Simulação escalável de epidemias em redes baseadas em passeios aleatórios com caracterização de transições de fase

Abstract

Understanding how networks and dynamic processes relate is a important topic of research, and particularly in the context of epidemics spreading through networks. In this work, we consider the scenario where individuals move through a network. Contagion occur when two (or more) individuals are in the same location (vertex). The aim of this work is to build a scalable simulator to this type of epidemic and characterize the behavior of epidemic in function of the network structure. In particular, our results indicate that the simulator is scalable in network size, simulation time and number of individuals. In addiction, results on the epidemic indicate a phase transition in several parameters of the model, so that epidemics terminate quickly or last for a long time.