A preliminary experimentation for large scale epidemic forecasting simulations

Agent-based modeling and simulation are some powerful techniques that are widely used with success for analyzing complex and emergent phenomena in many research and application areas Many different reasons are behind the success of such techniques, among which an important mention goes to the availability of a great variety of software tools, that ease the development of models, as well as the execution of simulations and the analysis of results This paper presents an actor software library, called ActoDeS, for the development of concurrent and distributed systems, and shows how it can be a suitable mean for building flexible and scalable epidemic forecasting simulations In particular, the paper presents the first results of the experimentation of ActoDeS for defining a COVID-19 epidemic diffusion model and for supporting the simulation in large populations © 2020 Copyright for this paper by its authors