Largest Measles Epidemic in North America in a Decade—Quebec, Canada, 2011: Contribution of Susceptibility, Serendipity, and Superspreading Events
Bibliographic record
Abstract
BACKGROUND: The largest measles epidemic in North America in the last decade, occurred in 2011 in Quebec, Canada, where rates of 1- and 2-dose vaccine coverage among children 3 years of age were 95%-97% and 90%, respectively, with 3%-5% unvaccinated. METHODS: Case patients identified through passive surveillance and outbreak investigation were contacted to determine clinical course, vaccination status, and possible source of infection. RESULTS: There were 21 measles importations and 725 cases. A superspreading event triggered by 1 importation resulted in sustained transmission and 678 cases. The overall incidence was 9.1 per 100,000; the highest incidence was in adolescents 12-17 years old (75.6 per 100,000), who comprised 56% of case patients. Among adolescents, 22% had received 2 vaccine doses. Outbreak investigation showed this proportion to have been an underestimate; active case finding identified 130% more cases among 2-dose recipients. Two-dose recipients had milder illness and a significantly lower risk of hospitalization than those who were unvaccinated or single-dose recipients. CONCLUSIONS: A chance superspreading event revealed an overall level of immunity barely above the elimination threshold when unexpected vulnerability in 2-dose recipients was taken into account. Unvaccinated individuals remain the immunization priority, but a better understanding of susceptibility in 2-dose recipients is needed to define effective interventions if elimination is to be achieved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".