Three sequential outbreaks of Group A Streptococcus over a two-year period at the Canadian Forces Leadership and Recruit School, St. Jean Garrison, Québec
Bibliographic record
Abstract
Background: Since December 2016, the basic military training (BMT) facility for the Canadian Armed Forces (CAF) has experienced repeated outbreaks of Group A Streptococcus (GAS).In 2018, a voluntary mass antibiotic prophylaxis (MAP) program was implemented to interrupt GAS transmission among recruits.The objective of this study was to describe the epidemiology of three GAS outbreaks and a period of increased pharyngitis infections at the CAF BMT facility in Québec over a two-year span, and to detail the prevention and control measures implemented to mitigate the risk to recruit health.Methods: Descriptive data were collected on invasive and severe GAS cases along with laboratory data including genotyping of throat swabs from recruits presenting with pharyngitis.A laboratory-based acute respiratory infection surveillance system was used to aid in monitoring and decision-making.Close contacts of recruits were assessed for asymptomatic GAS carriage and MAP adverse events surveillance was conducted.Results: Three distinct GAS outbreaks occurred at the Canadian Forces Leadership and Recruit School totaling eight invasive (iGAS) and 13 severe (sGAS) cases over two years.All iGAS/sGAS cases, apart from one instructor, were among recruits.The predominant strain in all three outbreaks was type emm6.4.A total of 11,293 recruits received MAP (penicillin G benzathine or azithromycin) between March 7, 2018 and November 18, 2019.There were eight reported serious adverse events related to penicillin administration. Conclusion:The CAF BMT facility experienced three GAS outbreaks over the course of two years, and despite the use of enhanced hygiene measures, only MAP has been effective in quelling these outbreaks.
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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 | 0.003 | 0.001 |
| 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".