Agent-Based Models for Combinations of Biomedical and Behavioral Interventions for HIV Prevention

• Activity Number: 650
• Type: Contributed
• Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): David Boren*+ and Ron Brookmeyer
• Companies: UCLA and UCLA
• Keywords: HIV ; PREP ; ART ; Network ; Intervention ; Power

Abstract

Progress in HIV prevention interventions, including the use of ART (anti-retroviral therapy) and PREP (pre-exposure prophylaxis), has been made in recent years. These developments have raised questions concerning the impact and optimal combination of biomedical and behavioral interventions. We describe an agent based social network model, based on sexual contact parameters relevant to MSMs in South Africa, which we use to evaluate the varying impact of these HIV prevention combinations. We then simulate across realistic values of several parameters: ART uptake, PREP uptake, HIV testing penetration, and broad UAI (unprotected anal intercourse) reduction. A statistical model has been created to describe quantitatively the effects of these parameters, and a power analysis has been performed to assess the feasibility of detecting these effects under reasonable conditions. Our findings suggest that using a multifaceted prevention approach can have a significant public health impact on reducing HIV incidence rates, but that establishing statistical significance in a controlled clinical trial might be a formidable challenge.