Evidence map›Paper›PMID 38335205›Full record

ArticlePloS one2024

Identification of SARS-CoV-2 variants in indoor dust.

John Van Dusen, Haley LeBlanc, Nicholas Nastasi, Jenny Panescu, Austin Shamblin, Jacob W Smith, Michael G Sovic, Amanda Williams, Mikkel B M Quam, Seth Faith and 1 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

John Van DusenDepartment of Microbiology, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America.ORCID 0009-0000-0236-2054
Haley LeBlancGenetic Counseling Program, College of Biological Sciences, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID 0000-0001-7234-2489
Nicholas NastasiEnvironmental Sciences Graduate Program, The Ohio State University, Columbus, Ohio, United States of America.
Jenny PanescuDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America.
Austin ShamblinApplied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America.ORCID 0009-0002-0225-8024
Jacob W SmithDepartment of Chemistry and Biochemistry, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America.ORCID 0000-0002-8754-5921
Michael G SovicApplied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America.ORCID 0000-0002-8556-3704
Amanda WilliamsInstitute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio, United States of America.
Mikkel B M QuamInfectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America.
Seth FaithApplied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America.
Karen C DannemillerDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America.

Funding

COVID-19 surveillance in public buildings using vacuumed dustR21AI168817 · NIAID · OHIO STATE UNIVERSITY · PI DANNEMILLER, KAREN · 2022 to 2023
$427k
NIAID NIH HHS R21 AI168817
6 · The paper itself

Abstract

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

Indexed as

COVID-19SARS-CoV-2DustEnvironmental MonitoringHumansDust

Identifiers

PMID38335205
PMCPMC10857703

What OpenQuestion holds

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Registered trials

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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.