The chapter "Epidemic Processes in Complex Networks" by Romualdo Pastor-Satorras, Claudio Castellano, Pies Van Mieghem, and Alessio Vespignani provides a comprehensive review of the theoretical and numerical modeling of epidemic spreading in complex networks. The authors highlight the impact of complex network properties on the behavior of equilibrium and nonequilibrium phenomena, emphasizing the importance of understanding epidemic dynamics in these networks. They discuss classical models such as the Susceptible-Infected-Susceptible (SIS) and Susceptible-Infected-Removed (SIR) models, and explore the connections between epidemic models and statistical physics concepts like phase transitions and absorbing states. The chapter also delves into network measures and models, including shortest path lengths, degree distributions, clustering coefficients, and centrality measures. It reviews the impact of network topology on epidemic behavior, particularly in heterogeneous networks, and discusses strategies for preventing or maximizing the spread of epidemics. The authors also cover realistic epidemic models, time-varying networks, and the generalization of epidemic processes to multi-species reaction-diffusion systems. Finally, they provide an outlook on future research directions, emphasizing the need for interdisciplinary collaboration to advance the field of epidemic modeling in complex networks.The chapter "Epidemic Processes in Complex Networks" by Romualdo Pastor-Satorras, Claudio Castellano, Pies Van Mieghem, and Alessio Vespignani provides a comprehensive review of the theoretical and numerical modeling of epidemic spreading in complex networks. The authors highlight the impact of complex network properties on the behavior of equilibrium and nonequilibrium phenomena, emphasizing the importance of understanding epidemic dynamics in these networks. They discuss classical models such as the Susceptible-Infected-Susceptible (SIS) and Susceptible-Infected-Removed (SIR) models, and explore the connections between epidemic models and statistical physics concepts like phase transitions and absorbing states. The chapter also delves into network measures and models, including shortest path lengths, degree distributions, clustering coefficients, and centrality measures. It reviews the impact of network topology on epidemic behavior, particularly in heterogeneous networks, and discusses strategies for preventing or maximizing the spread of epidemics. The authors also cover realistic epidemic models, time-varying networks, and the generalization of epidemic processes to multi-species reaction-diffusion systems. Finally, they provide an outlook on future research directions, emphasizing the need for interdisciplinary collaboration to advance the field of epidemic modeling in complex networks.