Abstract

The COVID-19 outbreak has shown that Modeling and Simulation (MS) methodologies are an important aspect to study the spread of the disease and assess the effect of different measures to diminish its negative effect. Although traditional models have been widely used, there is a need to build new, highly configurable disease models to explore multiple scenarios quickly. We present an MS framework to perform rapid prototyping of pandemic spread using the Cell-DEVS space-based discrete-event modeling approach. This method supports age segmentation of the population, hospital-capacity-dependent deaths, and enforcing mobility restriction policies. This method is useful for studying the spread of the disease, as well as combining the simulation results with different visualization tools.