Consideration of Trade-offs Regarding COVID-19 Containment Measures in the United States: Implications for Canada
Bibliographic record
Abstract
The economic stimulus package in the United States, which totaled $2.48 trillion, was designed to soften the economic impact of sweeping containment measures including shelter-in-place orders that were put in place to control the COVID-19 pandemic. In healthcare, interventions are rarely justified simply in terms of the number of lives saved but also in terms of a myriad of other trade-off factors including value-for-money or cost-effectiveness. The data suggest the incremental costs per life-year gained related to the economic shutdown can span a wide range depending on the baseline number of deaths in the absence of any containment measures. The results show that in the US, under no scenario for life-years gained does the stimulus package compare favourably to other healthcare interventions that have had favourable cost-effectiveness profiles. However, when comparing value-of-statistical-life-year (VSLY) threshold measures used in other sectors, it is plausible that the stimulus package could be viewed more favourably in the US.
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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 | 0.017 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".