1446. Correlation Between Adult Invasive and Noninvasive <i>Streptococcus pneumoniae</i> Disease in 13-Valent Pneumococcal Conjugate Vaccine Serotypes in the United States
Bibliographic record
Abstract
It is often assumed that there is correlation of Streptococcus pneumoniae (Sp) serotype distribution between invasive (INV) and non-invasive (N-INV) disease. This retrospective analysis assessed the correlations of the 13-Valent Pneumococcal Conjugate Vaccine serotypes (PCV13-type) between INV and N-INV diseases in US adults during 2009–2016. For INV and N-INV pneumonia, we used a bank of Sp isolates from the SENTRY Antimicrobial Surveillance Program, where 105 centers across 40 states and nine US Census regions collected isolates from sterile or nonsterile respiratory specimen types from consecutive patients with pneumonia (one per patient). The official online US Active Bacterial Core (ABC) surveillance database for Sp was used for INV pneumococcal disease (IPD); ABCs conducts active surveillance in selected counties across 10 states in United States. Of 6,508 Sp isolates obtained from adults from the SENTRY database, 15% were from invasive pneumonia (mainly blood cultures). In 2009, PCV13 serotypes accounted for 55 and 37% of INV and N-INV pneumococcal pneumonia; in 2016, they accounted for 25 and 23%, respectively. Between 2009 and 2016, ABC reported 23,704 IPD cases in adults ≥18 years; PCV13 serotypes accounted for 53% in 2009 and 25% of IPD in 2016. The correlations between IPD (ABC) with INV pneumonia (SENTRY) and N-INV pneumonia (SENTRY) were: 0.937 and 0.973 (both P < 0.01), respectively (Table 1). The proportion of IPD and N-INV pneumonia due to vaccine serotypes decreased consistently and monotonically until 2014 and then plateaued (Figure 1). We found a strong correlation between databases (SENTRY and ABC) and between INV and N-INV pneumococcal disease in the proportion of disease due to PCV13 types. Our findings would need to be confirmed at the individual serotype level. The observed decrease in PCV13-type disease through 2014 is compatible with herd effect from PCV13 vaccination in children. The plateau suggests remaining disease that may be addressed by direct vaccination of adults. Surveillance of IPD alone could guide some policy on PCV13-type pneumococcal pneumonia. J. A. Suaya, A. G. Arguedas, D. L. Swerdlow, Pfizer Inc.: Employee and Shareholder, Salary. R. E. Mendes, Merck: Research Contractor, Research support. J. Vojicic, Pfizer: Employee and Shareholder, Benefits and stock and Salary. R. E. Isturiz, Pfizer, Inc: Employee and Shareholder, Salary and Stock & Stock Options. B. D. Gessner, Pfizer Inc.: Employee and Shareholder, Salary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".