Predicting the Epidemiological Effects in the United Kingdom of Moving from PCV13 to PCV15 in the Routine Pediatric 1 + 1 Vaccination Schedule
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Pneumococcal conjugate vaccines (PCVs) were first introduced in the pediatric UK National Immunization Programme (NIP) in 2006 and subsequently led to a significant decline in invasive pneumococcal disease (IPD). In 2020, the UK NIP reduced the pediatric PCV dosing schedule from two infant doses and one toddler dose (2 + 1) to one infant dose and one toddler dose (1 + 1). This analysis evaluated the public health impact of pediatric vaccination with PCV15 versus PCV13 under a 1 + 1 schedule. METHODS: A population-level compartmental model was previously adapted to the UK setting. The impact on the IPD incidence of vaccination with PCV15 versus PCV13 under a 1 + 1 schedule was evaluated over a 20-year time horizon. The uncertainty regarding the vaccine efficacy (VE) of PCV13 and PCV15 under a 1 + 1 schedule was investigated through a probabilistic sensitivity analysis, i.e., the PCV VE under a 1 + 1 schedule was assumed to be 0-24% lower than the PCV VE under a 2 + 1 schedule. RESULTS: Relative to the initial IPD incidence, vaccination with PCV13 and PCV15 under a 1 + 1 schedule resulted in the IPD incidence in children <2 years old increasing by 11.1% (95% region: 8.4-14.5%) and 3.5% (0.2-7.7%), respectively, over the time horizon. At the end of the time horizon, in the overall population, PCV15 would lead to a 6.0% lower IPD incidence than PCV13 (10.70 IPD cases per 100,000 versus 11.38 per 100,000, respectively). CONCLUSIONS: Switching from PCV13 to PCV15 for routine pediatric vaccinations under the 1 + 1 dosing schedule in the UK led to a lower IPD incidence in both the pediatric and overall populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".