The evolution of workplace risk for Covid‐19 in Canadian healthcare workers and its relation to vaccination: A nested case‐referent study
Bibliographic record
Abstract
BACKGROUND: During the early months of the Covid-19 pandemic, studies demonstrated that healthcare workers (HCWs) were at increased risk of infection. Few modifiable risks were identified. It is largely unknown how these evolved over time. METHODS: A prospective case-referent study was established and nested within a cohort study of Canadian HCWs. Cases of Covid-19, confirmed by polymerase chain reaction, were matched with up to four referents on job, province, gender, and date of first vaccination. Cases and referents completed a questionnaire reporting exposures and experiences in the 21 days before case date. Participants were recruited from October 2020 to March 2022. Workplace factors were examined by mixed-effects logistic regression allowing for competing exposures. A sensitivity analysis was limited to those for whom family/community transmission seemed unlikely. RESULTS: 533 cases were matched with 1697 referents. Among unvaccinated HCWs, the risk of infection was increased if they worked hands-on with patients with Covid-19, on a ward designated for care of infected patients, or handled objects used by infected patients. Sensitivity analysis identified work in residential institutions and geriatric wards as high risk for unvaccinated HCWs. Later, with almost universal HCW vaccination, risk from working with infected patients was much reduced but cases were more likely than referents to report being unable to access an N95 mask or that decontaminated N95 masks were reused. CONCLUSIONS: These results suggest that, after a rocky start, the risks of Covid-19 infection from work in health care are now largely contained in Canada but with need for continued vigilance.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".