The Canadian National Vaccine Safety Network: surveillance of adverse events following immunisation among individuals immunised with the COVID-19 vaccine, a cohort study in Canada
Bibliographic record
Abstract
INTRODUCTION: COVID-19 vaccines require enhanced safety monitoring after emergency approval. The Canadian National Vaccine Safety Network monitors the safety of COVID-19 vaccines and provides enhanced monitoring for healthy, auto-immune, immunocompromised, pregnant and breastfeeding populations and allows for the detection of safety signals. METHODS AND ANALYSIS: Online participant reporting of health events in vaccinated and unvaccinated individuals 12 years of age and older is captured in three surveys: 1 week after dose 1, 1 week after dose 2 and 7 months after dose 1. Medically attended events are followed up by telephone. The number, percentage, rate per 10 000 and incident rate ratios with 95% CIs are calculated by health event, vaccine type, sex and in 10-year age groups. ETHICS AND DISSEMINATION: Each study site has Research Ethics Board approvals for the project (UBC Children's & Women's, CIUSSS de l'Estrie-CHUS, Health PEI, Conjoint Health Research Ethics Board, University of Calgary and Alberta Health Services, IWK Health, Unity Health Toronto and CHU de Québec-Université Laval Research Ethics Boards). Individuals are invited to participate in this active surveillance and electronic consent is given before proceeding to each survey. Weekly reports are shared with public health and posted on the study website. At least one peer-reviewed manuscript is produced.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".