Global Pneumococcal Disease and Policies for Control
Bibliographic record
Abstract
Background and Aims: Global serotype distribution of IPD in children ≥5 years old and adults pre-pneumococcal conjugate vaccine (PCV) introduction has not been described.We aimed to estimate the proportion due to top serotypes by geographic region.Methods: A systematic literature review identified studies reporting ≥20 IPD cases with serotype/serogroup information.We estimated the proportion of IPD due to 20 serotypes: PCV13-type, 22F, 32F, and any others in the top 13 of each geographic region (8, 9N, 10A, 12F, 16F, 20D).All other serotypes were grouped.Random-effects meta-analysis was used to estimate the average serotype proportion, normalizing to 100 percent.Results: Analyses included 72,954 isolates (>3500 in each region) from children ≥5 years and adults from 77 studies in 53 countries.70% of disease was accounted for by 9 serotypes in Africa, 12 in North America, 12 in Europe, 13 in Oceania, 14 in Latin America and Caribbean and 16 in Asia.Serotype 1 or 14 was the most common in all regions.Six serotypes (3, 6B, 7F, 14, 19F, 23F) were among the top 13 in all regions.Eleven serotypes (1, 3, 4, 5, 6B, 8, 9V, 14, 19A, 19F, 23F) covered the top 5 in all regions.Vaccine serotypes accounted for >50% of IPD: regional PCV10 plus 6A coverage range=52-62%, PCV13=60-75%, PCV15=64-77%, and 19/23 serotypes in polysaccharide vaccine (PPV23)=72-87%.Conclusion: A limited set of serotypes are common in older children and adults in all regions.Serotypes in existing vaccines included >50% of IPD.PCV13 and PPV23 add approximately 10% and 24%, respectively.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".