Invasive Pneumococcal Disease in UK Children <1 Year of Age in the Post–13-Valent Pneumococcal Conjugate Vaccine Era: What Are the Risks Now?
Bibliographic record
Abstract
BACKGROUND: Invasive pneumococcal disease (IPD) has declined significantly since the introduction of pneumococcal conjugate vaccines (PCVs). It is not known whether certain infant populations remain at higher risk of IPD in countries with established 13-valent PCV (PCV13) programs. We aimed to describe the epidemiology, clinical characteristics, serotype distribution, and outcomes of IPD in infants, and to estimate the relative risk of PCV13-type, non-PCV13-type, and overall IPD in premature infants compared to term infants during a 4-year period after the PCV13 program was established. METHODS: This was a prospective, enhanced national surveillance of laboratory-confirmed IPD in England in infants aged <1 year diagnosed during 2013-2016. RESULTS: There were 517 cases of IPD (incidence: 19/100000 infants). Incidence was significantly higher in premature infants compared with those born at term (49/100000 vs 17/100000; incidence rate ratio [IRR], 2.87; P < .001), with infants born before 28 weeks' gestation having the highest incidence (150/100000; IRR, 8.8; P < .001). Of the 454 IPD cases with serotyped isolates, most were caused by non-PCV13 serotypes (369 cases, 71.4%), with 85 cases (16.4%) due to PCV13 serotypes. There were 31 deaths (case fatality rate [CFR], 6.2% [95% confidence interval, 4.3%-8.6%]). Premature infants did not have a higher CFR than term infants (P = .62). CONCLUSIONS: IPD incidence in infants remains lower than rates reported prior to PCV7 introduction in England. The risk of IPD remains significantly higher in premature infants compared to infants born at term, for both PCV13 and non-PCV13 serotypes. Any changes to the infant PCV13 immunization schedule may disproportionally affect premature infants.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".