Opportunities and considerations for the design of decentralized delivery of antiretroviral therapy for female sex workers living with HIV in South Africa
Bibliographic record
Abstract
BACKGROUND: In South Africa, 60% of female sex workers (FSW) are living with HIV, many of whom experience structural and individual barriers to antiretroviral therapy (ART) initiation and adherence. Community-based decentralized treatment provision (DTP) may mitigate these barriers. To characterize optimal implementation strategies, we explored preferences for DTP among FSW living with HIV in Durban, South Africa. METHODS: Thirty-nine semi-structured in-depth interviews were conducted with FSW living with HIV (n = 24), and key informants (n = 15) including HIV program implementers, security personnel, and brothel managers. Participants were recruited using maximum variation and snowball sampling. Interviews were conducted in English or isiZulu between September-November 2017 and analyzed using grounded theory in Atlas.ti 8. RESULTS: DTP was described as an intervention that could address barriers to ART adherence and retention, minimizing transport costs, time and wage loss from clinic visits, and act as a safety net to address FSW mobility and clinic access challenges. Respondents highlighted contextual considerations for DTP and suggested that DTP should be venue-based, scheduled during less busy times and days, and integrate comprehensive health services including psychological, reproductive, and non-communicable disease services. ART packaging and storage were important for community-based delivery, and participants suggested DTP should be implemented by sex work sensitized staff with discrete uniform and vehicle branding. CONCLUSIONS: Incorporating FSW preferences may support implementation optimization and requires balancing of tensions between preferences and feasibility. These data suggest the potential utility of DTP for FSW as a strategy to address those most marginalized from current ART programs in South Africa.
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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 | 0.031 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".