Leveraging Sexually TransmittedInfection Data for Enhancing HIV Prevention and Management Guidelines: A Data Science Approach
Despite significant advancements in HIV prevention and treatment, there remains a critical gap in integrating sexually transmitted infection (STI) data into predictive models for HIV health care-related outcomes. STIs have been recognized as significant risk factors for HIV acquisition and poor HIV care outcomes through a range of biological (e.g., mucosal barrier disruption and inflammatory … Read more