Epidemics in interconnected small-world networks

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Abstract

Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

Figures

  • Fig 1. Interconnected small-world networks. The rewiring probability is p = 0.1. One randomly chosen node ai in network A is connected to a node bj in network B that is located at a spatial distance R from node ai, as defined in (Equation 1). When the spatial distance is specified as R = 1, for example, 8 nodes (gray) are at a spatial distance of 1 from node ai, and node bj is randomly chosen among these 8 nodes.
  • Fig 2. Epidemic threshold λc as a function of the rewiring probability for different spatial constraints R on the interconnection links. For a given rewiring probability p and a given spatial constraint R, we gradually increase the infection rate λ and find the corresponding infection density in the steady state for each infection rate. We consider λc as the first λ value corresponding to a non-zero infection density in the steady state. Each component network has a small-world topology with a rewiring probability p. The density of the interconnection links is q = 1. Initially, 10% of the nodes in network A are randomly chosen to be infected. The network size is N = 10000. The results have been averaged over 100 realizations.
  • Fig 3. Density ρ of infected nodes as a function of the infection rate λ for various rewiring probabilities. ρ is the average of the infection density ρA and ρB. The density of the interconnection links is q = 1, and the spatial length constraint is R = 1. Initially, 10% of the nodes in network A are randomly chosen to be infected. The network size is N = 10000. The results have been averaged over 100 realizations.
  • Fig 4. Epidemic spreading process in interconnected small-world networks. (a) illustrates the epidemic spreading pattern in network A. Initially, 16 nodes in the center of network A are infected. The rewiring probabilities are p = 0.1 ((1), (3)) and p = 1 ((2), (4)), and the infection rates are λ = 0.19 ((1), (2)) and λ = 0.24 ((3), (4)). (b) and (c) present the infection density ρA in network A as a function of time for two interconnected networks. Initially, 10% of the nodes in network A are randomly chosen to be infected. The infection rates are λ = 0.24 (b) and λ = 0.48 (c). The density of interconnection links is q = 1. The spatial length is R = 1. The network size is N = 10000. The results have been averaged over 100 realizations.
  • Fig 5. Time evolution of the average distance of infected nodes from the center of the lattice in network A. The infection rate is λ = 0.24. Initially, 16 nodes in the center of network A are infected. The density of interconnection links is q = 1. The spatial length is R = 1. The network size is N = 10000. The results have been averaged over 100 realizations.

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CITATION STYLE

APA

Liu, M., Li, D., Qin, P., Liu, C., Wang, H., & Wang, F. (2015). Epidemics in interconnected small-world networks. PLoS ONE, 10(3). https://doi.org/10.1371/journal.pone.0120701

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