Can HIV self-testing reach first-time testers? A telephone survey among self-test end users in Côte d’Ivoire, Mali, and Senegal
Bibliographic record
Abstract
BACKGROUND: Coverage of HIV testing remains sub-optimal in West Africa. Between 2019 and 2022, the ATLAS program distributed ~400 000 oral HIV self-tests (HIVST) in Côte d'Ivoire, Mali, and Senegal, prioritising female sex workers (FSW) and men having sex with men (MSM), and relying on secondary redistribution of HIVST to partners, peers and clients to reach individuals not tested through conventional testing. This study assesses the proportion of first-time testers among HIVST users and the associated factors. METHODS: A phone-based survey was implemented among HIVST users recruited using dedicated leaflets inviting them to anonymously call a free phone number. We collected socio-demographics, sexual behaviours, HIV testing history, HIVST use, and satisfaction with HIVST. We reported the proportion of first-time testers and computed associated factors using logistic regression. RESULTS: Between March and June 2021, 2 615 participants were recruited for 50 940 distributed HIVST (participation rate: 5.1%). Among participants, 30% received their HIVST kit through secondary distribution (from a friend, sexual partner, family member, or colleague). The proportion who had never tested for HIV before HIVST (first-time testers) was 41%. The main factors associated with being a first-time tester were sex, age group, education level, condom use, and secondary distribution. A higher proportion was observed among those aged 24 years or less (55% vs 32% for 25-34, aOR: 0.37 [95%CI: 0.30-0.44], and 26% for 35 years or more, aOR: 0.28 [0.21-0.37]); those less educated (48% for none/primary education vs 45% for secondary education, aOR: 0.60 [0.47-0.77], and 29% for higher education, aOR: 0.33 [0.25-0.44]). A lower proportion was observed among women (37% vs 43%, aOR: 0.49 [0.40-0.60]); those reporting always using a condom over the last year (36% vs 51% for those reporting never using them, aOR: 2.02 [1.59-2.56]); and those who received their HISVST kit through primary distribution (39% vs 46% for secondary distribution, aOR: 1.32 [1.08-1.60]). CONCLUSION: ATLAS HIVST strategy, including secondary distribution, successfully reached a significant proportion of first-time testers. HIVST has the potential to reach underserved populations and contribute to the expansion of HIV testing services in West 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".