Shaping the Future of HIV Self-Testing in Sub-Saharan Africa: Leveraging Predictive Modeling to Overcome Barriers and Enhance Targeted Interventions (Preprint)
Domaine:
healthcareCréateur:
FelMauOla
Éditeur:
JMI
Hôte:
UNSTRUCTURED
The use of predictive modeling in HIV prevention is gaining traction in Sub-Saharan Africa (SSA), particularly for enhancing HIV self-testing (HIVST) among underserved populations. Implementing predictive models to target HIVST interventions presents both opportunities and challenges, requiring culturally sensitive approaches and ethical considerations in data use. This Viewpoint explores the application of Random Forest (RF) and Classification and Regression Tree (CART) models to identify high-risk groups and optimize HIVST outreach. It highlights key considerations and lessons for practitioners in balancing technological innovation with community engagement and inclusivity to strengthen HIV response strategies across SSA.
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