Canadian vaccine safety surveillance reports following immunization with seasonal influenza vaccines, 2021–2022
Bibliographic record
Abstract
Background: Seasonal influenza vaccines (SIV) authorized for use in Canada have all undergone rigorous regulatory assessments for safety and effectiveness. Serious adverse events following immunization (AEFI) can occur, though they are rare. Continuous safety surveillance of vaccines during the post-marketing phase is a critical component of vaccination programs. This enables the detection of rare, late onset, or unexpected adverse events. An updated safety summary following the introduction of any new vaccines and/or formulations to immunization programs is necessary for refining the risk-benefit profile of a specific vaccine and maintaining public confidence. Here we provide an updated safety summary for SIVs distributed during the 2021/2022 influenza season from AEFI reports submitted to the Canadian Adverse Event Following Immunization Surveillance System (CAEFISS) and the Canadian Vigilance Database (CVD). Methods: We searched CAEFISS and CVD for individuals who were vaccinated with a SIV between October 1, 2021, and March 31, 2022. Descriptive statistics were calculated, including median age of vaccinated individuals, vaccines co-administered with SIV, and the most frequently reported AEFIs. Crude AEFI reporting rates were calculated by severity of the AEFI report, and SIV-type using doses distributed data. Medical reviews were conducted for reports including death, serious events (or outcomes) after SIV were administered alone, and selected adverse events (i.e., anaphylaxis, Guillain-Barré syndrome, febrile seizures, oculo-respiratory syndrome). Disproportionality analysis was used to identify potential safety signals among SIV and AEFI pairs. Results: There were 448 AEFI reports, with most AEFI classified as non-serious events (84.2%). The majority of reports described vaccination in adults at least 65 years of age (38.6%). The most frequently reported AEFIs were vaccination site pain, urticaria, pyrexia and rash. Medical review of AEFI reports did not find any evidence that reported deaths were related to vaccination with SIV. Among serious reports, nervous system disorders were the most commonly reported medical conditions. A higher number of events related to vaccination errors were also identified using disproportionality analysis. Conclusion: Findings from our analysis of reports to CAEFISS and CVD following vaccination with SIV are consistent with the known safety profile of SIVs distributed during the 2021/2022 influenza season. The majority of reports were non-serious with the most common AEFI symptoms occurring at the vaccination site or systemic symptoms that were self-limiting. The majority of vaccination error reports involved the administration of the vaccine at an inappropriate site, although no serious AEFIs were reported.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".