Group A streptococcal infections in Alberta, Canada 2018–2023
Bibliographic record
Abstract
Abstract Group A streptococcal or Streptococcus pyogenes infections have been increasing post-COVID-19 pandemic. We describe the epidemiology of S. pyogenes pharyngitis and invasive disease in Alberta, Canada 2018–2023. Positive pharyngitis specimens were identified from throat swabs collected from pharyngitis patients. Invasive S. pyogenes was defined as the isolation of S. pyogenes from a normally sterile site or severe skin infection. S. pyogenes isolates were emm typed. Pharyngitis and invasive disease displayed seasonal trends preceding the COVID-19 pandemic followed by a sharp decrease during COVID-19 intervention measures. After the lifting of interventions, rates of pharyngitis and invasive disease rose. There were 182 983 positive pharyngitis specimens between 2018 and 2023 for a positivity rate of 17.6%. The highest rates occurred in the 0–9 age group in 2023 (41.5%). Invasive disease increased in 2022–2023 driven by emm1 and 12 types. M1UK strain was the most frequent M1 type associated with invasive disease (59% of M1 isolates sequenced). Notably, out of 182 983 pharyngitis cases, there were 111 cases of invasive S. pyogenes detected for an invasive disease rate of 0.06%. This descriptive epidemiology of S. pyogenes pharyngitis and invasive S. pyogenes disease highlights the rapid increase in cases of S. pyogenes occurring in western Canada and illustrates the critical need for a vaccine.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".