Cost-effectiveness of voluntary HIV screening in Russia
Bibliographic record
Abstract
Russia has one of the world's fastest growing HIV epidemics, and HIV screening has been widespread. Whether such screening is an effective use of resources is unclear. We used epidemiologic and economic data from Russia to develop a Markov model to estimate costs, quality of life and survival associated with a voluntary HIV screening programme compared with no screening in Russia. We measured discounted lifetime health-care costs and quality-adjusted life years (QALYs) gained. We varied our inputs in sensitivity analysis. Early identification of HIV through screening provided a substantial benefit to persons with HIV, increasing life expectancy by 2.1 years and 1.7 QALYs. At a base-case prevalence of 1.2%, once-per-lifetime screening cost $13,396 per QALY gained, exclusive of benefit from reduced transmission. Cost-effectiveness of screening remained favourable until prevalence dropped below 0.04%. When HIV-transmission-related costs and benefits were included, once-per-lifetime screening cost $6910 per QALY gained and screening every two years cost $27,696 per QALY gained. An important determinant of the cost-effectiveness of screening was effectiveness of counselling about risk reduction. Early identification of HIV infection through screening in Russia is effective and cost-effective in all but the lowest prevalence groups.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".