Value Added by the Prevnar 13 Childhood Immunization Program in Alberta, Canada (2010–2015)
Bibliographic record
Abstract
BACKGROUND: Streptococcus pneumoniae is a pathogen causing acute respiratory infections, as well as meningitis and bacteremia. The province of Alberta, Canada, began vaccinating infants against seven S. pneumoniae serotypes in 2002 using Prevnar 7 (PCV7). However, a 13-valent conjugate vaccine (PCV13) was introduced in 2010 to address changes in the distribution of serotypes causing disease. PCV13 targets 13 serotypes including six additional serotypes to the previously adopted PCV7. OBJECTIVE: In this study, we estimate the impact of the new PCV13 immunization program on the burden of disease and related healthcare costs in Alberta. METHODS: Serotype-specific passive surveillance invasive pneumococcal disease (IPD) data were drawn from the Alberta Public Health Laboratory. These data were used to estimate average annual IPD incidence of the six additional serotypes included in PCV13 during the PCV7 era (2000-2009), and after the introduction of PCV13 (2011-2015). The difference in estimated cases pre-/post-PCV13 was used to estimate associated changes in direct health service costs. RESULTS: Following the replacement of PCV7 with PCV13 in 2010, the number of cases of IPD caused by the additional serotypes contained in PCV13 has declined significantly across all ages. The expected number of IPD cases prevented annually is an estimated 1.6 per 100,000. Direct health service costs are expected to be averted as a result of the implementation of PCV13 universal vaccination in Alberta. Indirect benefits are experienced by ages >20 years as IPD incidence significantly declines following the PCV13 infant immunization in Alberta. CONCLUSION: The impact on direct healthcare costs of replacing PCV7 with PCV13 in Alberta's public immunization program are estimated to be CAN$3.5 million as of 2015.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".