Data-Driven Multiscale Analysis of the HIV Epidemic in the USA: Structural and Practical Identifiability Across Epidemiological Scales

The article presents a multiscale mathematical analysis of the HIV epidemic in the USA that couples viral dynamics within individual patients with transmission at the population level. The model is structured by treatment age and accounts for how viral load influences infectiousness and progression to AIDS. Researchers fitted the model to clinical data (viral load and target cell counts) and epidemiological data (HIV incidence, diagnoses, and AIDS classifications) from the CDC. The analysis showed that the model is identifiable under certain conditions and that current strategies are unlikely to meet 2030 targets. Results indicate that increasing diagnosis rates and reducing transmission from diagnosed individuals could significantly alter epidemic trajectories. The study emphasizes the importance of multiscale modeling in developing effective HIV intervention strategies.