Abstract

We present here a set of prototypical mechanisms aimed at modeling the social adaptation and response triggered in the population by the knowledge of the spreading of an infectious disease. We define models that couples the spreading of information and behavioral changes with the spreading of the infectious disease by considering the local and non-local prevalence-based information available to individuals in the population. The behavioral changes are modeled both as the onset of effective social distancing and contact reduction as well as changes in the mobility patterns of individuals. The defined models exhibit a rich phase space with multiple epidemic peaks and threshold behavior. In addition, we show that in specific cases the change of mobility pattern may counterintuitively enhance the disease spreading. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.

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