Epidemics with temporary link deactivation in scale-free networks

被引:6
|
作者
Shkarayev, Maxim S. [1 ]
Tunc, Ilker [2 ]
Shaw, Leah B. [3 ]
机构
[1] Iowa State Univ, Dept Phys & Astron, Ames, IA 50011 USA
[2] Univ Miami, John P Hussman Inst Human Genom, Miami, FL 33156 USA
[3] Coll William & Mary, Dept Appl Sci, Williamsburg, VA 23187 USA
基金
美国国家科学基金会;
关键词
adaptive networks; epidemics model; moment-closure; approximation;
D O I
10.1088/1751-8113/47/45/455006
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Evaluating performance of link prediction in scale-free evolving networks and a Facebook community
    Grieshober, Laurie
    Blair, Rachael Hageman
    SOCIAL NETWORK ANALYSIS AND MINING, 2014, 4 (01) : 1 - 10
  • [42] Structural Hole Based Link Addition for Capacity Enhancement in Scale-Free Networks
    Wang, Dong
    Liu, Erwu
    Liu, Dong
    Qu, Xinyu
    Ma, Rufei
    Wang, Rui
    Wang, Ping
    Liu, Fuqiang
    Liu, Chi Harold
    2015 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2015,
  • [43] RSH: A Link-Addition Strategy for Capacity Enhancement in Scale-Free Networks
    Wang, Dong
    Liu, Erwu
    Liu, Dong
    Qu, Xinyu
    Ma, Rufei
    Wang, Ping
    Liu, Xingcheng
    IEEE COMMUNICATIONS LETTERS, 2015, 19 (12) : 2110 - 2113
  • [44] An efficient link closing strategy for improving traffic capacity on scale-free networks
    Zhang, Junfeng
    Ma, Jinlong
    Li, Hui-Jia
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 604
  • [45] Enhancing traffic capacity of scale-free networks by link-directed strategy
    Ma, Jinlong
    Han, Weizhan
    Guo, Qing
    Zhang, Shuai
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2016, 27 (03):
  • [46] The Effects of Link and Node Capacity on Traffic Dynamics in Weighted Scale-Free Networks
    Hu, M. B.
    Jiang, R.
    Wu, Y. H.
    Wu, Q. S.
    COMPLEX SCIENCES, PT 1, 2009, 4 : 580 - +
  • [47] Epidemic spreading on dynamical networks with temporary hubs and stable scale-free degree distribution
    Wu, An-Cai
    JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2014,
  • [48] Will Scale-Free Popularity Develop Scale-Free Geo-Social Networks?
    Liu, Dong
    Fodor, Viktoria
    Rasmussen, Lars Kildehoj
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2019, 6 (03): : 587 - 598
  • [49] SIR EPIDEMICS ON A SCALE-FREE SPATIAL NESTED MODULAR NETWORK
    Gandolfi, Alberto
    Cecconi, Lorenzo
    ADVANCES IN APPLIED PROBABILITY, 2016, 48 (01) : 137 - 162
  • [50] A new scale-free network model for simulating and predicting epidemics
    Liang, Chen-Wei
    Ku, Chien-Kuo
    Liang, Jeng-Jong
    JOURNAL OF THEORETICAL BIOLOGY, 2013, 317 : 11 - 19