Influenza epidemic model with dynamic social networks of agents with individual behaviour: A self organize perspective

It's well known the existence of an interplay between the spread of an infectious disease like influenza and behavioral changes of individuals. An outbreak can trigger behavioral responses, at the group and individual levels, which in turn can influence the course of the epidemic. Daily life interactions can be modeled by adaptive temporal networks in an explicit contact space through an agent-based model, where each agent represents the interacting individuals. In this paper we introduce an individual-based model where the behavior of each individual is determined both by the external stimuli and its own appreciation of the environment and can be built as a combination of three interacting blocks: i) individual behavior, ii) social behavior and iii) epidemic state or epidemiological behavior. We fit the model for a real influenza epidemic and perform the model validation, comparing the results with the classical approaches.