Invasive group A streptococcal (iGAS) surveillance in Island Health, British Columbia, 2022
Bibliographic record
Abstract
Background: Invasive group A streptococcal disease (iGAS) is caused by Streptococcus pyogenes group A bacteria.In 2022, multiple disease alerts for iGAS in the Island Health region, in the context of increased infections in the paediatric population in Europe and the United States, prompted further investigation into local trends.This surveillance study summarizes epidemiological trends of iGAS in the region covered by Island Health, a regional health authority in British Columbia, in 2022.Methods: In British Columbia, iGAS is a reportable disease; all confirmed cases are reported to the regional authority and the provincial health authority (BC Centre for Disease Control).Island Health's iGAS surveillance system is passive and collects information on cases that are identified through laboratory testing.Surveillance data were summarized for 2022 and compared with historical data from 2017-2021.Results: In 2022, the incidence rate was 11.4 cases per 100,000 population (n=101), the highest observed rate in the last six years.The median age of cases was 53 years, with a range of 0-96 years, and 64% of cases were male.The highest risk of infection was reported in men 40-59 years of age, with an incidence rate of 21.3 cases per 100,000 population.The most common emm types were emm92 (n=14), emm49 (n=13), and emm83 (n=12).Overall, 85% (n=86) of cases were hospitalized, 21% (n=21) were admitted to the intensive care unit, and 6% (n=6) died.Conclusion: This study highlights that the incidence of iGAS in the Island Health region continued to increase throughout the coronavirus disease 2019 (COVID-19) pandemic, reaching its highest annual rate in 2022.In contrast to reports from Europe and the United States, there was no notable increase in infections in the paediatric population.Given the sustained increase in iGAS activity, continued monitoring and description of the epidemiology of these cases on a regular basis is imperative.
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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 | 0.002 |
| 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".