Streptococcus pneumoniae Carriage in the Gaza Strip
Bibliographic record
Abstract
BACKGROUND: Pneumococcal infections cause major morbidity and mortality in developing countries. We report the epidemiology of S. pneumoniae carriage in a developing region, the Gaza strip, and evaluate the theoretical coverage of carriage strains by pneumococcal conjugate vaccines (PCVs). METHODOLOGY: In 2009 we conducted a cross-sectional survey of S. pneumoniae carriage in healthy children and their parents, living throughout the Gaza strip. Data were collected and nasopharyngeal swabs were obtained. Antibiotic susceptibilities were determined by Vitek-2 and serotypes by the Quellung reaction. PRINCIPAL FINDINGS: S. pneumoniae carriage was detected in 189/379 (50%) of children and 30/376 (8%) of parents. Carriage prevalence was highest in children <6 months of age (63%). Significant predictors for child carriage were number of household members and DCC attendance. The proportion of pediatric and adults isolates with serotypes included in PCV7 were 32% and 20% respectively, and 46% and 33% in PCV13 respectively. The most prominent non-vaccine serotypes (NVT) were 35B, 15B/C and 23B. Penicillin-nonsusceptible strains were carried by 70% of carriers, penicillin-resistant strains (PRSP) by 13% and Multi-drug-resistant (MDR) by 30%. Of all PRSP isolates 54% belonged to serotypes included in PCV7 and 71% in the PCV13. Similarly, 59% and 73% of MDR-SP isolates, would theoretically be covered by PCV7 and PCV13, respectively. CONCLUSIONS: This study demonstrates that, PCV13-included strains were carried by 46% and 33% of pediatric and adult subjects respectively. In the absence of definitive data regarding the virulence of the NVT strains, it is difficult to predict the effect of PCVs on IPD in this region.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".