Stochastic Modeling of HIV Reactivation Under ART Washout and Immune Fluctuations

Abstract

Post-treatment Human Immunodeficiency Virus (HIV-1) rebound is dictated by the stochastic reactivation of latent reservoirs influenced by immune fluctuations and Antiretroviral Therapy (ART) decay. In this paper, we study the effects of time, immune variability, and ART pharmacokinetics on HIV reactivation following treatment interruption. In this work, we model latency reversal as a Poisson-driven stochastic process shaped by circadian rhythms, transient inflammation, and immune bursts. We incorporate gamma-distributed waiting times in order to capture heterogeneity in activation dynamics and confirm the reduced early post-ART reactivation. Building on earlier stochastic models of reactivation, we present a rigorous framework that captures a range of activation dynamics—including constant, sinusoidal, stochastic, and exponentially decaying rates—reflecting both immune-driven variability and pharmacokinetic influences on latency reversal. We further investigate block-and-lock strategies, showing that combining ART with latency-promoting agents pharmacologically stabilizes the reservoir and delays reactivation, particularly when drug decay is slow. In addition, we study a deterministic model describing the dynamics of viruses, latent cells, and infected cells, including the role of the immune response and the effect of shock-and-kill strategies. Our results reveal that synchronizing latency-reversing agents with immune activation cycles enhances viral clearance and delays rebound. This framework refines post-treatment control predictions and generalizes to persistent infections, such as Hepatitis B Virus (HBV) and Cytomegalovirus (CMV), where immune fluctuations and drug decay shape stochastic viral reactivation.