Propagation models of epidemics and rumors are essential for predicting and controlling the transmission of infectious agents and social behavior. Most models developed in complex networks only considers static structures where connections are maintained over time. Only recently, epidemic propagation models in adaptive networks have been proposed. In these networks, the connections are not static, varying during the spread of the infectious agent. In this study, we will aim to study such models and propose new network adaptation rules. Rumors models will also be considered. The results will allow a better understanding of the spread of information in complex networks with time-varying structure.
News published in Agência FAPESP Newsletter about the scholarship: