Evidence map›Paper›PMID 36203558›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Impact of sample clarification by size exclusion on virus detection and diversity in wastewater-based epidemiology.

Temitope O C Faleye, Peter Skidmore, Amir Elyaderani, Sangeet Adhikari, Nicole Kaiser, Abriana Smith, Allan Yanez, Tyler Perleberg, Erin M Driver, Rolf U Halden and 2 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. 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, 2 citations in OpenAlex.

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

12 authors at 2 institutions in 1 country.

Temitope O C FaleyeBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Peter SkidmoreCollege of Health Solutions, Arizona State University, Tempe, AZ, USA.
Amir ElyaderaniCollege of Health Solutions, Arizona State University, Tempe, AZ, USA.
Sangeet AdhikariBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Nicole KaiserCollege of Health Solutions, Arizona State University, Tempe, AZ, USA.
Abriana SmithCollege of Health Solutions, Arizona State University, Tempe, AZ, USA.
Allan YanezBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Tyler PerlebergBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Erin M DriverBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Rolf U HaldenBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Arvind VarsaniBiodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA.
Matthew ScotchBiodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
Center for Environmental Health · USArizona State University · US

Funding

Bioinformatics Framework for Wastewater-based Surveillance of Infectious DiseasesU01LM013129 · NLM · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI HALDEN, ROLF U, SCOTCH, MATTHEW · 2020 to 2022
$3.3M
NLM NIH HHS U01 LM013129
6 · The paper itself

Abstract

The use of wastewater-based epidemiology (WBE) for early detection of virus circulation and response during the SARS-CoV-2 pandemic increased interest in and use of virus concentration protocols that are quick, scalable, and efficient. One such protocol involves sample clarification by size fractionation using either low-speed centrifugation to produce a clarified supernatant or membrane filtration to produce an initial filtrate depleted of solids, eukaryotes and bacterial present in wastewater (WW), followed by concentration of virus particles by ultrafiltration of the above. While this approach has been successful in identifying viruses from WW, it assumes that majority of the viruses of interest should be present in the fraction obtained by ultrafiltration of the initial filtrate, with negligible loss of viral particles and viral diversity. We used WW samples collected in a population of ~700,000 in southwest USA between October 2019 and March 2021, targeting three non-enveloped viruses (enteroviruses [EV], canine picornaviruses [CanPV], and human adenovirus 41 [Ad41]), to evaluate whether size fractionation of WW prior to ultrafiltration leads to appreciable differences in the virus presence and diversity determined. We showed that virus presence or absence in WW samples in both portions (filter trapped solids [FTS] and filtrate) are not consistent with each other. We also found that in cases where virus was detected in both fractions, virus diversity (or types) captured either in FTS or filtrate were not consistent with each other. Hence, preferring one fraction of WW over the other can undermine the capacity of WBE to function as an early warning system and negatively impact the accurate representation of virus presence and diversity in a population.

Indexed as

Adenovirus 41High-throughput nucleotide sequencingPicornaviridaeSample clarification by size fractionationWastewater-based epidemiological monitoring

Identifiers

PMID36203558
PMCPMC9536034
OpenAlexW4297359566

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.