Distribution of serotypes causing invasive pneumococcal disease in older adults from high-income countries and impact of pediatric and adult vaccination policies
Bibliographic record
Abstract
BACKGROUND: Neither indirect protection through use of 13-valent and 10-valent pneumococcal conjugate vaccines (PCV13 and PCV10) in pediatric National Immunization Programs (NIPs) nor direct vaccination with the 23-valent polysaccharide vaccine have eliminated vaccine serotype invasive pneumococcal disease (IPD) in older adults. Vaccinating older adults with higher-valency PCV15 and PCV20 could address remaining IPD due to pediatric PCV serotypes plus additional IPD due to serotypes included in these vaccines. METHODS: We collected serotype-specific IPD data in older adults (≥65 years in most countries), from national or regional surveillance systems or hospital networks of 33 high-income countries. Data were from official government websites, online databases, surveillance system reports, published literature, and personal communication with in-country investigators. Average percentages of IPD serotypes were calculated. RESULTS: Among 52,905 cases of IPD with a serotype identified, PCV13 serotypes accounted for 33.7% of IPD (55.8% and 30.6% for countries with PCV10 and PCV13 in the pediatric NIP), most commonly serotypes 3 (14.9%) and 19A (7.0%). PCV15 and PCV20 would cover an additional 10.4% and 32.9% of older adult IPD beyond PCV13 serotypes (PCV10 countries: 7.7% and 23.3%; PCV13 countries: 10.6% and 34.6%). The most common of these additional serotypes were 8 (9.9%), 22F (7.9%), 12F (4.6%), and 11A (3.3%). PPSV23 policies for older adults were not correlated with lower IPD percentages due to PPSV23 serotypes. CONCLUSIONS: Vaccinating older adults with higher-valency PCVs, especially PCV20, could substantially reduce the remaining IPD burden in high-income countries, regardless of current PCV use in pediatric NIPs and adult PPSV23 policies.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".