Using a Modeling-Based Approach to Assess and Optimize HIV Linkage to Care Services.

Evidence-based linkage to care interventions (LTCs) help recently diagnosed HIV+ individuals engage in care in a timely manner yet are heavily impacted by the systems in which they are embedded. We developed a prototype agent-based model informed by data from an established LTC program targeting youth and young adults aged 13-24 in Memphis, Tennessee. We then tested two interventions to improve LTC in a simulated environment: expanding testing sites versus using current testing sites but improving direct referral to LTC staff from organizations providing testing, to understand the impact on timely linkage to care. Improving direct referral to the LTC program decreased days to successful linkage from an average of 30 to 23 days but expanding testing sites increased average days to 31 days unless those sites also made direct referrals. We demonstrated how LTC is impacted by the system and interventions for shortening days to linkage to care.