Evidence map›Paper›PMID 35061676›Full record

ArticlePloS one2022

Effectiveness of various cleaning strategies in acute and long-term care facilities during novel corona virus 2019 disease pandemic-related staff shortages.

Emil Lesho, Donna Newhart, Lisa Reno, Scott Sleeper, Julia Nary, Jennifer Gutowski, Stephanie Yu, Edward Walsh, Roberto Vargas, Dawn Riedy and 1 more

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Non-pharmaceutical interventions for COVID-19: a systematic review on environmental control measures.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
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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.

Emil LeshoRochester Regional Health, Rochester, NY, United States of America.ORCID 0000-0003-3917-5871
Donna NewhartRochester Regional Health, Rochester, NY, United States of America.
Lisa RenoRochester Regional Health, Rochester, NY, United States of America.
Scott SleeperRochester Regional Health, Rochester, NY, United States of America.
Julia NaryRochester Regional Health, Rochester, NY, United States of America.
Jennifer GutowskiRochester Regional Health, Rochester, NY, United States of America.
Stephanie YuRochester Regional Health, Rochester, NY, United States of America.
Edward WalshUniversity of Rochester School of Medicine and Dentistry, Rochester, NY, United States of America.
Roberto VargasRochester Regional Health, Rochester, NY, United States of America.
Dawn RiedyRochester Regional Health, Rochester, NY, United States of America.
Robert MayoRochester Regional Health, Rochester, NY, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCleanliness of hospital surfaces helps prevent healthcare-associated infections, but comparative evaluations of various cleaning strategies during COVID-19 pandemic surges and worker shortages are scarce. PURPOSE AND

methodsTo evaluate the effectiveness of daily, enhanced terminal, and contingency-based cleaning strategies in an acute care hospital (ACH) and a long-term care facility (LTCF), using SARS-CoV-2 RT-PCR and adenosine triphosphate (ATP) assays. Daily cleaning involved light dusting and removal of visible debris while a patient is in the room. Enhanced terminal cleaning involved wet moping and surface wiping with disinfectants after a patient is permanently moved out of a room followed by ultraviolet light (UV-C), electrostatic spraying, or room fogging. Contingency-based strategies, performed only at the LTCF, involved cleaning by a commercial environmental remediation company with proprietary chemicals and room fogging. Ambient surface contamination was also assessed randomly, without regard to cleaning times. Near-patient or high-touch stationary and non-stationary environmental surfaces were sampled with pre-moistened swabs in viral transport media.

resultsAt the ACH, SARS-CoV-2 RNA was detected on 66% of surfaces before cleaning and on 23% of those surfaces immediately after terminal cleaning, for a 65% post-cleaning reduction (p = 0.001). UV-C enhancement resulted in an 83% reduction (p = 0.023), while enhancement with electrostatic bleach application resulted in a 50% reduction (p = 0.010). ATP levels on RNA positive surfaces were not significantly different from those of RNA negative surfaces. LTCF contamination rates differed between the dementia, rehabilitation, and residential units (p = 0.005). 67% of surfaces had RNA after room fogging without terminal-style wiping. Fogging with wiping led to a -11% change in the proportion of positive surfaces. At the LTCF, mean ATP levels were lower after terminal cleaning (p = 0.016).

conclusionAmbient surface contamination varied by type of unit and outbreak conditions, but not facility type. Removal of SARS-CoV-2 RNA varied according to cleaning strategy. IMPLICATIONS: Previous reports have shown time spent cleaning by hospital employed environmental services staff did not correlate with cleaning thoroughness. However, time spent cleaning by a commercial remediation company in this study was associated with cleaning effectiveness. These findings may be useful for optimizing allocation of cleaning resources during staffing shortages.

Indexed as

Adenosine TriphosphateCOVID-19Cross InfectionDisinfectantsDisinfectionFomitesHealth FacilitiesHealth PersonnelHumansInfection ControlLong-Term CareNew YorkPatients' RoomsRNA, ViralSARS-CoV-2Ultraviolet RaysAdenosine TriphosphateDisinfectantsRNA, Viral

Identifiers

PMID35061676
PMCPMC8782535

What OpenQuestion holds

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LicenceCC BY
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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.