Characterising COVID-19 school and childcare outbreaks in Canada in 2021: a surveillance study
Bibliographic record
Abstract
Background: In January 2021, the Public Health Agency of Canada launched the Canadian COVID-19 Outbreak Surveillance System to monitor outbreaks by setting. Schools and childcare centres were identified as settings of interest, as children play a key role in the transmission chain of other respiratory illnesses. This paper describes outbreak trends observed in school and childcare settings from January to December 2021 when many public health measures were in place. Methods: School and childcare outbreak data from five jurisdictions were included, representing 76% of the total Canadian population. Epidemiological curves were generated, trends in outbreak settings and cases' age distribution over time were examined and descriptive statistics on outbreak size were calculated. Results: In 2021, most school and childcare outbreaks were in primary schools (42%). Severity was low in school and childcare settings (0.40% of outbreak cases hospitalised, <0.01% of outbreak cases deceased). Most school and childcare outbreaks reported fewer than 10 cases per outbreak. During the start of the 2021-2022 school year (September 2021), there were fewer outbreaks in secondary schools and fewer cases among those aged 12+ years compared with January-June of 2021. Conclusion: During the study period, there was no observed association between an increase in school and childcare outbreaks and an increase in incidence rates in community case data. Children remain a population of interest for SARS-CoV-2; however, severity in paediatric populations remained low throughout 2021 and the risk of transmission in Canadian schools was low.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".