| Abstract: |
| In this study, we examine the dynamics of HIV-1 infection using mathematical models that capture both patient-specific behavior and population-level patterns. The model is formulated as a three-dimensional system describing the interactions between uninfected target cells, infected target cells, and viral load. We first perform mathematical model fits using longitudinal RNA measurements from individual patients, allowing parameters to be estimated directly from clinically observed data. In addition to this mathematical modeling approach, we conduct a statistical analysis across the patient cohort to investigate population-level patterns. Interestingly, the same patients emerge as the best-fitting cases under both approaches, indicating strong agreement between the mathematical modeling results and the statistical population analysis. |
|