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    Epidemic processes in complex networks

    Romualdo Pastor-Satorras*, Claudio Castellano, Piet Van Mieghem, and Alessandro Vespignani

    Romualdo Pastor-Satorras*

    • Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord B4, 08034 Barcelona, Spain

    Claudio Castellano

    • Istituto dei Sistemi Complessi (ISC-CNR), via dei Taurini 19, I-00185 Roma, Italy and Dipartimento di Fisica, “Sapienza” Università di Roma, P.le A. Moro 2, I-00185 Roma, Italy

    Piet Van Mieghem

    • Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands

    Alessandro Vespignani

    • Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston Massachusetts 02115, USA and Institute for Scientific Interchange Foundation, Turin 10133, Italy
    • *romualdo.pastor@upc.edu

    Rev. Mod. Phys. 87, 925 – Published 31 August, 2015

    DOI: https://doi.org/10.1103/RevModPhys.87.925

    Abstract

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

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