| Abstract: |
| The progression of viral infections is determined by the dynamic interplay between viral replication strategies and the host`s adaptive immune response. Central to this process is the balance between effector T-cell activation and the induction of regulatory mechanisms that, while preventing excessive tissue damage, may inadvertently facilitate viral persistence. Understanding the non-linear transitions within these regulatory feedback loops is essential for identifying the biological triggers of viral pathogenesis.
In this talk, we propose a mathematical framework based on a system of non-linear ordinary differential equations (ODEs) to investigate the interactions between viral load, effector cell populations, and regulatory signaling pathways. The model incorporates specific transcription factor-mediated dynamics that govern the suppressive modulation of the immune response throughout the infection process. We conduct a rigorous qualitative analysis, including the determination of steady states and their stability, to identify parameter thresholds where the system undergoes significant regime shifts. Our findings highlight critical parameters, such as the suppression rate of effector populations, which act as primary drivers for the transition between viral clearance and immune escape. This model is specifically applied to and validated against viral pathogenesis data, providing mechanistic insights into potential therapeutic interventions and the complex dynamics of viral-host co-evolution. |
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