Spending of HIV resources in Asia and Eastern Europe: systematic review reveals the need to shift funding allocations towards priority populations
Bibliographic record
Abstract
INTRODUCTION: It is increasingly important to prioritize the most cost-effective HIV interventions. We sought to summarize the evidence on which types of interventions provide the best value for money in regions with concentrated HIV epidemics. METHODS: We conducted a systematic review of peer-reviewed and grey literature reporting measurements of cost-effectiveness or cost-benefit for HIV/AIDS interventions in Asia and Eastern Europe. We also collated HIV/AIDS spending assessment data from case-study countries in the region. RESULTS: We identified 91 studies for inclusion, 47 of which were from peer-reviewed journals. Generally, in concentrated settings, prevention of mother-to-child transmission programmes and prevention programmes targeting people who inject drugs and sex workers had lower incremental cost-effectiveness ratios than programmes aimed at the general population. The few studies evaluating programmes targeting men who have sex with men indicate moderate cost-effectiveness. Collation of prevention programme spending data from 12 countries in the region (none of which had generalized epidemics) indicated that resources for the general population/non-targeted was greater than 30% for eight countries and greater than 50% for five countries. CONCLUSIONS: There is a misalignment between national spending on HIV/AIDS responses and the most affected populations across the region. In concentrated epidemics, scarce funding should be directed more towards most-at-risk populations. Reaching consensus on general principles of cost-effectiveness of programmes by epidemic settings is difficult due to inconsistent evaluation approaches. Adopting a standard costing, impact evaluation, benefits calculation, analysis and reporting framework would enable cross comparisons and improve HIV resource prioritization and allocation.
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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 | 0.036 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".