Canadian blood suppliers: An expanding role in public health surveillance?
Bibliographic record
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic galvanized blood donor seroprevalence studies, which continue to inform public health policy. We propose that the two Canadian blood suppliers, Héma-Québec and Canadian Blood Services, expand their role in public health surveillance in the post-pandemic period. Together blood suppliers have near-national reach, collecting blood donations nearly every day in all larger cities and many smaller municipalities. Blood donors are a healthy subset of the general population. Demographic data, routine infectious disease testing and screening questionnaire data are collected for all donations. Close to one million blood samples per year could be made available for surveillance. With 90% repeat donors, longitudinal sampling is possible. Current blood donor surveillance includes monitoring infectious marker rates in low risk (e.g. HIV, hepatitis C virus) or asymptomatic (e.g. West Nile virus) populations, and ad hoc studies to monitor transfusion-transmissible infections. These include tick-borne infections such as Babesia microti and foodborne infections such as hepatitis E. Canadian Blood Services and Héma-Québec are actively seeking to engage with public health professionals to further develop a role in public health surveillance.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".