Improved vaccine coverage for First Nations children receiving first dose on-reserve: a retrospective cohort study in western Canada
Bibliographic record
Abstract
INTRODUCTION: Fragmentation in immunisation reporting systems pose challenges in measuring vaccine coverage for First Nations children in Canada. Some Nations have entered into data-sharing agreements with the province of Alberta's health ministry, enabling novel opportunities to calculate coverage. METHODS: Partnering with a First Nations community in Alberta, this retrospective cohort study calculated routine childhood vaccine coverage. Administrative data for vaccines delivered within and outside the community were linked to calculate partial and complete immunisation coverage in 2013-2019 at ages 2 and 7 years for children living in the community. We also compared vaccine coverage each year for (a) children who were and were not continuous community residents and (b) children who received or not their first vaccine at the on-reserve community health centre. We also calculated the mean complete coverage across all study years with 95% CIs. RESULTS: For most vaccines, coverage was higher (p<0.05) at ages 2 and 7 years for children that received their first vaccine at the First Nations health centre, compared with those who received their first dose elsewhere. For example, for pneumococcal vaccine, the mean level of complete coverage in 2-year-olds was 55.7% (52.5%-58.8%) for those who received their first vaccine in the community, compared with 33.3% (29.4%-37.3%) for those who did not; it was also higher at 7 years (75.6%, 72.7%-78.5%, compared with 55.5%, 49.7%-61.3%). CONCLUSION: Initiating the vaccine series at the on-reserve community health centre had a positive impact on coverage. The ability to measure accurate coverage through data-sharing agreements and vaccine record linkage will support First Nations communities in identifying individual and community immunity. The findings also support the transfer of health funding and service delivery to First Nations to improve childhood immunisation uptake.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".