Airborne contamination of COVID-19 in hospitals: a scoping review of the current evidence

  1. Gabriel Birgand
  2. Nathan Peiffer-Smadja
  3. Sandra Fournier
  4. Solen Kerneis
  5. François-Xavier Lescure
  6. Jean-Christophe Lucet

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Abstract

Introduction

A controversy remains worldwide regarding the transmission routes of SARS-CoV-2 in hospital settings. We reviewed the current evidence on the air contamination with SARS-CoV-2 in hospital settings, and the factors associated to the contamination including the viral load and the particles size.

Methods

The MEDLINE, Embase, Web of Science databases were systematically interrogated for original English-language articles detailing COVID-19 air contamination in hospital settings between 1 December 2019 and 21 July 2020. This study was conducted in accordance with the PRISMA-ScR guidelines. The positivity rate of SARS-CoV-2 viral RNA and culture were described and compared according to the setting, clinical context, air ventilation system, and distance from patient. The SARS-CoV-2 RNA concentrations in copies per m 3 of air were pooled and their distribution were described by hospital areas. Particle sizes and SARS-CoV-2 RNA concentrations in copies or TCID50 per m 3 were analysed after categorization of sizes in < 1 µm, 1–4 µm, and > 4 µm.

Results

Among 2,034 records identified, 17 articles were included in the review. Overall, 27.5% (68/247) of air sampled from close patients’ environment were positive for SARS-CoV-2 RNA, without difference according to the setting (ICU: 27/97, 27.8%; non-ICU: 41/150, 27.3%; p = 0.93), the distance from patients (< 1 meter: 1/64, 1.5%; 1–5 meters: 4/67, 6%; p = 0.4). In other areas, the positivity rate was 23.8% (5/21) in toilets, 9.5% (20/221) in clinical areas, 12.4% (15/121) in staff areas, and 34.1% (14/41) in public areas. A total of 78 viral cultures were performed in three studies, and 3 (4%) were positive, all from close patients’ environment. The median SARS-CoV-2 RNA concentrations varied from 1.10 3 copies per m 3 (IQR: 0.4.10 3 -9.10 3 ) in clinical areas to 9.7.10 3 (5.1.10 3 -14.3.10 3 ) in the air of toilets or bathrooms. The protective equipment removal and patients’ rooms had high concentrations/titre of SARS-CoV-2 with aerosol size distributions that showed peaks in the < 1 µm region, and staff offices in the > 4µm region.

Conclusion

In hospital, the air near and away from COVID-19 patients is frequently contaminated with SARSCoV-2 RNA, with however, rare proofs of their viability. High viral loads found in toilet/bathrooms, staff and public hallways suggests to carefully consider these areas.

Article activity feed

  1. NCRC

    Our take

    This study, available as a preprint and thus not yet peer reviewed, provides further evidence that viral RNA can be found in hospital settings, particularly in areas closest to COVID-19 patients, and in bathroom and other public spaces. Less has been shown about the viability of this virus and the potential for airborne transmission. Future studies collecting information on air samples would benefit from providing data on location of sample collection, ventilation systems in place, distance from any positive patients, further clinical context, and viability of virus.

    Study design

    other

    Study population and setting

    The current literature on air contamination in hospital settings was reviewed. Articles published on MEDLINE, Embase, and Web of Science databases between December 1, 2019 and July 21, 2020 were included in the review. The search was augmented to include a review of selected infectious disease journals and certain preprint servers. Data abstraction included key characteristics of the samples (RNA concentrations and particle sizes), the setting and clinical context, the ventilation system, and the methods around sample collection.

    Summary of main findings

    Of the 2034 papers identified, 17 were included in the review, excluding duplicates and those papers unrelated to the topic. One in three samples taken from air close to COVID-19 patients (68/247) contained SARS-CoV-2 RNA. No significant difference was found in the presence of RNA by location (ICU vs. non-ICU) or by distance (<1 meter vs. 1 to 5 meters). Viral RNA was found in samples from other non COVID-19 specific areas, including bathrooms, other clinical areas, staff areas, and public areas. The percentage of samples coming back with positive detection of viral RNA was highest in public areas (34.1% or 14/41). The median concentration of RNA was higher in the air of bathrooms than in clinical areas.

    Study strengths

    The methods of the review are well-detailed and follow PRISMA guidelines.

    Limitations

    Methods used to collect and analyze air samples are disparate across studies included, and context around the samples collected was not regularly reported (e.g. location, ventilation, distance, clinical context). It is unclear whether the studies included are actually comparable and should be analyzed together as this scoping review has done.

    Value added

    This study compiles the evidence related to viral RNA presence in air samples in hospital settings.

  2. ScreenIT

    SciScore for 10.1101/2020.09.09.20191213: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: We performed a systematic search of MEDLINE via PubMed, Embase, Web of Science, on 21 July 2020 with the terms covering COVID-19, air contamination in hospital settings in articles published between 1 December 2019 and 21 July 2020 (see Supplement S1 for details of search strategies).
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    We also searched some preprint servers, including BioRxiv (https://www.biorxiv.org/).
    BioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    We described the setting, patient clinical contexts, ventilation, air sampling and SARS-CoV-2 search methods, and the qualitative and quantitative results according to settings and the hospital area.
    SARS-CoV-2
    suggested: (Active Motif Cat# 91351, RRID:AB_2847848)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study also has some limitations. First, the context (location, ventilation, distance, clinical context) were infrequently detailed in studies. As explained above, this potentially affected the comparability of data, and the reliability of pooled data analysis. Misclassification may have occurred when variables were categorized without enough details. This issue was avoided by performing the categorization only when data were available. Second, for a better clarity of the analysis, we did not include contamination of surfaces. However, air and surface contamination are potentially correlated, and may ease the understanding of resuspension. Finally, we included article not validated through a peer review process.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.09.09.20191213v1 on medRxiv