US isolationism, HIV, and primary care integration: the inflection point for low-income and middle-income countries is now
Bibliographic record
Abstract
The abrupt withdrawal of US global health funding, including major cuts to the President's Emergency Plan for AIDS Relief and US Agency for International Development, threatens decades of advances in global HIV control and progresss towards the UN 95-95-95 target by 2025. Despite more than US$120 billion invested in Africa and 30 million people on antiretroviral therapy globally, the global HIV response remains short of the target, with 28% of those living with HIV still virally unsuppressed. As vertical HIV programmes collapse, integrating HIV services into primary health care offers a path forward. Primary health care, with its syndemic approach and infrastructure for chronic disease management, is well positioned to absorb HIV services while ensuring sustainability. Although challenges remain, especially in terms of resource reallocation and leadership, full integration is feasible, cost-effective, and aligned with universal health coverage goals. With coordinated national leadership, this funding crisis represents an opportunity to transform HIV control by integrating HIV services within resilient, sustainable, person-centred primary health-care systems capable of reaching the 95-95-95 target on the path towards achieving epidemic control, HIV elimination, and long-term health equity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 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".