Two-year retrospective review of costs associated with COVID-19 case management in Regina, Saskatchewan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic, declared in March 2020, caused significant morbidity and mortality globally. This study aims to estimate the costs associated with managing COVID-19 infected patients in Regina. METHOD: The study focuses on the direct and indirect healthcare costs of managing a COVID-19 case. Costing elements included are diagnostic, public health, inpatient and outpatient management costs. The costing analysis estimates the total cost of COVID-19 case management in Regina, the average cost per case based on disease severity, and the costs for diagnostics, public health management, and clinical areas. RESULTS: Severe cases, representing 1.3% of cases, accounted for a quarter of the total cost of illness, while moderate cases (1.8%) contributed to less than 5% of the overall cost. Mild cases (96.9%) were responsible for three-quarters of the associated illness costs. Over two years, approximately $85 million was spent on the care of 28,733 cases, primarily due to hospitalization costs. Annual per-patient expenses increased from $45 in 2020 to $183 in 2021, reflecting a higher case burden and greater health care utilization. Furthermore, the Omicron variant accounted for 44% of the disease burden and 36% of the illness costs. Patients older than 80 accounted for 10% of illness costs, while children aged less than 18 accounted for about 17%. CONCLUSION: The primary costs were human resources and hospitalizations for older individuals, significantly impacting the Saskatchewan Health Authority's budget due to the pandemic. This analysis does not fully capture the effects in Regina.
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| 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 it