What does sustainability mean in the HIV and AIDS response?
Bibliographic record
Abstract
Immense progress has been made in the fight against HIV and AIDS. Achieving and exceeding the AIDS targets for the Millennium Development Goals (MDGs) was accomplished, in large part, due to an unprecedented financial investment from the international community. Following an $800 million dip in donor disbursements in 2010, the discourse has since shifted to the need for greater sustainability of funding. But what does sustainability mean? Current efforts focus heavily on fiscal imperatives such as increasing domestic funding. This is important - needs are increasing at a faster rate than donor funding, especially with increased treatment coverage. The problem is that measures of financial sustainability tell very little about the actual sustainability of specific programmes, disease trajectories or enabling environments. Recognising that current definitions of sustainability lack clarity and depth, we offer a new six-tenet conceptualisation of what sustainability means in the HIV and AIDS response: (1) financial, (2) epidemiological, (3) political, (4) structural, (5) programmatic, and (6) human rights. Based on these, we examine examples of donor transitions for their approach to sustainability, including PEPFAR in South Africa, the Global Fund in Eastern Europe, and the Bill and Melinda Gates Foundation in India (Avahan). We conclude that sustainability must be understood within a broader framework beyond funding stability. We also recommend that certain interventions, such as programming for key populations, may have to continue to receive external support even if affected countries can afford to pay.
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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 | 0.027 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.052 |
| Scholarly communication | 0.026 | 0.030 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".