Factors Associated with SARS-CoV-2 Infection before Vaccination among European Health Care Workers
Bibliographic record
Abstract
BACKGROUND: Health care workers (HCWs) were on the frontline of the current pandemic. We aimed at identifying determinants of SARS-CoV-2 infection and the effectiveness of personal protection equipment (PPE) worn by HCWs before vaccination. METHODS: We abstracted data on SARS-CoV-2 infection based on positive PCR results and sociodemographic characteristics of 38,793 HCWs from public hospitals and public health authorities from 10 European centers. We fitted cohort-specific multivariate logistic regression models to identify determinants of infection and combined the results using random-effects meta-analyses. RESULTS: The overall prevalence of infection before vaccination among HCWs was 9.58%. Infection was associated with the presence of selected symptoms; no association was found between sociodemographic factors and increased risk of infection. The use of PPE and particularly FFP2/FFP3 masks had a different protective effect during the first and second waves of the COVID pandemic. CONCLUSIONS: The study provides evidence that mask use was the most effective PPE in preventing SARS-CoV-2 infection among HCWs.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".