A Prospective Observational Cohort Comparison of SARS-CoV-2 Seroprevalence Between Paramedics and Matched Blood Donors in Canada During the COVID-19 Pandemic
Bibliographic record
Abstract
STUDY OBJECTIVE: SARS-CoV-2 represents an occupational risk to paramedics, who work in uncontrolled environments. We sought to identify the occupation-specific risk to paramedics by comparing their seroprevalence of SARS-CoV-2 infection-specific antibodies to that of blood donors in Canada. METHODS: In this prospective cohort study, we performed serology testing (Elecsys Anti-SARS-CoV-2 nucleocapsid assay) on samples from paramedics and blood donors (January to July 2021) in Canada. Paramedic samples were compared to blood donor samples through 1:1-matched (based on age, sex, location, date of blood collection, and vaccination status) and raking weighted comparisons. We compared the seroprevalence with a risk difference (and 95% confidence interval [CI]) and performed secondary analyses within subgroups defined by vaccination status. RESULTS: The 1:1 match included 1,627 cases per group; in both groups, 723 (44%) were women, with a median age of 38. The raking weighted comparison included 1,713 paramedic samples and 19,515 blood donor samples, with similar characteristics. In the 1:1 match, the seroprevalence was similar (difference 1.2; 95% CI -0.20 to 2.7) between paramedics (5.2%) and blood donors (3.9%). The raking weighted comparison was consistent (difference 0.97; 95% CI -0.10 to 2.0). The unvaccinated paramedic samples, in comparison to the blood donor samples, demonstrated a higher seroprevalence in the 1:1 (difference 5.9; 95% CI 1.8 to 10) and weighted (difference 6.5; 95% CI 1.8 to 10) comparisons. Among vaccinated cases, the between-group seroprevalence was similar. CONCLUSION: Overall, paramedics demonstrated similar evidence of prior SARS-CoV-2 infection to that of blood donors. However, among unvaccinated individuals, evidence of prior infection was higher among paramedics compared to blood donors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".