ArticleJournal of photochemistry and photobiology. B, Biology2022
UV-C irradiation-based inactivation of SARS-CoV-2 in contaminated porous and non-porous surfaces.
Article in Journal of photochemistry and photobiology. B, Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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.
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Who cites it
11 citing papers in PubMed, 24 citations in OpenAlex.
- Efficacy of Antimicrobials Against Enveloped and Non-Enveloped Viruses on Porous Materials: A Review.Microorganisms · 2025Review
- Nanotechnology meets medicine: applications of atomic force microscopy in disease.Biophysical reviews · 2025Review
- Inactivation of deposited bioaerosols on food contact surfaces with UV-C light emitting diode devices.Applied and environmental microbiology · 2025Article
- Inactivation of Hepatitis A Virus and Feline Calicivirus on Model Food Contact Surfaces by Ultraviolet Light (UV-C) Systems.Foods (Basel, Switzerland) · 2024Article
- Impacts of Surface Characteristics and Dew Point on the Blue-Light (BLMicroorganisms · 2023Article
- Article
- Virus Behavior after UVMicroorganisms · 2023Article
- Edible alginate-based films with anti-SARS-CoV-2 activity.Food microbiology · 2023Article
- High-Intensity Ultraviolet-C Irradiation Efficiently Inactivates SARS-CoV-2 Under Typical Cold Chain Temperature.Food and environmental virology · 2023Article
- Application of Ultraviolet-C Radiation and Gaseous Ozone for Microbial Inactivation on Different Materials.ACS omega · 2022Article
- SARS-CoV-2 air and surface contamination in residential settings.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The SARS-CoV-2 pandemic emphasized effective cleaning and disinfection of common spaces as an essential tool to mitigate viral transmission. To address this problem, decontamination technologies based on UV-C light are being used. Our aim was to generate coherent and translational datasets of effective UV-C-based SARS-CoV-2 inactivation protocols for the application on surfaces with different compositions. Virus infectivity after UV-C exposure of several porous (bed linen, various types of upholstery, synthetic leather, clothing) and non-porous (types of plastic, stainless steel, glass, ceramics, wood, vinyl) materials was assessed through plaque assay using a SARS-CoV-2 clinical isolate. Studies were conducted under controlled environmental conditions with a 254-nm UV-C lamp and irradiance values quantified using a 254 nm-calibrated sensor. From each material type (porous/non-porous), a product was selected as a reference to assess the decrease of infectious virus particles as a function of UV-C dose, before testing the remaining surfaces with selected critical doses. Our data show that UV-C irradiation is effectively inactivating SARS-CoV-2 on both material types. However, an efficient reduction in the number of infectious viral particles was achieved much faster and at lower doses on non-porous surfaces. The treatment effectiveness on porous surfaces was demonstrated to be highly variable and composition-dependent. Our findings will support the optimization of UV-C-based technologies, enabling the adoption of effective customizable protocols that will help to ensure higher antiviral efficiencies.
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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.