Estimating background rates of Guillain-Barré Syndrome in Ontario in order to respond to safety concerns during pandemic H1N1/09 immunization campaign
Bibliographic record
Abstract
BACKGROUND: The province of Ontario, Canada initiated mass immunization clinics with adjuvanted pandemic H1N1 influenza vaccine in October 2009. Due to the scale of the campaign, temporal associations with Guillain-Barré syndrome (GBS) and vaccination were expected. The objectives of this analysis were to estimate the number of background GBS cases expected to occur in the projected vaccinated population and to estimate the number of additional GBS cases which would be expected if an association with vaccination existed. The number of influenza-associated GBS cases was also determined. METHODS: Baseline incidence rates of GBS were determined from published Canadian studies and applied to projected vaccine coverage data to estimate the expected number of GBS cases in the vaccinated population. Assuming an association with vaccine existed, the number of additional cases of GBS expected was determined by applying the rates observed during the 1976 Swine Flu and 1992/1994 seasonal influenza campaigns in the United States. The number of influenza-associated GBS cases expected to occur during the vaccination campaign was determined based on risk estimates of GBS after influenza infection and provincial influenza infection rates using a combination of laboratory-confirmed cases and data from a seroprevalence study. RESULTS: The overall provincial vaccine coverage was estimated to be between 32% and 38%. Assuming 38% coverage, between 6 and 13 background cases of GBS were expected within this projected vaccinated cohort (assuming 32% coverage yielded between 5-11 background cases). An additional 6 or 42 cases would be expected if an association between GBS and influenza vaccine was observed (assuming 32% coverage yielded 5 or 35 additional cases); while up to 31 influenza-associated GBS cases could be expected to occur. In comparison, during the same period, only 7 cases of GBS were reported among vaccinated persons. CONCLUSIONS: Our analyses do not suggest an increased number of GBS cases due to the vaccine. Awareness of expected rates of GBS is crucial when assessing adverse events following influenza immunization. Furthermore, since individuals with influenza infection are also at risk of developing GBS, they must be considered in such analyses, particularly if the vaccine campaign and disease are occurring concurrently.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".