Epidemic spreading under infection-reduced-recovery

被引:8
|
作者
Zhang, Xiyun [1 ]
Ruan, Zhongyuan [2 ]
Zheng, Muhua [3 ,4 ]
Barzel, Baruch [5 ,6 ]
Boccaletti, Stefano [7 ,8 ,9 ]
机构
[1] Jinan Univ, Dept Phys, Guangzhou 510632, Guangdong, Peoples R China
[2] Zhejiang Univ Technol, Inst Cyberspace Secur, Hangzhou 310023, Zhejiang, Peoples R China
[3] Univ Barcelona, Dept Fis Mat Condensada, E-08028 Barcelona, Spain
[4] Univ Barcelona, Inst Complex Syst UBICS, Barcelona, Spain
[5] Bar Ilan Univ, Dept Math, IL-5290002 Ramat Gan, Israel
[6] Bar Ilan Univ, Gonda Multidisciplinary Brain Res Ctr, IL-5290002 Ramat Gan, Israel
[7] CNR, Inst Complex Syst, Via Madonna Piano 10, I-50019 Sesto Fiorentino, Italy
[8] Northwestern Polytech Univ, Unmanned Syst Res Inst, Xian 710072, Peoples R China
[9] Natl Res Univ, Moscow Inst Phys & Technol, 9 Inst Skiy Per, Dolgoprudnyi 141701, Moscow Region, Russia
基金
以色列科学基金会;
关键词
Epidemic Spreading; Covid-19; Complex Networks; Dynamical Phase Transition; Explosive Ttransitions; SIS Model;
D O I
10.1016/j.chaos.2020.110130
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The pandemic transition is a hallmark of current epidemiological models, predicting a continuous shift from a healthy to a pandemic state, whose critical point is driven by the parameters of the disease, e.g., its infection, recovery or mortality rates. These parameters, characterizing the disease cycle, are tuned by the biological characteristics of the pathogen, capturing its natural time-scales, often considered independent of the state of the spread itself. If, however, the disease gains a population-wide impact, its prevalence may exceed the health-care system capacity, resulting in sub-optimal treatment, and hence a potential feedback mechanism, in which the disease cycle is no longer decoupled from the state of the spread. Such dependence was demonstrated during the spread of COVID-19, for instance, where hard-hit places showed elevated mortality rates, likely due to an over-stressed health-care system. We therefore introduce an infection-reduced recovery mechanism, linking an individual's rate of recovery to the prevalence of the disease. The outcome, we show, may have dramatic consequences on the observed patterns of spread. For instance, under rather broad conditions, the pandemic transition becomes discontinuous, exhibiting an abrupt shift from a healthy to a pandemic state. In some cases the disease reaches population-wide coverage even below the classically predicted critical transition point. We also observe a potential multi-stability and hysteresis, capturing an irreversible pandemic transition, in which overcoming the disease requires us to quench infection rates significantly below the critical threshold. These findings not only provide hints on the current difficulties to contain COVID-19, but more broadly, they set the bar for sustaining a stably functioning treatment capacity in the face of population-wide demand. (c) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] SIS epidemic spreading with correlated heterogeneous infection rates
    Qu, Bo
    Wang, Huiijuan
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2017, 472 : 13 - 24
  • [2] Targeted Recovery as an Effective Strategy against Epidemic Spreading
    Bottcher, L.
    Andrade, J. S., Jr.
    Herrmann, H. J.
    SCIENTIFIC REPORTS, 2017, 7
  • [3] Epidemic spreading in metapopulation networks with heterogeneous infection rates
    Gong, Yong-Wang
    Song, Yu Rong
    Jiang, Guo-Ping
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2014, 416 : 208 - 218
  • [4] EFFECTS OF MOTION ON EPIDEMIC SPREADING
    Buscarino, Arturo
    Di Stefano, Agnese
    Fortuna, Luigi
    Frasca, Mattia
    Latora, Vito
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2010, 20 (03): : 765 - 773
  • [5] SEAIR Epidemic spreading model of COVID-19
    Basnarkov, Lasko
    CHAOS SOLITONS & FRACTALS, 2021, 142
  • [6] Dynamics of public opinion under the influence of epidemic spreading
    Wu, Junhui
    Ni, Shunjiang
    Shen, Shifei
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2016, 27 (07):
  • [7] Epidemic spreading in complex networks
    Ruan ZhongYuan
    SCIENTIA SINICA-PHYSICA MECHANICA & ASTRONOMICA, 2020, 50 (01)
  • [8] A novel epidemic spreading model with decreasing infection rate based on infection times
    Huang, Yunhan
    Ding, Li
    Feng, Yun
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 444 : 1041 - 1048
  • [9] Dynamic properties of epidemic spreading on finite size complex networks
    Ying, L
    Yang, L
    Shan, XM
    Ren, Y
    Jiao, J
    Qiu, B
    CHINESE PHYSICS, 2005, 14 (11): : 2153 - 2157
  • [10] The influence of time delay on epidemic spreading under limited resources
    Jiang, Jian
    Zhou, Tianshou
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 508 : 414 - 423