Modeling the influence of information on the coevolution of contact networks and the dynamics of infectious diseases

Outbreaks of infectious diseases may awaken the awareness of individuals, consequently, they may adjust their contact patterns according to the perceived risk from disease. In this paper, we assume that individuals make decisions on breaking or recovering links according to the information of diseases spreading which they have acquired. They will reduce some links when diseases are prevalent and have high risks; otherwise, they will recover some original links when the diseases are controlled or present minimal risk. Under such an assumption, we study the effects of information of diseases on the contact patterns within the population and on the dynamics of epidemics. By extensive simulations and theoretical analysis, we find that, due to the time-delayed information of diseases, both the density of the disease and the topology of the network vary with time in a periodic form. Our results indicate that the quality of information available to individuals can have an important effect on the spreading of infectious diseases and implications for related problems.

► A model is proposed to reflect how human responses to some sudden epidemics.
► Individuals decide to remove or recovery some links based on risk estimations.
► The coevolutionary model can induce Hopf bifurcation under some conditions.
► The critical value of the emergence of Hopf bifurcation is analyzed.