Evaluating the cost-effectiveness of COVID-19 mRNA primary-series vaccination in Qatar: An integrated epidemiological and economic analysis
Bibliographic record
Abstract
Qatar implemented a mass primary-series vaccination campaign to mitigate the impact of the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to retrospectively evaluate the cost-effectiveness of this program both before and after onset of the omicron wave. An economic evaluation was conducted from the public healthcare system perspective between January 5, 2021, and September 18, 2023. Cost-effectiveness was determined using an epidemiological retrospective cohort study and health economic modeling that compared the cohort of individuals who received two vaccine doses with the unvaccinated cohort with respect to incidence of infection, incidence of severe COVID-19 forms, quality-adjusted life years (QALYs), and medical costs. During the pre-omicron phase, primary-series vaccination incurred an additional cost of $104,422,358, led to a gain of 724.7 QALYs, and savings of $54,790,858 in direct medical costs. The incremental cost-effectiveness ratio (ICER) was $68,485 per QALY gained. The number needed to vaccinate was 35.4 individuals (95% CI: 24.4-49.9) to prevent one infection and 718.0 individuals (95% CI: 469.4-984.0) to prevent one severe COVID-19 outcome. The cost per infection averted was $3,180 (95% CI: $2,189-$4,484) and per severe COVID-19 outcome averted was $64,468 (95% CI: $42,146-$88,354). Vaccination of individuals ≥50 years of age, those more clinically vulnerable to severe COVID-19, and those with multiple coexisting conditions was substantially more cost-effective. Cost-effectiveness of primary-series vaccination was substantially reduced during the omicron phase, but vaccination remained cost-effective. Sensitivity analyses confirmed the findings. Primary-series vaccination was cost-effective with an ICER below the 1 GDP per capita threshold during the pre-omicron phase and within the 1-3 GDP per capita thresholds during the omicron phase. Targeted vaccination strategies for those most vulnerable to COVID-19 were the most cost-effective and remained essential, even in situations of moderate vaccine effectiveness or reduced infection severity.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".