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Infection-Probability-Dependent Interlayer Interaction Propagation Processes in Multiplex Networks
Liu, Juan1,2; Wu, Xiaoqun3,4; Lu, Jinhu5; Wei, Xiang6
2021-02-01
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN2168-2216
Volume51Issue:2Pages:1085-1096
AbstractDifferent spreading processes in multiplex networks may interact with each other and display intertwined effects. In this paper, we propose a theoretical framework called infection-probability-dependent interlayer interaction propagation processes in multiplex networks with an arbitrary number of layers, to more precisely depict the intertwined effects which bring challenges to the existing state-dependent interlayer interaction models. Specifically, the spreading rate of each node is regulated by the proposed spreading rate function (SRF) which depends on both the intrinsic dynamics in its layer and the infection probabilities of its counterparts. We propose an algorithm to obtain the spreading threshold of each layer of the proposed theoretical framework. We analyze the three-layer tuberculosis-awareness-flu model with the SRF of each node being the expectation of infection-probability-dependent spreading rate. This paper gives a thorough and detailed numerical investigation of the impact and interaction of system settings and the spreading threshold of each layer. We find that for tuberculosis spreading which is in competing relation with awareness and cooperation relation with flu, the epidemic threshold is a constant when other layers' intrinsic spreading rates are small. The cooperation layer has dramatic influence on the constant while the competing layer has no effect on it.
KeywordEpidemic threshold multiplex network propagation process spreading rate function (SRF)
DOI10.1109/TSMC.2018.2884894
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFB0800401] ; National Natural Science Foundation of China[61621003] ; National Natural Science Foundation of China[61532020] ; National Natural Science Foundation of China[11472290] ; National Natural Science Foundation of China[61573262] ; Local Undergraduate Colleges and Universities Joint Special Foundation of Yunnan Provincial Science and Technology Department[2017FH001062]
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000608693000039
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/58059
Collection中国科学院数学与系统科学研究院
Corresponding AuthorLu, Jinhu
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
3.Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
4.Wuhan Univ, Hubei Key Lab Computat Sci, Wuhan 430072, Peoples R China
5.Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Sch Automat Sci & Elect Engn, State Key Lab Software Dev Environm, Beijing 100191, Peoples R China
6.Honghe Univ, Dept Engn, Mengzi 661199, Peoples R China
Recommended Citation
GB/T 7714
Liu, Juan,Wu, Xiaoqun,Lu, Jinhu,et al. Infection-Probability-Dependent Interlayer Interaction Propagation Processes in Multiplex Networks[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(2):1085-1096.
APA Liu, Juan,Wu, Xiaoqun,Lu, Jinhu,&Wei, Xiang.(2021).Infection-Probability-Dependent Interlayer Interaction Propagation Processes in Multiplex Networks.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(2),1085-1096.
MLA Liu, Juan,et al."Infection-Probability-Dependent Interlayer Interaction Propagation Processes in Multiplex Networks".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.2(2021):1085-1096.
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