The funding landscape for HIV in Asia and the Pacific
Bibliographic record
Abstract
INTRODUCTION: Despite recent and robust economic growth across the Asia-Pacific region, the majority of low- and middle-income countries in the region remain dependent on some donor support for HIV programmes. We describe the availability of bilateral and multilateral official development assistance (ODA) for HIV programmes in the region. METHODS: The donor countries considered in this analysis are Australia, Canada, Denmark, France, Germany, Netherlands, Norway, Sweden, the United Kingdom and the United States. To estimate bilateral and multilateral ODA financing for HIV programmes in the Asia-Pacific region between 2004 and 2013, we obtained funding data from the Organisation for Economic Co-operation and Development Creditor Reporting System database. Where possible, we checked these amounts against the funding data available from government aid agencies. Estimates of multilateral ODA financing for HIV/AIDS were based on the country allocations announcement by the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund) for the period 2014 to 2016. RESULTS: Countries in the Asia-Pacific region receive the largest share of aid for HIV from the Global Fund. Bilateral funding for HIV in the region has been relatively stable over the last decade and is projected to remain below 10% of the worldwide response to the epidemic. Bilateral donors continue to prioritize ODA for HIV to other regions, particularly sub-Saharan Africa; Australia is an exception in prioritizing the Asia-Pacific region, but the United States is the bilateral donor providing the greatest amount of assistance in the region. Funding from the Global Fund has increased consistently since 2005, reaching a total of US$1.2 billion for the Asia-Pacific region from 2014 to 2016. CONCLUSIONS: Even with Global Fund allocations, countries in the Asia-Pacific region will not have enough resources to meet their epidemiological targets. Prevention funding is particularly vulnerable and requires greater domestic leadership and coordination. Bilateral donors are still crucially important in the response to HIV throughout the Asia-Pacific region.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".