Speaker
Description
The aim of this work is to introduce a new class of immuno-epidemiological models for infectious diseases and to investigate some of its mathematical properties. The proposed framework couples two dynamical subsystems operating at different biological scales: a within-host model describing viral and immunological kinetics, and a between-host model governing population-level transmission. The interaction between the two scales is mediated by a population viral load variable Q, which aggregates the viral output of all actively infected cohorts and modulates transmission rates. A key novelty of the approach is that a within-host subsystem is initiated for each daily cohort of newly infected individuals, with initial viral load determined by the value of Q on the day of infection. This construction creates bidirectional feedback: epidemic incidence generates new intra-host trajectories, while intra-host viral amplification shapes the evolution of Q and, in turn, epidemic growth. Numerical simulations illustrate how this multiscale feedback generates emergent epidemic patterns, including a characteristic delay between incidence and population viral load, and highlight the respective roles of within-host parameters in shaping epidemic outcomes.
