Epidemiology of serogroup B invasive meningococcal disease in Ontario, Canada, 2000 to 2010
Bibliographic record
Abstract
BACKGROUND: Invasive meningococcal disease (IMD) caused by serogroup B is the last major serogroup in Canada to become vaccine-preventable. The anticipated availability of vaccines targeting this serogroup prompted an assessment of the epidemiology of serogroup B disease in Ontario, Canada. METHODS: We retrieved information on confirmed IMD cases reported to Ontario's reportable disease database between January 1, 2000 and December 31, 2010 and probabilistically-linked these cases to Public Health Ontario Laboratory records. Rates were calculated with denominator data obtained from Statistics Canada. We calculated a crude number needed to vaccinate using the inverse of the infant (<1 year) age-specific incidence multiplied by expected vaccine efficacies between 70% and 80%, and assuming only direct protection (no herd effects). RESULTS: A total of 259 serogroup B IMD cases were identified in Ontario over the 11-year period. Serogroup B was the most common cause of IMD. Incidence ranged from 0.11 to 0.27/100,000/year, and fluctuated over time. Cases ranged in age from 13 days to 101 years; 21.4% occurred in infants, of which 72.7% were <6 months. Infants had the highest incidence (3.70/100,000). Case-fatality ratio was 10.7% overall. If we assume that all infant cases would be preventable by vaccination, we would need to vaccinate between 33,784 and 38,610 infants to prevent one case of disease. CONCLUSIONS: Although rare, the proportion of IMD caused by serogroup B has increased and currently causes most IMD in Ontario, with infants having the highest risk of disease. Although serogroup B meningococcal vaccines are highly anticipated, our findings suggest that decisions regarding publicly funding serogroup B meningococcal vaccines will be difficult and may not be based on disease burden alone.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".