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
Digital 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.
Authors
- Aliasgar Esmail (ORCID: https://orcid.org/0000-0002-1835-9252)
- Thomas F. Duchaîne (ORCID: https://orcid.org/0000-0002-3454-1839)
- Nora Engel (ORCID: https://orcid.org/0000-0002-1823-3908)
- Keertan Dheda (ORCID: https://orcid.org/0000-0001-7709-5341)
- Nitika Pant Pai (ORCID: https://orcid.org/0000-0002-4672-0500)
- Qihuang Zhang (ORCID: https://orcid.org/0000-0003-1455-2159)
- Ashlyn Beecroft
- Chen Liang (ORCID: https://orcid.org/0000-0003-1781-859X)
- Olivia Vaikla (ORCID: https://orcid.org/0000-0002-5551-9825)
Institutions
- University of Cape Town (ZA)
- McGill University Health Centre (CA)
- Department of Health (TW)
- McGill University (CA)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1371/journal.pdig.0000791
- Citations
- 1
- Primary Topic
- HIV/AIDS Research and Interventions
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- McGill University Health Centre
- Grand Challenges Canada