Is Affordability and Accessibility All It Takes?
Bibliographic record
Abstract
The Affordable Medicine Facility – malaria (AMFm) was a pilot project established to subsidize quality-assured artemisinin-based combination therapies (QAACTs) in eight malaria-endemic African regions: Kenya, Uganda, Ghana, Niger, Nigeria, Madagascar, Tanzania (mainland) and Zanzibar. The objectives of the program were to increase the affordability and availability of artemisimin-based combination therapies (ACT), as well as the market share relative to other less effective antimalarial medicines. Overall, the AMFm program had a greater impact in the private-for-profit sector than the public sector. In general, public services do not work as well as their private counterparts in most countries. Inadequate services in remote areas necessitate prohibitively long journeys to access resources and care. In general, the private sector was able to provide supplies of ACTs, as long as it was profitable. Seven countries showed significant increases in availability in the private sector, six regions had significant decreases in QAACT cost, with declines ranging from $1.28 to $4.82, and all eight regions had increases in market share. Impact in remote regions was substantial, with 60% (Ghana) and 48.5% (Kenya) of facilities in remote areas stocking QAACTs. Negotiations with manufacturers, the involvement of the private sector, and supporting interventions were critical in the success of AMFm. The AMFm pilot project then transitioned into a private sector co-payment mechanism involving only six countries. The AMFm program was not sustainable due to the enormous costs of the program, potentially due to unnecessary and excessive orders of ACTs, with an estimated total of 500 million USD. Fixing this sustainability issue would make a program such as this one more applicable to other malaria-endemic countries, which have limited financial resources.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.006 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".