Evidence map›Paper›PMID 36913370›Full record

ArticlePloS one2023

The spatial and temporal distribution of SARS-CoV-2 from the built environment of COVID-19 patient rooms: A multicentre prospective study.

Michael Fralick, Madison Burella, Aaron Hinz, Hebah S Mejbel, David S Guttman, Lydia Xing, Jason Moggridge, John Lapp, Alex Wong, Caroline Nott and 3 more

Full text readMulticenter Study
In one paragraph

Article in PloS one, 2023. 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
–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

6 citing papers in PubMed.

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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

13 authors.

Michael FralickSinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada.ORCID 0000-0002-2082-2445
Madison BurellaSinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada.
Aaron HinzDepartment of Biology, University of Ottawa, Ottawa, Ontario, Canada.
Hebah S MejbelDepartment of Biology, University of Ottawa, Ottawa, Ontario, Canada.
David S GuttmanDepartment of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
Lydia XingThe Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Jason MoggridgeLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.ORCID 0000-0003-1291-5868
John LappSinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada.
Alex WongDepartment of Biology, Carleton University, Ottawa, Ontario, Canada.
Caroline NottThe Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Nicole Harris-LintonLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.
Rees KassenDepartment of Biology, University of Ottawa, Ottawa, Ontario, Canada.
Derek R MacFaddenThe Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.

Funding

CIHR EGA 179419
6 · The paper itself

Abstract

backgroundSARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment.

methodsWe conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals.

resultsOver the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily.

conclusionsWe were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy.

Indexed as

COVID-19Built EnvironmentHumansOntarioPatients' RoomsProspective StudiesSARS-CoV-2

Identifiers

PMID36913370
PMCPMC10010533

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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identifiers read4
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.