The Impact of the COVID-19 Pandemic in Long-Term Care in Canada
Bibliographic record
Abstract
The COVID-19 pandemic has disproportionately affected Canada's long-term care (LTC) sector, with residents of LTC and retirement homes accounting for 67% of all COVID-19-related deaths as of February 15, 2021. This study investigated the impact of the COVID-19 pandemic on LTC residents across Canada during the first six months of the pandemic, including how care changed for residents, using data from the Canadian Institute for Health Information's LTC and acute care databases. The results suggest that LTC residents received less medical care, with fewer physician visits and hospital transfers compared with the same period in 2019. They also had less contact with family/friends compared with the same period in 2019, which was associated with higher levels of depression. In provinces where it could be measured, the number of LTC resident deaths from all causes was higher than pre-pandemic years during the peak of the first wave, even in jurisdictions with few COVID-19-related deaths in LTC.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".