Regional differences in pediatric pneumococcal vaccine schedules for Indigenous children in Canada: an environmental scan
Bibliographic record
Abstract
BACKGROUND: Streptococcus pneumoniae bacteria causes substantial morbidity and mortality worldwide, especially in children under 5 years of age. Prevention of these outcomes by pneumococcal conjugate vaccines (PCV) is an important public health initiative, supported by publicly funded vaccination programs in Canada. While the National Advisory Committee on Immunization (NACI) provides national recommendations for vaccination schedules, decisions on vaccination program delivery are made regionally, creating potential for variability across the country. In addition, defining the groups that are most at risk has become a complex endeavor for provinces and territories in Canada, specifically considering Indigenous children. METHODS: In this environmental scan, we reviewed policy documents, provincial/territorial and international PCV schedules, and scientific literature, and consulted with vaccination program stakeholders and experts from across the country, in order to understand the evolution of PCV vaccination guidelines and policies in Canada and identify whether and how the needs of Indigenous children are addressed. RESULTS: As of March 2023, most regions do not specify particular vaccination requirements for Indigenous children; however, three provinces identify Indigenous children as "high risk" and use varying language to recommend a four dose, rather than the routine three dose, schedule. Our results also draw attention to evidence gaps supporting a differing practice for Indigenous populations. CONCLUSIONS: Future PCV program innovation requires inclusive and clear policies as well as definitive evidence-based policies and practices in order to improve equitable population health.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".