Trends in serotype distribution and disease severity in adults hospitalised with <i>Streptococcus pneumoniae</i> infection in Bristol and Bath: a retrospective cohort study, 2006-2022
Bibliographic record
Abstract
ABSTRACT Ongoing surveillance is essential to inform policy decisions and monitor serotype replacement following pneumococcal conjugate vaccination (PCV) deployment. We report serotype and disease severity trends in this retrospective cohort of hospitalised adults in Bristol-Bath, 2006-22. Of 1686 invasive pneumococcal disease (IPD) cases, 1501 (89.0%) had known serotype. We also identified 2033/3719 cases of non-IPD. IPD declined sharply during the early COVID-19 pandemic. Over 2022 it gradually returned to pre-pandemic levels. Disease severity also changed throughout this period: CURB65 severity and inpatient mortality decreased whilst ICU admissions increased. PCV7 and PCV13-serotype IPD decreased from 2006-09 to 2021-22. However, significant residual PCV13-serotype IPD remains, representing 21.7% [15.5-29.6] of 2021-22 cases, highlighting that significant adult PCV-serotype disease still occurs despite 17-years of paediatric PCV usage in the UK. We found increased proportions of serotype 3 and 8 IPD, whilst 19F and 19A re-emerged. In 2020-22, 68.2% IPD cases were potentially covered by PCV20. Article Summary We observed significant serotype shifts but perseverance and re-emergence of some serotypes covered by PCVs over this 17-year retrospective study, which found considerable adult pneumococcal disease attributable to PCV-serotypes despite high uptake of paediatric PCV.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".