During an epidemic, people may adapt or alter their social contacts to avoid infection. Various adaptation mechanisms have been studied previously. Recently, a new adaptation mechanism was presented in (Tunc et al 2013 J. Stat. Phys. 151 355), where susceptible nodes temporarily deactivate their links to infected neighbors and reactivate when their neighbors recover. Considering the same adaptation mechanism on a scale-free network, we find that the topology of the subnetwork consisting of active links is fundamentally different from the original network topology. We predict the scaling exponent of the active degree distribution and derive mean field equations by using improved moment closure approximations based on the conditional distribution of active degree given the total degree. These mean field equations show better agreement with numerical simulation results than the standard mean field equations based on a homogeneity assumption.
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Univ Colorado, Dept Appl Math, 526 UCB, Boulder, CO 80309 USAUniv Colorado, Dept Appl Math, 526 UCB, Boulder, CO 80309 USA
Broido, Anna D.
Clauset, Aaron
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Univ Colorado, Dept Comp Sci, 430 UCB, Boulder, CO 80309 USA
Univ Colorado, BioFrontiers Inst, 596 UCB, Boulder, CO 80309 USA
Santa Fe Inst, 1399 Hyde Pk Rd, Santa Fe, NM 87501 USAUniv Colorado, Dept Appl Math, 526 UCB, Boulder, CO 80309 USA
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Seoul Natl Univ, Interdisciplinary Program Computat Sci & Technol, Seoul 08826, South KoreaSeoul Natl Univ, Interdisciplinary Program Computat Sci & Technol, Seoul 08826, South Korea
Bae, Jun Hyung
Lee, Sang-Mook
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Seoul Natl Univ, Dept Earth & Environm Sci, Seoul 08826, South KoreaSeoul Natl Univ, Interdisciplinary Program Computat Sci & Technol, Seoul 08826, South Korea