Mapping government financing for antimicrobial resistance responses in East and Southern Africa: implications for sustainability and domestic ownership: a narrative review
Bibliographic record
Abstract
Antimicrobial resistance (AMR) poses a significant and growing public health challenge in East and Southern Africa. Despite formal commitments to the National Action Plans, domestic financing for AMR remains critically limited, with most countries continuing to depend heavily on external donor funding. This narrative review examines the current extent to which domestic fiscal commitments align with national AMR policy goals across the two regions. Government websites for ministries of health and finance, donor platforms, and three academic databases (Scopus, JSTOR, Google Scholar) were searched for eligible articles. National budget statements and media reports were also reviewed where available. Three researchers independently screened titles and summaries, followed by full-text reviews to confirm eligibility. The findings reveal that while several countries have developed National Action Plans, very few have allocated domestic funding to implement them. Only Malawi, Nigeria and Uganda reported modest domestic contributions, while in other countries such as Zambia, Ethiopia, and South Africa, AMR programs remain largely donor-financed or lack dedicated budget lines altogether. Veterinary and laboratory sectors are particularly underfunded, with minimal integration into broader AMR strategies. While this review has several limitations including restricted access to current, comprehensive national budget data and a reliance on secondary sources such as donor and World Health Organization reports, which may introduce bias, the patterns identified in this review still offer valuable insight into regional funding dynamics and can inform future policy and research efforts. We conclude that without dedicated domestic financing and accountability mechanisms, AMR efforts in the region may face significant sustainability challenges observed in other health responses such as HIV. Strengthening AMR governance requires clear budgetary commitments, sustainable co-financing models, and policy instruments to reduce dependency on external support.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".