COVID-19 outbreaks in child care facilities Alberta from March 2020 to December 31, 2021
Bibliographic record
Abstract
Background: Children attending child care are vulnerable to SARS CoV-2 infection, and mitigationmeasures like masking, distancing, enhanced hygiene are not feasible for this population. Describingoutbreak growth during the COVID-19 pandemic in child care centres may provide insight in how to bestmitigate the risks of COVID-19 and other infectious diseases in these settings.Objective: To describe the characteristics of child care outbreaks and associated cases in Alberta.Methods: Our observational study used data on outbreaks and associated cases tracked through theAlberta Health Services Communicable Disease Outbreak Management database. We included allCOVID-19 outbreaks opened in child care facilities in the province (March 2020 to December 31, 2021).We compared the characteristics of outbreaks and cases during each wave of the pandemic.Outcome: 841 outbreaks were opened in Alberta, including 4613 cases (70.2% in children and 29.8%adults). Outbreaks averaged 5.5 cases per outbreak, and the average duration of time betweensymptoms starting in the first and last case was 9.7 days. The likely index was a child in 55.1% ofoutbreaks.Conclusions: Adults are a high proportion of cases compared to their proportion of the population atchild care facilities, and have consistently higher attack rates than children. Children have the highestattack rates when other children are the index case. Measures shown to be effective in other settings toreduce spread among adults can be implemented here, such as vaccination, strictly enforcing exclusionof those symptomatic, and facilitating rapid testing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".