Interacting social and disease dynamics in multiplex networks

FEDERICO VAZQUEZ

Buenos Aires

Conferencia; NetSci-X-2023, International School and Conference on Network Science; 2023

A major issue in the theoretical modeling of epidemic spreading is to investigate the effects of human social behavior in the propagation of a disease.  In this work we explore the spreading of the awareness of a disease as a method to control a pandemic.  We assume that aware individuals can take measures (isolation, quarantine) to reduce the risk of contagion.  I will present results that show how the prevalence of the disease is affected by the rate of information dissemination, and by the relative speed between disease and information spreading.  I will also show that the dynamics of individuals' opinions could have striking consequences on the statistical properties of disease spreading.  These results are obtained within a multiplex network framework in which the interaction between disease and social processes takes place in a bi-layer network.