Long-term trends in invasive pneumococcal disease in Manitoba, Canada
Bibliographic record
Abstract
Invasive pneumococcal disease (IPD) remains a significant public health problem in Manitoba, Canada although publically-funded pneumococcal conjugate (PCV7 and PCV13) and polysaccharide (PPV23) vaccination programs exist. We analyzed routine surveillance and administrative health data to examine trends in IPD rates as these vaccines were introduced. Data on all individuals with a laboratory-confirmed diagnosis of IPD between 2001 and 2014 were obtained from the provincial Communicable Diseases Surveillance database and linked with Manitoba's provincial immunization registry and physician and hospital databases. We calculated IPD incidence rates overall, by serotype and for different population subgroups defined by socio-demographic and clinical (e.g., chronic diseases, immune status) characteristics. Annual IPD incidence (95%CI) was 8.6 (8.2-9.1)/100,000 people during the study period (n = 1092), and rates were higher in recent years and in regions with predominately indigenous populations. Reduction in the incidence of serotypes included in PCV7 have been offset by rising rates of PCV13-only serotypes in children, and more recently by rising rates of PPV-only serotypes and non-vaccine serotypes among young children and older adults (≥ 65 years). Rates were 3 times higher in those with a chronic disease and highest (> 175-fold) among alcoholics, organ-transplant, and chronic kidney failure patients. The case fatality rate was 12.0% within 30 d of diagnosis. Despite the introduction of several vaccination programs, overall rates of IPD have not declined in Manitoba in the last decade, due to increase in incidence of non-PCV7 serotypes. A disproportionately high burden of disease impacts indigenous communities and people with chronic disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".