Effectiveness of germicidal ultraviolet light to inactivate coronaviruses on personal protective equipment to reduce nosocomial transmission
Bibliographic record
Abstract
Abstract Objective: To circumvent the need for rationing personal protective equipment (PPE), we explored whether germicidal ultraviolet light (GUV) could be used to inactivate human coronaviruses on PPE, enabling safe reuse. Design: We performed a laboratory study to assess the ability of 2 commercially available portable GUV devices to inactivate 2 common cold coronaviruses (HCoV-229E and HCoV-OC43) and severe acute respiratory syndrome coronavirus virus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), on the surface of whole N95 respirators and coupons cut from those respirators. We experimentally contaminated N95 respirators with coronavirus cultures and then assessed viral inactivation after GUV exposure by plaque assay, the median tissue culture infectious dose (TCID 50 ) assay, and quantitative reverse-transcriptase polymerase chain reaction (RT-PCR). Results: We found that GUV could efficiently inactivate coronaviruses on the surface of N95 masks, with an average reduction in viral titers of 5-log for HCoV-229E, 3-log for HCoV-OC43, and 5-log for SARS-CoV-2. In addition, the GUV susceptibility of HCoV-229E was similar on coupons and whole N95 respirators. Conclusions: We demonstrate that diverse human coronaviruses, including SARS-CoV-2, are susceptible to GUV inactivation, and 2 scalable portable GUV devices were effective in inactivating coronaviruses on N95 respirators. Thus, GUV treatment with commercially scalable devices may be an effective method to decontaminate PPE, allowing their safe reuse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".