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Title: Estimating the epidemic threshold on networks by deterministic connections

Journal Article · · Chaos (Woodbury, N. Y.)
DOI:https://doi.org/10.1063/1.4901334· OSTI ID:22402512
;  [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)

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.

OSTI ID:
22402512
Journal Information:
Chaos (Woodbury, N. Y.), Vol. 24, Issue 4; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); ISSN 1054-1500
Country of Publication:
United States
Language:
English

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