ArticleInfection control and hospital epidemiology2020
Air and environmental sampling for SARS-CoV-2 around hospitalized patients with coronavirus disease 2019 (COVID-19).
Article in Infection control and hospital epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 10 of them syntheses that pooled it.
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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.
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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.
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Who cites it
102 citing papers in PubMed, 10 syntheses or guidelines pooled it, 199 citations in OpenAlex.
- A review on measurements of SARS-CoV-2 genetic material in air in outdoor and indoor environments: Implication for airborne transmission.The Science of the total environment · 2022Pooled it
- Surface contamination with SARS-CoV-2: A systematic review.The Science of the total environment · 2021Pooled it
- Contamination of Air and Surfaces in Workplaces with SARS-CoV-2 Virus: A Systematic Review.Annals of work exposures and health · 2021Pooled it
- SARS-CoV-2: a systematic review of indoor air sampling for virus detection.Environmental science and pollution research international · 2021Pooled it
- Prevalence of SARS-CoV-2 RNA on inanimate surfaces: a systematic review and meta-analysis.European journal of epidemiology · 2021Pooled it
- Airborne transmission of SARS-CoV-2 via aerosols.Reviews in medical virology · 2021Pooled it
- [Is Disinfection of Public Surfaces useful for the Prevention of SARS-CoV-2 Infections?]Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2021Pooled it
- AHNS endocrine surgery section consensus statement on nasopharyngolaryngoscopy and clinic reopening during COVID-19: How to get back to optimal safe care.Head & neck · 2021Guideline
- Effectiveness of Pre-procedural Mouth Rinses in Reducing Aerosol Contamination During Periodontal Prophylaxis: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Assessment of Air Contamination by SARS-CoV-2 in Hospital Settings.JAMA network open · 2020Pooled it
- Portable air cleaners and residential exposure to SARS-CoV-2 aerosols: A real-world study.Indoor air · 2022Trial
- Detection of airborne bovine coronavirus RNA in pen environments and exhaled breath of calves.JDS communications · 2026Article
- SARS-CoV-2 Surface Contamination and Viable Virus in High-Ventilation Single Rooms: Implications for Fomite Transmission.Juntendo medical journal · 2026Article
- Study on the mortality risk and predictive model for COVID-19 inpatients with pneumonia manifestations.PeerJ · 2026Article
- Outbreak of melioidosis in a highly urbanized area.Emerging microbes & infections · 2025Article
- Air, surface, and wastewater surveillance of SARS-CoV-2; a multimodal evaluation of COVID-19 detection in a built environment.Journal of exposure science & environmental epidemiology · 2025Article
- Detection of SARS-CoV-2 in bioaerosols and surface samples from healthcare facilities in Klang Valley, Malaysia.Scientific reports · 2025Article
- Microbial Contamination of Door Handles: A Global Systematic Review and Meta-Analysis of Public and Healthcare Settings.Environmental health insights · 2025Review
- Environmental biocontamination by SARS-CoV-2 Virus in the hospital setting.Current research in microbial sciences · 2025Article
- 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 · 2024Article
42 more citing papers are in PubMed but not listed here.
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Authors and funding
15 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe role of severe respiratory coronavirus virus 2 (SARS-CoV-2)-laden aerosols in the transmission of coronavirus disease 2019 (COVID-19) remains uncertain. Discordant findings of SARS-CoV-2 RNA in air samples were noted in early reports.
methodsSampling of air close to 6 asymptomatic and symptomatic COVID-19 patients with and without surgical masks was performed with sampling devices using sterile gelatin filters. Frequently touched environmental surfaces near 21 patients were swabbed before daily environmental disinfection. The correlation between the viral loads of patients' clinical samples and environmental samples was analyzed.
resultsAll air samples were negative for SARS-CoV-2 RNA in the 6 patients singly isolated inside airborne infection isolation rooms (AIIRs) with 12 air changes per hour. Of 377 environmental samples near 21 patients, 19 (5.0%) were positive by reverse-transcription polymerase chain reaction (RT-PCR) assay, with a median viral load of 9.2 × 102 copies/mL (range, 1.1 × 102 to 9.4 × 104 copies/mL). The contamination rate was highest on patients' mobile phones (6 of 77, 7.8%), followed by bed rails (4 of 74, 5.4%) and toilet door handles (4 of 76, 5.3%). We detected a significant correlation between viral load ranges in clinical samples and positivity rate of environmental samples (P < .001).
conclusionSARS-CoV-2 RNA was not detectable by air samplers, which suggests that the airborne route is not the predominant mode of transmission of SARS-CoV-2. Wearing a surgical mask, appropriate hand hygiene, and thorough environmental disinfection are sufficient infection control measures for COVID-19 patients isolated singly in AIIRs. However, this conclusion may not apply during aerosol-generating procedures or in cohort wards with large numbers of COVID-19 patients.
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Registered trials
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.