Cost-utility analysis of current COVID-19 vaccination program recommendations in Canada
Bibliographic record
Abstract
Background As COVID-19 becomes established as an endemic disease with widespread population immunity, there is uncertainty about the economic benefit of ongoing COVID-19 vaccination programs. We assessed the cost-effectiveness of a COVID-19 vaccination program similar to current Canadian recommendations, modelled as annual vaccination for people aged less than 65 years with chronic medical conditions and biannual vaccination for adults aged 65 years and older. Methods Using a static individual-based model of medically attended COVID-19 in a population of one million people, we estimated costs (in 2023 Canadian dollars), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). We used health system and societal perspectives and a 1.5 % discount rate. Parameters were based on recent COVID-19 epidemiology, vaccine characteristics, and costs. Results Between July 2024 and September 2025, a program similar to current Canadian recommendations was estimated to avert 3.1 % (95 % credible interval (CrI): 3.0 to 3.2 %) of outpatient cases, 8.8 % (95 % CrI: 7.3 to 10.4 %) of inpatient cases, 3.6 % (95 % CrI: 2.8 to 4.3 %) of PCC cases, and 9.4 % (95 % CrI: 5.6 to 13.8 %) of deaths compared to no vaccination. The number needed to vaccinate to prevent one hospitalization and one death was 1121 (95 % CrI: 941 to 1357) and 8656 (95 % CrI: 5848 to 14,915), respectively. For the health system perspective, the program would cost an additional $4.695 million but result in 221.17 QALYs gained, leading to an ICER of $21,227 per QALY compared to no vaccination. Vaccine price influenced cost-effectiveness, with higher prices reducing the likelihood the program met common cost-effectiveness thresholds. Conclusions A program similar to current COVID-19 recommendations in Canada is likely effective and cost-effective compared to no vaccination. However, unlike some other research studies, alternate vaccination strategies that may offer better value for money were not evaluated.
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How this classification was reachedexpand
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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 teacher head, 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".