The nonlinear spreading dynamics of epidemiological and digital epidemiology aims at revealing the evolution and emergent behaviour propagations of diseases, behaviour, and information in the networked socio-technical systems. Those spreading dynamics are rarely independent from each other, yet they are coevolving with strong interactions.

Recently, to uncover and understand the interacting mechanisms, spatio-temporal evolving patterns, critical phenomena, and phase transitions of networked coevolution spreading is a hot topic in network science. The significance of this issue and why it attracts increasing attention lies in three aspects. Coevolving spreading widely exists in epidemiological and social systems with important practical relevance, for example, the HIV results in lower immunity of virus carriers, who are therefore more susceptible to infectious diseases such as tuberculosis and hepatitis. Another positive example is that the propagation of disease-related information in social media could largely depress the spreading of the corresponding epidemic disease. The complex interactions during the coevolving dynamics lead to rich phase transition phenomena and novel physics, such as the coexisting thresholds caused by competitive interactions and the first-order phase transition caused by cooperation interactions. The multiscale structure, multiplexity, and temporality of networks remarkably affects the criticality of spreading dynamics, not only the value of thresholds, but also the critical exponents and the type of phase transitions.

This Special Issue aims to provide both theoretical and empirical investigations about the coevolving spreading dynamics on complex networks. We warmly encourage original related research papers from different disciplines ranging from biology, physics, computer science, mathematics, and sociology. Furthermore, high-quality review articles describing the current state of the art are also invited.

Potential topics include but are not limited to the following:

• Deterministic/stochastic model of coevolving spreading
• Data-driven model for coevolving spreading
• Coevolving epidemic spreading in biological systems
• Coevolving social contagions in social systems
• Coevolving of epidemiological-social spreading
• Evolution and emergent behaviour of coevolving spreading with distinct interaction mechanisms
• Source identification and influential maximization for coevolving spreading
• New theoretical approaches for coevolving spreading
• Critical phenomena and phase transitions in coevolving spreading
• Dynamical analysis and control of coevolving spreading
• Modelling coevolving spreading on single, multilayer, multiplex, interconnected and temporal complex networks
• Modelling coevolving spreading with distinct interacting mechanisms