Description of COVID-19 outbreaks in childcare facilities in Alberta, March 2020 to December 31, 2021
Bibliographic record
Abstract
Background: Children attending childcare are vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and mitigation measures such as masking, distancing, enhanced hygiene are not feasible for this population. Describing outbreak growth during the coronavirus disease 2019 (COVID-19) pandemic in childcare centres may provide insight into how to best mitigate the risks of COVID-19 and other infectious diseases in these settings. This article describes the childcare outbreaks and associated cases in Alberta at different time periods throughout the pandemic. Methods: Our observational analysis used data on outbreaks and associated cases tracked through the Alberta Health Services Communicable Disease Outbreak Management database. We included all COVID-19 outbreaks opened in childcare facilities (March 2020 to December 31, 2021). We compared the characteristics of outbreaks and cases during each wave of the pandemic. Results: There were a total of 841 childcare outbreaks, including 4,613 cases (70.2% in children and 29.8% adults). Many characteristics of outbreaks and cases varied across pandemic waves, including attack rates (12.1%-28.7% in adults and 5.8%-16.3% in children), percent of cases in children (56.4%-77.3%), and percent of outbreaks with a child index case (34.0%-70.1%). The overall average cases/outbreak was 5.5 (range: 1-68), and case examples of large outbreaks showed that delaying testing and attending daycare while symptomatic seemed to drive higher transmission. Conclusion: Waves had different outbreak and case characteristics, for both adults and children. Transmission may happen more readily among adults and among children than between those two groups. Measures shown to be effective to reduce transmission in other settings can be implemented here, such as vaccination, strictly enforcing the exclusion of those symptomatic, and facilitating rapid testing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 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".