Association Between Implementation of a Universal Face Mask Policy for Healthcare Workers in a Health Care System and SARS-CoV-2 Positivity Testing Rate in Healthcare Workers
Bibliographic record
Abstract
OBJECTIVE: Examine the effect of a universal facemask policy for healthcare workers (HCW) and incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity. METHODS: Daily number of symptomatic HCW tested, SARS-CoV-2 positivity rates, and HCW job-descriptions were collected pre and post Universal HCW facemask policy (March 26, 2020). Multiple change point regression was used to model positive-test-rate data. SARS-CoV-2 testing and positivity rates were compared for pre-intervention, transition, post-intervention, and follow-up periods. RESULTS: Between March 12 and August 10, 2020, 19.2% of HCW were symptomatic for COVID-19 and underwent SARS-CoV-2 testing. A single change point was identified ∼March 28-30 (95% probability). Before the change point, the odds of a tested HCW having a positive result doubled every 4.5 to 7.5 days. Post-change-point, the odds of a tested HCW having a positive result halved every 10.5 to 13.5 days. CONCLUSIONS: Universal facemasks were associated with reducing HCW's risk of acquiring COVID-19.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".