Nowadays, one of the challenges we face when carrying out modeling of epidemic spreading is to develop methods to control the disease transmission. For doing that, we intend to explore how beneficial the information that people manage about a disease is to reduce the risk of an outbreak. In this paper we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information (rumor) about the knowledge of this disease --and its prevention methods-- using the unaware-aware-unaware dynamics  . Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes. We study the behavior of this model using a mean-field approach that gives results in good agreement with Monte Carlo simulations on  complex networks. We find that increasing the rate of rumor propagation reduces the disease prevalence, as one may expect. However, increasing the speed of the rumor process as compare to the epidemic process has the counter intuitive result of increasing the  prevalence. This result opens an interesting discussion about the effects of information spreading on disease propagation.
Nowadays, one of the challenges we face when carrying out modeling of epidemic spreading is to develop methods to control disease transmission. In this article we study how the spreading of knowledge of a disease affects the propagation of that disease in a population of interacting individuals. For that, we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information about the disease --and its prevention methods-- using the unaware-aware-unaware dynamics , so that informed individuals are less likely to be infected . Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes. We study the behavior of this model using a mean-field approach that gives results in good agreement with Monte Carlo simulations on homogeneous complex networks. We find that increasing the rate of information dissemination reduces the disease prevalence, as one may expect. However, increasing the speed of the information process as compared to that of the epidemic process has the counter intuitive effect of increasing the disease prevalence. This result opens an interesting discussion about the effects of information spreading on disease propagation.
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For doing that, we intend to explore how beneficial the information that people manage about a disease is to reduce the risk of an outbreak. In this paper
In this article we study how the spreading of knowledge of a disease affects the propagation of that disease in a population of interacting individuals. For that,
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