Genomic Analysis of a Serotype 5<i>Streptococcus pneumoniae</i>Outbreak in British Columbia, Canada, 2005–2009
Bibliographic record
Abstract
Background. Streptococcus pneumoniae can cause a wide spectrum of disease, including invasive pneumococcal disease (IPD). From 2005 to 2009 an outbreak of IPD occurred in Western Canada, caused by a S. pneumoniae strain with multilocus sequence type (MLST) 289 and serotype 5. We sought to investigate the incidence of IPD due to this S. pneumoniae strain and to characterize the outbreak in British Columbia using whole-genome sequencing. Methods. IPD was defined according to Public Health Agency of Canada guidelines. Two isolates representing the beginning and end of the outbreak were whole-genome sequenced. The sequences were analyzed for single nucleotide variants (SNVs) and putative genomic islands. Results. The peak of the outbreak in British Columbia was in 2006, when 57% of invasive S. pneumoniae isolates were serotype 5. Comparison of two whole-genome sequenced strains showed only 10 SNVs between them. A 15.5 kb genomic island was identified in outbreak strains, allowing the design of a PCR assay to track the spread of the outbreak strain. Discussion. We show that the serotype 5 MLST 289 strain contains a distinguishing genomic island, which remained genetically consistent over time. Whole-genome sequencing holds great promise for real-time characterization of outbreaks in the future and may allow responses tailored to characteristics identified in the genome.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".