COVID-19 Personal Protective Equipment in the Home: Navigating the Complexity of Donning and Doffing
Bibliographic record
Abstract
PURPOSE: The safety of care professionals and patients is paramount while caring for people with infectious diseases, including those with confirmed or suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19). Existing policies and protocols for donning and doffing personal protective equipment (PPE) are primarily for institutional settings such as hospitals, not for home visits for patient care. We describe a protocol for donning and doffing PPE in home settings. METHODS: We used an iterative, rapid-prototyping approach to develop the protocol. A small workgroup created preliminary drafts, drawing on hospital-based protocols and modifying them, while undertaking simulations. Wider input was solicited via 2 webinars; 1 regional (Hamilton, Ontario) with palliative clinicians, and 1 national (Canada) with varying professions. We also consulted a group of infectious disease experts. A "how-to" video accompanies the protocol. RESULTS: Twelve versions of the protocol were produced, with major changes occurring within the first 6 versions. A national webinar mid-development provided further validation and minor modifications. Subsequent versions involved minor changes. The protocol has 4 phases: (1) Preparing, (2) Entering the Home, (3) Leaving the Home, and (4) After the Visit and Reprocessing. In addition to PPE-related equipment, the protocol requires additional materials including 2 pails for transporting supplies, plastic bags, hand sanitizer, disinfectant wipes, and printed easy-to-use checklists. CONCLUSIONS: .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.069 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".