Modeling and Simulation of Space-Based Pandemic Scenarios Using an Open-Source Platform

Abstract

The classic susceptible-infected-recovered (SIR) models provide a good approach for modeling the spread of communicable diseases. However, this model is not suitable to understand the spatial implications on the spreading of the disease or the impact of individual interactions. Our open-source platform uses an extension of the classic SIR models for rapidly prototyping different aspects of virus spread and infection of the population using a spatial approach. This platform is useful for studying the spread of the disease and analyzing the simulation results with advanced visualization tools.