Interacting Dynamics of opinion and disease on multiplex networks

FÁTIMA VELÁSQUEZ ROJAS; FEDERICO VAZQUEZ

Lyon

Conferencia; 26th IUPAP International Conference on Statistical Physics (STATPHYS 26).; 2016

IUPAP

We study the effects on the interaction between two different processes, the formation of opinions and the propagation of a disease in a population of individuals using a bilayer network. The nodes (people) are the same for both networks and are superposed through a fraction q (0 < q < 1) of pairs of nodes connected by the two types of links (opinion and disease). The frequency of interaction between two nodes depends on their states of disease and opinion. Sick people avoid leaving home and reduce their influence on the opinion of their peers, at least physically; on the other hand, people who think differently, do not meet frequently, thus reducing the possibility of infecting others. On one layer runs the dynamics of the Voter Model, while on the other layer runs the dynamics of the Contact Process. We explore how the formation of opinions affects the spread of diseases and vice versa: we analyze the dependence of the mean consensus time of opinions (𝜏) with the coupling. The mean consensus time is larger compared to the case of uncoupled networks and their behavior can increase monotonically or even, not monotonous. We also found that for finite systems, the density of infected individuals presents an abrupt jump with the coupling (q) and the infection probability (𝛽), while for infinite systems the phase transition between endemic and healthy phase is continuous. Similarly, as the coupling increases, the effective infection probability decreases, reducing the size of the infected phase.