Predictive Analytics for Retention in Care in an Urban HIV Clinic
In the United States, less than half of HIV-positive individuals are retained in care. This machine learning model was developed to identify patients at risk for dropping out of care in an urban HIV care clinic using electronic medical records and geospatial data.
Peer Linkage and Re-engagement of Women of Color with HIV
In the San Francisco Bay Area (SFBA), trans women of color are disproportionately affected by HIV and have poor HIV care outcomes. This analysis was to identify associations between intervention exposure and primary HIV care visits, ART prescription, and retention in HIV care.
