The outbreak of an epidemic can trigger adaptive behavioral responses from individuals these responses will then play an important role in the spread of the infection. In order to characterize the interaction between human adaptive behaviors and epidemic spread, we propose a concrete interplay model in quenched multiplex networks. We model interaction between individuals and spread of the infection, as individual layers within the multiplex networks. Susceptibility of each individual to infection can then be mitigated by the strength of his/her adaptive behaviors, which is a direct response to information transmission. The model we propose is generic and applicable to a range of public health scenarios. We provide a caricature model of individual opinion, coupled through information propagation to the opinion of others. As opinion synchronizes in the information network, infectivity is shown to decrease in the epidemic contact network. While simple, the model is a useful proxy for many real-life and more complex scenarios. In particular, we observe the phenomenon of oscillation in an epidemic network with adaptive behaviors, and find that the epidemic control strategy from the perspective of behavioral control is extremely relevant for epidemic control. As an example, our results on SARS, a potentially fatal disease, have demonstrated the improved understanding of behavioral effects on infectious disease dynamics and control.