# Coevolution spreading in complex networks

## TL;DR

This review discusses recent advances in understanding how multiple spreading processes coevolve on complex networks, highlighting theoretical methods, critical phenomena, and the influence of network topology.

## Contribution

It synthesizes recent research on coevolution spreading dynamics, emphasizing statistical mechanics and network science perspectives across various mechanisms.

## Key findings

- Analysis of phase transitions in coevolution spreading
- Impact of network topology on spreading dynamics
- Identification of critical phenomena and mechanisms

## Abstract

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.