Early antiretroviral therapy and daily pre‐exposure prophylaxis for <scp>HIV</scp> prevention among female sex workers in Cotonou, Benin: a prospective observational demonstration study
Bibliographic record
Abstract
INTRODUCTION: In sub-Saharan Africa, HIV prevalence remains high, especially among key populations. In such situations, combination prevention including clinical, behavioural, structural and biological components, as well as adequate treatment are important. We conducted a demonstration project at the Dispensaire IST, a clinic dedicated to female sex workers (FSWs) in Cotonou, on early antiretroviral therapy (E-ART, or immediate "test-and-treat") and pre-exposure prophylaxis (PrEP). We present key indicators such as uptake, retention and adherence. METHODS: ) for PrEP or received a first-line antiretroviral regimen as per Benin guidelines. We used generalized estimating equations to assess trends in adherence and sexual behaviour. RESULTS: Among FSWs in the catchment area, HIV testing coverage within the study framework was 95.5% (422/442). At baseline, HIV prevalence was 26.3% (111/422). Among eligible FSWs, 95.5% (105/110) were recruited for E-ART and 88.3% (256/290) for PrEP. Overall retention at the end of the study was 59.0% (62/105) for E-ART and 47.3% (121/256) for PrEP. Mean (±SD) duration of follow-up was 13.4 (±7.9) months for E-ART and 11.8 (±7.9) months for PrEP. Self-reported adherence was over 90% among most E-ART participants. For PrEP, adherence was lower and the proportion with 100% adherence decreased over time from 78.4% to 56.7% (p-trend < 0.0001). During the 250.1 person-years of follow-up among PrEP initiators, two seroconversions occurred (incidence 0.8/100 person-years (95% confidence interval: 0.3 to 1.9/100 person-years)). The two seroconverters had stopped using PrEP for at least six months before being found HIV-infected. In both groups, there was no evidence of reduced condom use. CONCLUSIONS: This study provides data on key indicators for the integration of E-ART and PrEP into the HIV prevention combination package already offered to FSWs in Benin. PrEP may be more useful as an individual intervention for adherent FSWs rather than a specific public health intervention. E-ART was a more successful intervention in terms of retention and adherence and is now offered to all key populations in Benin. STUDY REGISTRATION: ClinicalTrials.gov NCT02237.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".