Structural Barriers, Stochastic Avoidance, and Outbreak Risk in HIV Prevention for People Who Inject Drugs

Background: Despite highly efficacious long-acting injectable pre-exposure prophylaxis (LAI-PrEP) achieving >99% efficacy in clinical trials, people who inject drugs (PWID) experience near-zero population-level HIV prevention effectiveness. We hypothesized that nested structural barriers, not pharmacological limitations, explain this disparity. Methods: We developed a Monte Carlo simulation modeling an 8-step LAI-PrEP cascade for PWID under current U.S. policy conditions (n=100,000 per scenario). We decomposed barriers into three layers: pathogen biology, HIV testing gaps, and architectural barriers (policy, stigma, infrastructure, research exclusion, algorithmic deprioritization). We compared PWID outcomes to men who have sex with men (MSM) receiving identical pharmacological interventions and modeled stochastic avoidance failure using network density dynamics. Results: Under current policy, PWID achieved P(R0=0) = 0.003% (95% CI: 0.000-0.006%) compared to 16.3% for MSM—a 5,433-fold disparity. Architectural barriers accounted for 93.2% of cascade failure (policy 38.4%, infrastructure 21.9%, stigma 20.5%, algorithmic bias 8.2%, research exclusion 4.1%), while HIV testing gaps contributed 6.8%. Even theoretical maximum intervention achieved only 19.7% effectiveness. Stochastic avoidance modeling predicted 73.8% probability of major outbreak within 5 years (median: 3.0 years). Conclusions: Current HIV prevention for PWID relies on probability rather than intervention. Structural barriers—particularly criminalization and MSM-centric infrastructure—create conditions where effective prevention is mathematically impossible regardless of drug efficacy. Policy reform addressing these architectural barriers is essential to prevent predictable outbreaks.