Changing Patterns of SARS-CoV-2 Seroprevalence among Canadian Blood Donors during the Vaccine Era
Bibliographic record
Abstract
Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, our blood donor seroprevalence study has informed Canadian public health policy at national and provincial levels. We describe the only continuously running national seroprevalence study in Canada, which spans the full length of the pandemic and per capita is one of the largest programs in the world. The benefit of seroprevalence studies is that they identify a broad range of asymptomatic and symptomatic infection histories that may not be identified with active SARS-CoV-2 nucleic acid testing programs or when case definitions change. As vaccination was deployed in Canada, we estimated the proportion of donors with vaccine-related antibodies and developed population-level estimates of SARS-CoV-2 spike antibody concentrations. Monthly predictive mathematical models and our results engaged public health organizations in new ways. In the future, we intend to continue to expand on these interactions with provincial and national public health teams.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".