Epidemics and immunization in scale‐free networks

By Romualdo Pastor-Satorras, Alessandro Vespignani. 2002

299 citations recorded by the source corpus.

Complex interacting networks are observed in systems from such diverse areas as physics, biology, economics, ecology, and computer science. For example, economic or social interactions often organize themselves in complex network structures. Similar phenomena are observed in traffic flow and in communication networks as the internet. In current problems of the Biosciences, prominent examples are protein networks in the living cell, as well as molecular networks in the genome. On larger scales one finds networks of cells as in neural networks, up to the scale of organisms in ecological food webs. This book defines the field of complex interacting networks in its infancy and presents the dynamics of networks and their structure as a key concept across disciplines. The contributions present common underlying principles of network dynamics and their theoretical description and are of interest to specialists as well as to the non-specialized reader looking for an introduction to this new exciting field. Theoretical concepts include modeling networks as dynamical systems with numerical methods and new graph theoretical methods, but also focus on networks that change their topology as in morphogenesis and self-organization. The authors offer concepts to model network structures and dynamics, focussing on approaches applicable across disciplines.

Subfields: Modeling and Simulation, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/b34a2ac3bb09ba4d05b247f76fec1401e75169ab

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Citations in the corpus

What is Twitter, a social network or a news media? (2010, background): “This area is extensively researched from sociology, marketing, and epidemiology [15, 19, 30 , 33].”
Epidemic spreading in real networks: an eigenvalue viewpoint (2003, background): “IIS-9817496, IIS-9988876, IIS0083148, IIS-0113089, IIS-0209107 IIS-0205224 by the Pennsylvania Infrastructure Technology Alliance (PITA) Grant No. 22-901-0001, and by the Defense Advanced Research Projects Agency under Contract No.”
On the approximability of influence in social networks (2008, background): “The dynamic processes governing the di.usion of information and word-of-mouth e.ects have been studied in many .elds, including Epidemiology [7, 23, 28], Sociology [24, 25, 31, 21, 5], Economics, and Computer Science [9, 27, 14, 13, 15, 11, 4, 6, 22, 12].”
Large graph limit for an SIR process in random network with heterogeneous connectivity (2010, unknown): “, [4, 10, 23]) or large population approximations (e.”
Influence of network structure on rumor propagation (2007, unknown): “The epidemic spreading on complex networks have also been discussed on other models [ 23 ,24], such as on the SI model [25,26] and on the SIRS model [27].”
Epidemic spreading on heterogeneous networks with identical infectivity (2006, background): “Recently, power-law degree distributions have been observed in various networks [1, 2]. One of the original, and still primary reasons for studying networks is to understand the mechanisms by which diseases and other things, such as information and rumors spread over [ 3 ,4].”
The Structure and Function of Complex Networks (2003, background): “For other helpful conversations and comments about networks thanks go to Lada Adamic, László Barabási, Stefan Bornholdt, Duncan Callaway, Peter Dodds, Jennifer Dunne, Rick Durrett, Stephanie Forrest, Michelle Girvan, Jon Kleinberg, James Moody, Cris Moore, Martina Morris, Juyong Park, Richard Rot”
Link Prediction in Complex Networks: A Survey (2010, methodology): “15 Ignoring the degree–degree correlations and applying the mean-field approximation, the spreading threshold equals the ratio between the first and the second moments of the degree distribution [138,139].”
Knowledge transfer in a tourism destination: the effects of a network structure (2009, background): “Recent advances in the study of complex networks have allowed a reconsideration of epidemic diffusion models to take into account the effects of nonhomogeneous network topologies (Kuperman & Abramson, 2001; Pastor-Satorras & Vespignani, 2001, 2003).”