Epidemiology of invasive pneumococcal and Haemophilus influenzae diseases in Northwestern Ontario, Canada, 2010–2015
Bibliographic record
Abstract
INTRODUCTION: North American indigenous populations experience a high burden of invasive bacterial infections. Because Streptococcus pneumoniae and Haemophilus influenzae have multiple antigenic variants, the existing vaccines cannot prevent all cases. This study addresses the current epidemiology of invasive H. influenzae and pneumococcal disease (IPD) in a region of Northwestern Ontario, Canada with a relatively high (82%) indigenous population. METHODS: Data were retrieved from a retrospective chart review at a hospital servicing a population of 29000 (82% indigenous), during January 2010-July 2015. RESULTS: Ten cases of invasive H. influenzae disease and 37 cases of IPD were identified. The incidence of both in the study population (6.3 and 23.1/100000/year, respectively) exceeded national rates (1.6 and 9.0/100000/year). H. influenzae serotype a (Hia) was the most common (50%), followed by non-typeable H. influenzae (20%). In adults, 77% of IPD cases were caused by serotypes included in the 23-valent pneumococcal polysaccharide vaccine. All paediatric IPD cases were caused by serotypes not included in the 13-valent pneumococcal conjugate vaccine. The case-fatality rate was 10% for invasive H. influenzae and 2.7% for IPD. Most cases exhibited substantial co-morbidity. CONCLUSIONS: In Northwestern Ontario, the incidence of invasive Hia disease exceeds that of H. influenzae type b (Hib) in the pre-Hib vaccine era. This provides strong support for the development of a new Hia vaccine. Improved pneumococcal vaccination of high-risk adults in the region is warranted.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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".