ArticlePLOS digital health2025
Exploring the diagnostic accuracy of an HIV self-test optimized by a digital app-based solution: Results from a secondary data analysis of a field trial in South Africa.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The trial behind it
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Who cites it
1 citing paper in PubMed.
- Acceptability, Usability, and Clinical Appropriateness of an AI-Powered Tool for Linkage to HIV Services After HIV Self-Testing in South Africa: Mixed Methods Evaluation.Journal of medical Internet research · 2026Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo reach UNAIDS 95-95-95 targets, digital HIV self-testing (HIVST) strategy aided by applications, platforms, and readers can engage young people and adults living with undetected HIV infection. Evidence on its acceptability, feasibility, impact exists, yet accuracy data are limited.
methodsA secondary data analysis of a quasi-RCT of digital HIVST in South Africa was performed. We hypothesized app-guided digital interpretation of oral self-test enhanced test accuracy. We compared accuracy between digital HIVST supervised vs. unsupervised (with/without healthcare worker). Self-test results were interpreted and uploaded by participants, compared using computer vision technology, against lab reference standard by trained healthcare professionals.
results1513 digital HIVST participants reported pooled Sensitivity (Sn) = 95.52% (95% CI, 94.48%-96.56%); Specificity (Sp): 99.93% (95% CI, 99.79%-100.06%); Positive predictive value (PPV): 99.22% (95% CI, 98.78%-99.67%); Negative Predictive Value (NPV): 99.57% (95% CI, 99.24%-99.90%). 565 participants on supervised digital HIVST, reported a pooled Sn: 93.65% (95% CI, 91.64-95.66); Sp: 100.00% (95% CI, 100.00-100.00); PPV: 100.00% (95% CI, 100.00-100.00); NPV: 99.21% (95% CI, 98.48-99.94). 968 unsupervised digital HIVST participants, reported a pooled Sn: 97.18% (95% CI, 96.13-98.24); Sp: 99.89% (95% CI, 99.67-100.10); PPV: 98.57% (95% CI, 97.82-99.33); NPV: 99.77% (95% CI, 99.47-100.08). Non-digital HIVST vs. study digital HIVST data at 5% significance level - Sn: chi = 0.6495, p-value = 0.4203, Sp: chi = 0.3831, p-value = 0.5259. Supervised vs. unsupervised HIVST at 5% significance level - Sn: chi = 0.973, p-value = 0.3237, Sp: chi = 0.527, p-value = 0.4449.
conclusionsDigital HIVST improved interpretation of test results, increased accuracy and predictive value estimations (upper limit 98%-100%), removing subjectivity. Unsupervised digital HIVST users performed better than supervised. Digital HIVST results can potentially signal a rapid triage to therapy or prevention pathways, while awaiting lab confirmation. Findings have implications for scale up of digital HIVST initiatives in global settings.
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Registered trials
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