2701. The Impact of Infant 13-valent Conjugate Pneumococcal Vaccination Program on Invasive Pneumococcal Disease in Children in British Columbia, Canada
Bibliographic record
Abstract
Abstract Background A significant reduction in invasive pneumococcal disease (IPD) has been reported following implementation of the 7-valent pneumococcal conjugate vaccine (PCV7) infant immunization program, but not much has been reported after introduction of the 13-valent vaccine (PCV13). This study represents the effect of PCV13 on IPD in British Columbia, Canada over a 14 year period (2002–2015). Methods Using provincial IPD laboratory surveillance data, we calculated the annual incidence following implementation of PCV7 (September 2004), and PCV13 (September 2010) in children less than 17 years of age. We also compared incidence rate ratios (IRR) against pre-PCV13 (2004–2010) and pre-PCV7 (2002–2003) baselines for overall and age-specific IPD rates using Poisson regression. Results A total of 697 cases were reported over the 14 year period. The overall annual incidence decreased from 10.9 cases per 100,000 population in 2002 to 4.64 cases per 100,000 population in 2015. While overall decline of IPD was 59% (IRR 0.41; 95% CI: 0.35–0.51) compared with baseline, this reduction was greatest after introduction of PCV7 (IRR 0.44; 95% CI: 0.37–0.53); the incremental change after introduction of PCV13 was non-significant (IRR 0.94; 95% CI: 0.78–1.13). The greatest reduction in IPD was in children <2 years of age (PCV13 vs baseline: IRR 0.19; 95% CI: 0.14–0.25), followed by children 3–5 years of age (PCV13 vs baseline: IRR 0.34; 95% CI: 0.21–0.56); no significant change was observed in 6–17 year olds. Conclusion While IPD rates have been significantly reduced since the introduction of the PCV vaccines, the impact of the additional 6 serotypes in the PCV13 vaccine is non-significant. Disclosures All authors: No reported disclosures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".