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

Area of Science:

• Public Health
• Health Systems Research
• Epidemiology

Background:

• Linkage to care (LTC) interventions are crucial for timely engagement of newly diagnosed HIV+ individuals.
• These interventions are significantly influenced by the healthcare systems they operate within.
• Youth and young adults (13-24 years) are a key demographic for targeted LTC programs.

Purpose of the Study:

• To develop and test a prototype agent-based model simulating HIV linkage to care.
• To evaluate the impact of two distinct interventions on reducing time to care engagement.
• To understand system-level effects on the efficacy of linkage to care interventions.

Main Methods:

• Developed an agent-based model using data from an established LTC program in Memphis, Tennessee.
• Simulated two interventions: expanding testing sites and improving direct referrals from testing sites to LTC staff.
• Analyzed the impact of interventions on the number of days to successful linkage to care.

Main Results:

• Improving direct referrals to LTC staff decreased average days to linkage from 30 to 23 days.
• Expanding testing sites alone increased average days to linkage to 31 days.
• Expanding testing sites combined with direct referrals showed improved linkage times.

Conclusions:

• Direct referral systems are more effective than simply expanding testing sites for timely HIV linkage to care.
• Healthcare system design and referral processes critically impact the success of LTC interventions.
• Agent-based modeling can effectively simulate and evaluate public health interventions for HIV care.