Evidence map›Paper›PMID 33850045›Full record

ArticlemSystems2021

Indoor Dust as a Matrix for Surveillance of COVID-19.

Nicole Renninger, Nicholas Nastasi, Ashleigh Bope, Samuel J Cochran, Sarah R Haines, Neeraja Balasubrahmaniam, Katelyn Stuart, Aaron Bivins, Kyle Bibby, Natalie M Hull and 1 more

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.3field-weighted citation impact, top 6% 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

29 citing papers in PubMed, 59 citations in OpenAlex.

  1. Article
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  6. Predicting COVID-19 Cases Across a Large University Campus Using Built Environment Surveillance.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024
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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

11 authors at 2 institutions in 1 country.

Nicole RenningerDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Nicholas NastasiDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Ashleigh BopeDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Samuel J CochranDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Sarah R HainesDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Neeraja BalasubrahmaniamDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Katelyn StuartDivision of Environmental Health Sciences, College of Public Health, Ohio State University, Columbus, Ohio, USA.
Aaron BivinsDepartment of Civil & Environmental Engineering & Earth Sciences, College of Engineering, University of Notre Dame, Notre Dame, Indiana, USA.
Kyle BibbyDepartment of Civil & Environmental Engineering & Earth Sciences, College of Engineering, University of Notre Dame, Notre Dame, Indiana, USA.ORCID https://orcid.org/0000-0003-3142-6090
Natalie M HullDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA.
Karen C DannemillerDepartment of Civil, Environmental & Geodetic Engineering, College of Engineering, Ohio State University, Columbus, Ohio, USA Dannemiller.70@osu.edu.ORCID https://orcid.org/0000-0003-4754-6804
The Ohio State University · USUniversity of Notre Dame · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ongoing disease surveillance is a critical tool to mitigate viral outbreaks, especially during a pandemic. Environmental monitoring has significant promise even following widespread vaccination among high-risk populations. The goal of this work is to demonstrate molecular severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) monitoring in bulk floor dust and related samples as a proof of concept of a noninvasive environmental surveillance methodology for coronavirus disease 2019 (COVID-19) and potentially other viral diseases. Surface swab, passive sampler, and bulk floor dust samples were collected from the rooms of individuals positive for COVID-19, and SARS-CoV-2 was measured with quantitative reverse transcription-PCR (RT-qPCR) and two digital PCR (dPCR) methods. Bulk dust samples had a geometric mean concentration of 163 copies/mg of dust and ranged from nondetects to 23,049 copies/mg of dust detected using droplet digital PCR (ddPCR). An average of 89% of bulk dust samples were positive for the virus by the detection methods compared to 55% of surface swabs and fewer on the passive sampler (19% carpet, 29% polystyrene). In bulk dust, SARS-CoV-2 was detected in 76%, 93%, and 97% of samples measured by qPCR, chip-based dPCR, and droplet dPCR, respectively. Detectable viral RNA in the bulk vacuum bags did not measurably decay over 4 weeks, despite the application of a disinfectant before room cleaning. Future monitoring efforts should further evaluate RNA persistence and heterogeneity in dust. This study did not measure virus infectivity in dust or potential transmission associated with dust. Overall, this work demonstrates that bulk floor dust is a potentially useful matrix for long-term monitoring of viral disease in high-risk populations and buildings.

Indexed as

built environmentCOVID-19dustindoor environmentmonitoringoutbreakSARS-CoV-2surveillancevacuumvirus

Identifiers

PMID33850045
PMCPMC8547012
OpenAlexW3152973541

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.