Speaker
Description
The human immunodeficiency virus (HIV) epidemic remains a pressing public health challenge in the United States, despite major advances in treatment and prevention. Achieving the national Ending the HIV Epidemic (EHE) goals by 2030 requires a deeper understanding of the interplay between individual-level viral dynamics and population-level transmission. To address this, we develop and analyze a nested multiscale immuno-epidemiological HIV model that explicitly links within-host processes to epidemic outcomes. The model incorporates viral load–dependent transmission and treatment effects, allowing us to capture how immune responses and therapeutic interventions shape epidemic trajectories. We derive the basic reproduction number and establish threshold conditions for the existence and stability of the disease-free and endemic equilibria. We fit the multiscale model to within-host clinical data from 80 HIV-infected individuals and to national CDC surveillance data on incidence, diagnoses, and AIDS classifications. Our results show that reducing transmission from diagnosed individuals and increasing diagnosis rates could lead to epidemic declines consistent with EHE targets. This study highlights the importance of multiscale modeling in identifying intervention pathways and underscores the need for strengthened strategies to accelerate epidemic control.
