The spreading time in SIS epidemics on networks

被引:6
|
作者
He, Zhidong [1 ]
Van Mieghem, Piet [1 ]
机构
[1] Delft Univ Technol, Fac EECS, POB 5031, NL-2600 GA Delft, Netherlands
关键词
SIS epidemics; Spreading time; Heavy-tailed distribution; TOPOLOGY;
D O I
10.1016/j.physa.2017.12.048
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In a Susceptible-Infected-Susceptible (SIS) process, we investigate the spreading time T-m, which is the time when the number of infected nodes in the metastable state is first reached, starting from the outbreak of the epidemics. We observe that the spreading time Tm resembles a lognormal-like distribution, though with different deep tails, both for the Markovian and the non-Markovian infection process, which implies that the spreading time can be very long with a relatively high probability. In addition, we show that a stronger virus, with a higher effective infection rate tau or an earlier timing of the infection attempts, does not always lead to a shorter average spreading time E[T-m]. We numerically demonstrate that the average spreading time E[T-m] in the complete graph and the star graph scales logarithmically as a function of the network size N for a fixed fraction of infected nodes in the metastable state. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:317 / 330
页数:14
相关论文
共 50 条
  • [21] Vaccinating SIS epidemics in networks with zero-determinant strategy
    Li, Xiaojie
    Li, Cong
    Li, Xiang
    2017 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2017, : 2275 - 2278
  • [22] Vaccinating SIS epidemics under evolving perception in heterogeneous networks
    Xiao-Jie Li
    Xiang Li
    The European Physical Journal B, 2020, 93
  • [23] SIS model of epidemic spreading on dynamical networks with community
    Chengyi Xia
    Shiwen Sun
    Feng Rao
    Junqing Sun
    Jinsong Wang
    Zengqiang Chen
    Frontiers of Computer Science in China, 2009, 3 : 361 - 365
  • [24] SIS model of epidemic spreading on dynamical networks with community
    Xia, Chengyi
    Sun, Shiwen
    Rao, Feng
    Sun, Junqing
    Wang, Jinsong
    Chen, Zengqiang
    FRONTIERS OF COMPUTER SCIENCE IN CHINA, 2009, 3 (03): : 361 - 365
  • [25] Chaotic spreading of epidemics in complex networks of excitable units
    Vannucchi, FS
    Boccaletti, S
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2004, 1 (01) : 49 - 55
  • [26] Estimating the state of epidemics spreading with graph neural networks
    Abhishek Tomy
    Matteo Razzanelli
    Francesco Di Lauro
    Daniela Rus
    Cosimo Della Santina
    Nonlinear Dynamics, 2022, 109 : 249 - 263
  • [27] The effects of global awareness on the spreading of epidemics in multiplex networks
    Zang, Haijuan
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 492 : 1495 - 1506
  • [28] Estimating the state of epidemics spreading with graph neural networks
    Tomy, Abhishek
    Razzanelli, Matteo
    Di Lauro, Francesco
    Rus, Daniela
    Della Santina, Cosimo
    NONLINEAR DYNAMICS, 2022, 109 (01) : 249 - 263
  • [29] Competing spreading processes on multiplex networks: Awareness and epidemics
    Granell, Clara
    Gomez, Sergio
    Arenas, Alex
    PHYSICAL REVIEW E, 2014, 90 (01)
  • [30] Optimal policy design to mitigate epidemics on networks using an SIS model
    Cenedese, Carlo
    Zino, Lorenzo
    Cucuzzella, Michele
    Cao, Ming
    2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2021, : 4266 - 4271