  The propagations of diseases, behaviors and information in real systems are
rarely independent of each other, but they are coevolving with strong
interactions. To uncover the dynamical mechanisms, the evolving spatiotemporal
patterns and critical phenomena of networked coevolution spreading are
extremely important, which provide theoretical foundations for us to control
epidemic spreading, predict collective behaviors in social systems, and so on.
The coevolution spreading dynamics in complex networks has thus attracted much
attention in many disciplines. In this review, we introduce recent progress in
the study of coevolution spreading dynamics, emphasizing the contributions from
the perspectives of statistical mechanics and network science. The theoretical
methods, critical phenomena, phase transitions, interacting mechanisms, and
effects of network topology for four representative types of coevolution
spreading mechanisms, including the coevolution of biological contagions,
social contagions, epidemic-awareness, and epidemic-resources, are presented in
detail, and the challenges in this field as well as open issues for future
studies are also discussed.
