Extended use or reuse of single-use surgical masks and filtering face-piece respirators during the coronavirus disease 2019 (COVID-19) pandemic: A rapid systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Shortages of personal protective equipment during the coronavirus disease 2019 (COVID-19) pandemic have led to the extended use or reuse of single-use respirators and surgical masks by frontline healthcare workers. The evidence base underpinning such practices warrants examination. OBJECTIVES: To synthesize current guidance and systematic review evidence on extended use, reuse, or reprocessing of single-use surgical masks or filtering face-piece respirators. DATA SOURCES: We used the World Health Organization, the European Centre for Disease Prevention and Control, the US Centers for Disease Control and Prevention, and Public Health England websites to identify guidance. We used Medline, PubMed, Epistemonikos, Cochrane Database, and preprint servers for systematic reviews. METHODS: Two reviewers conducted screening and data extraction. The quality of included systematic reviews was appraised using AMSTAR-2. Findings were narratively synthesized. RESULTS: In total, 6 guidance documents were identified. Levels of detail and consistency across documents varied. They included 4 high-quality systematic reviews: 3 focused on reprocessing (decontamination) of N95 respirators and 1 focused on reprocessing of surgical masks. Vaporized hydrogen peroxide and ultraviolet germicidal irradiation were highlighted as the most promising reprocessing methods, but evidence on the relative efficacy and safety of different methods was limited. We found no well-established methods for reprocessing respirators at scale. CONCLUSIONS: Evidence on the impact of extended use and reuse of surgical masks and respirators is limited, and gaps and inconsistencies exist in current guidance. Where extended use or reuse is being practiced, healthcare organizations should ensure that policies and systems are in place to ensure these practices are carried out safely and in line with available guidance.
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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 | 0.002 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| 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 | 0.001 |
| 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 it