Diffusion of resources and their impact on epidemic spreading in multilayer networks with simplicial complexes

被引:46
|
作者
Sun, Qingyi [1 ]
Wang, Zhishuang [2 ]
Zhao, Dawei [3 ]
Xia, Chengyi [4 ]
Perc, Matjaz [5 ,6 ,7 ,8 ]
机构
[1] Tianjin Univ Technol, Tianjin Key Lab Intelligence Comp & Novel Software, Tianjin 300384, Peoples R China
[2] Wuyi Univ, Fac Intelligence Manufacture, Jiangmen 529020, Peoples R China
[3] Qilu Univ Technol, Shandong Acad Sci, Shandong Comp Sci Ctr, Natl Supercomp Ctr Jinan,Shandong Prov Key Lab Com, Jinan 250014, Peoples R China
[4] Tiangong Univ, Sch Control Sci & Engn, Tianjin 300387, Peoples R China
[5] Univ Maribor, Fac Nat Sci & Math, Koroska Cesta 160, Maribor 2000, Slovenia
[6] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
[7] Alma Mater Europaea, Slovenska Ul 17, Maribor 2000, Slovenia
[8] Complex Sci Hub Vienna, Josefstadterstr 39, A-1080 Vienna, Austria
关键词
Simplicial complexes; Resource diffusion; Epidemic spreading; Two-layered complex network; AWARENESS; MODEL; POPULATIONS; VACCINATION; DISEASES; POLICY; MEDIA;
D O I
10.1016/j.chaos.2022.112734
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Recent studies have shown that personal resources have a significant impact on the dynamics of epidemic spreading. In previous studies, the main way for individuals to be able to obtain resources was through pairwise interactions. However, the human relationship network is often characterized also by group interactions, not just by pairwise interactions. To study the impact of resource diffusion on disease propagation in such higher -order networks, we therefore propose a multilayer network model, where the upper-layer network represents a resource network composed of random simplicial complexes to transmit resources, while the lower-layer network represents the network of physical contacts where the disease can spread. We derive the outbreak threshold expression for the epidemic by means of the micro Markov chain method, which reveals that the diffusion of resources may substantially change the epidemic threshold. We also show that the final fractions of infected individuals obtained via the micro Markov chain method and the classical Monte Carlo method are very similar, thus confirming that the model can predict well the epidemic spreading within the networked population. Finally, through extensive simulations, we show also that increasing the spread of resources on 2 -simplexes can suppress the epidemic spreading and outbreaks, thus outlining possibilities for novel containment strategies.
引用
收藏
页数:8
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