationViral RNAWastewater

Identifiers

PMID35872187
PMCPMC9303066
OpenAlexW4286436631

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.