Year: 2015
Type: article
Abstract: Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth’s surface; however, in modern contagions long-range edges—for example, due to airline transportation or communication media—allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct ‘contagion maps’ that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks. The spreading dynamics of a contagion depend on the structure of an underlying network, and long-range edges due to airline transportation or media communication can significantly alter such dynamics. Here the authors use contagion dynamics on networks to produce point clouds for this analysis.
Source: Nature Communications
DOI: 10.1038/ncomms8723
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,990
Funders: National Science Foundation, European Commission, King Abdullah University of Science and Technology, National Institutes of Health, Defense Advanced Research Projects Agency, Engineering and Physical Sciences Research Council, Division of Mathematical Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Air Force Office of Scientific Research
Awards: G1598839328, Community Structure In Multislice Networks, G1774196161, INSPIRE: Nonlinear Data Reduction applied to Dense Granular Media, G2527266087, Mathematical framework for multiplex networks, G3595383695, Collaborative proposal: Computing Dynamics of Multiparameter Systems, G4022875974, Statistical and Applied Mathematical Sciences Institute, G4420254675, G4636648896, G4709654761, G551029724, Models and Tools for Dynamic Health-Relevant Diffusion over Complex Networks, CDI-TYPE II--COLLABORATIVE RESEARCH: Using Algebraic Topology to Connect Models with Measurements in Complex Nonequilibrium Systems, G6434574035, G7167414125, G7675897866, Models of spatio-temporal reaction systems with applications to systems and synthetic biology, G862860306, G8673896826
OpenAlex ID: W1830471444