Economic evaluation of HIV testing options for low-prevalence high-income countries: a systematic review
Bibliographic record
Abstract
INTRODUCTION: This study reviewed the economic evidence of rapid HIV testing versus conventional HIV testing in low-prevalence high-income countries; evaluated the methodological quality of existing economic evaluations of HIV testing studies; and made recommendations on future economic evaluation directions of HIV testing approaches. METHODS: A systematic search of selected databases for relevant English language studies published between Jan 1, 2001, and Jan 30, 2019, was conducted. The methodological design quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) and the Drummond tool. We reported the systematic review according to the PRISMA guidelines. RESULTS: Five economic evaluations met the eligibility criteria but varied in comparators, evaluation type, perspective, and design. The methodologic quality of the included studies ranged from medium to high. We found evidence to support the cost-effectiveness of rapid HIV testing approaches in low-prevalence high-income countries. Rapid HIV testing was associated with cost per adjusted life year (QALY), ranging from $42,768 to $90,498. Additionally, regardless of HIV prevalence, rapid HIV testing approaches were the most cost-effective option. CONCLUSIONS: There is evidence for the cost-effectiveness of rapid HIV testing, including the use of saliva-based testing compared to usual care or hospital-based serum testing. Further studies are needed to draw evidence on the relative cost-effectiveness of the distinct options and contexts of rapid HIV testing.
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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 | 0.029 | 0.117 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".