Pneumococcal Colonization and the Nasopharyngeal Microbiota of Children in Botswana
Bibliographic record
Abstract
Streptococcus pneumoniae is the predominant bacterial respiratory pathogen during childhood. Nasopharyngeal colonization precedes infections caused by S. pneumoniae. Interactions between S. pneumoniae and the nasopharyngeal microbial communities of children are poorly described. We collected nasopharyngeal swabs from 170 children 1 to 23 months of age without pneumonia in Botswana between August 2012 and June 2016. We tested these samples for common respiratory viruses and S. pneumoniae using PCR. We sequenced the V3 region of the bacterial 16S ribosomal RNA gene and used zero-inflated Gaussian distribution mixture models to compare the relative abundances of bacterial genera in children with and without S. pneumoniae colonization. Mean age was 8.3 months, and 51% were female. Ninety-six (56%) children were colonized with S. pneumoniae and 59 (35%) had one or more respiratory viruses. S. pneumoniae colonization was associated with older age (P = 0.0001). Upper respiratory symptoms were more frequent in children with S. pneumoniae colonization (60% vs. 32%; P = 0.001), even among children without respiratory viruses (50% vs. 20%; P = 0.002). Principal component analysis using Bray-Curtis distances demonstrated that nasopharyngeal samples clustered by S. pneumoniae detection (Figure 1). S. pneumoniae colonization was associated with higher relative abundances of Haemophilus, Moraxella, and Streptococcus, and lower relative abundances of Corynebacterium and Staphylococcus (Figure 2). Respiratory virus infection had no appreciable effect on the composition of the nasopharyngeal microbiota. S. pneumoniae colonization is associated with substantial alterations of the nasopharyngeal microbiota of children independent of respiratory virus co-infection. Prospective studies are needed to determine the extent to which the nasopharyngeal microbiota modifies S. pneumoniae colonization risk. All authors: No reported disclosures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".