A refractory density approach to a multi-scale SEIRS epidemic model
arXiv:2407.02396 · doi:10.1016/j.idm.2025.03.004
Abstract
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.
17 pages, 7 figures
References in corpus (7)
- Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size
- Global stability of SAIRS epidemic models
- Boltzmann-type equations for multi-agent systems with label switching
- An SIR-like kinetic model tracking individuals' viral load
- Optimal epidemic control by social distancing and vaccination of an infection structured by time since infection: the covid-19 case study
- Global stability of multi-group SAIRS epidemic models
- A multigroup approach to delayed prion production