  We propose a novel multi-scale modeling framework for infectious disease
spreading, borrowing ideas and modeling tools from the so-called Refractory
Density (RD) approach. We introduce a microscopic model that describes the
probability of infection for a single individual and the evolution of the
disease within their body. From the individual-level description, we then
present the corresponding population-level model of epidemic spreading on the
mesoscopic and macroscopic scale. We conclude with numerical illustrations
taking into account either a white Gaussian noise or an escape noise to
showcase the potential of our approach in producing both transient and
asymptotic complex dynamics as well as finite-size fluctuations consistently
across multiple scales. A comparison with the epidemiology of coronaviruses is
also given to corroborate the qualitative relevance of our new approach.
