Personal protective equipment preservation strategies in the covid-19 era: A narrative review
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has led to personal protective equipment (PPE) supply concerns on a global scale. While efforts to increase production are underway in many jurisdictions, demand may yet outstrip supply leading to PPE shortages, particularly in low resource settings. PPE is critically important for the safety of healthcare workers (HCW) and patients and to reduce viral transmission within healthcare facilities. A structured narrative review was completed to identify methods for extending the use of available PPE as well as decontamination and reuse. METHODS: Database searches were conducted in MEDLINE and EMBASE for any available original research or review articles detailing guidelines for the safe extended use of PPE, and/or PPE decontamination and reuse protocols prior to September 28, 2020. Grey literature in addition to key websites from the Centers for Disease Control and Prevention (CDC), World Health Organization (WHO), Infection Prevention Association of Canada (IPAC), and the National Health Service (NHS) was also reviewed. RESULTS: Extended use guidelines support co-locating patients with confirmed COVID-19 within specific areas of healthcare facilities to enable the use of PPE between multiple patients, and reduce PPE requirements outside these areas. Decontamination strategies for N95 respirators and face shields range from individual HCWs using conventional ovens and microwave steam bags at home, to large-scale centralized decontamination using autoclave machines, ultraviolet germicidal irradiation, hydrogen peroxide vapors, or peracetic acid dry fogging systems. Specific protocols for such strategies have been recommended by the US CDC and WHO and are being implemented by multiple institutions across North America. Further studies are underway testing decontamination strategies that have been reported to be effective at inactivating coronavirus and influenza, and on SARs-CoV-2 specifically. CONCLUSIONS: This narrative review summarizes current extended use guidelines and decontamination protocols specific to COVID-19. Preserving PPE through the implementation of such strategies could help to mitigate shortages in PPE supply, and enable healthcare facilities in low resource settings to continue to operate safely for the remainder of the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".