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Title: Estimating the epidemic threshold on networks by deterministic connections

For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.
Authors:
;  [1] ;  [2] ;  [3]
  1. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004 (China)
  2. Department of Mathematics, Shanghai University, Shanghai 200444 (China)
  3. School of Mathematics and Statistics, The University of Western Australia, Crawley, Western Australia 6009 (Australia)
Publication Date:
OSTI Identifier:
22402512
Resource Type:
Journal Article
Resource Relation:
Journal Name: Chaos (Woodbury, N. Y.); Journal Volume: 24; Journal Issue: 4; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; COMMUNITIES; COMPUTERIZED SIMULATION; DETERMINISTIC ESTIMATION; NETWORK ANALYSIS; PROBABILITY; RANDOMNESS; STOCHASTIC PROCESSES