SARS-CoV-2 outbreaks in long-term care facilities during the Omicron era in Québec, Canada
Bibliographic record
Abstract
Residents of long-term care facilities (LTCFs) are at a high risk of severe COVID-19. Our study analyzed the COVID-19 outbreaks, associated cases and case fatality ratio (CFR) in LTCFs from May-2022 to September-2024 in Québec, Canada. An ecological analysis was conducted including all active LTCFs during the study period (n = 471). Regression analyses using generalized estimating equations were used to model odds of an active COVID-19 outbreak, confirmed COVID-19 cases incidence rate ratio (IRR) and ratio of CFR over different periods (wave 7, 2022-23 season, 2023-24 season), regions and LTCF bed capacity. A total of 2,501 outbreaks were recorded, corresponding to 39,089 COVID-19 cases (among residents and health care workers). The odds of an active outbreak, IRR of COVID-19 cases, and ratio of CFR declined significantly during the 2023-24 season compared to wave 7 (-35%, -39% and -24%, respectively; p-values < 0.0001). While larger LTCFs (≥ 40 beds) were up to 7 times more likely to have an active outbreak vs.10-39 beds, COVID-19 IRR and ratio of CFR were comparable across LTCFs' bed-capacity. In summary, the burden of COVID-19 on LTCF residents has declined from May 2022 to September 2024. Bed capacity seems to predict outbreak occurrence but not virus transmission within LTCFs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".