Programmatic and ethical challenges in the implementation of treatment-as-prevention in the context of HIV and drug-resistant tuberculosis co-infection in sub-Saharan Africa
Bibliographic record
Abstract
There is limited literature on programmatic challenges in the implementation of a treatment-as-prevention (TasP) strategy among human immunodeficiency virus (HIV) and drug-resistant tuberculosis (DR-TB) co-infected individuals in sub-Saharan Africa (SSA). This paper highlights specific programmatic challenges surrounding the implementation of this strategy among HIV and DR-TB co-infected populations in SSA. In SSA, limitations in administrative, human and financial resources and poor health infrastructure, as well as increased duration and complexity of providing long-term treatment for HIV individuals co-infected with DR-TB, pose substantial challenges to the implementation of a TasP strategy and warrant further investigation. A comprehensive approach must be devised to implement TasP strategy, with special attention paid to the sizable HIV and DR-TB co-infected populations. We suggest that evidence-informed and human rights-based guidelines for participant protection and strategies for programme delivery must be developed and tailored to maximise the benefits to those most at risk of developing HIV and DR-TB co-infection. Assessing regional circumstances is crucial, and TasP programmes in the region should be complemented by combined prevention strategies to achieve the intended goals.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".