UM
A Bi-Virus Competing Spreading Model with Generic Infection Rates
Lu-Xing Yang1; Xiaofan Yang3; Yuan Yan Tang2
2018
Source PublicationIEEE Transactions on Network Science and Engineering
ISSN2327-4697
Volume5Issue:1Pages:2-13
Abstract

Due to widespread applications, the multi-virus competing spreading dynamics has recently aroused considerable interests. To our knowledge, all previous competing spreading models assume infection rates that are each linear in the virus occupancy probabilities of the individuals in a population. As linear infection rates are overestimation of real infection rates, in some situations these models cannot accurately predict the spreading process of multiple competing viruses. This work takes the first step toward enhancing the accuracy of multi-virus competing spreading models. A continuous-time bilayer-network-based bi-virus competing spreading model with generic infection rates is proposed. Criteria for the extinction of both viruses and for the survival of only one virus are presented, respectively. Numerical examples show that (1) if the generic bi-virus spreading model with linear infection rates predicts that the fraction of nodes infected with some virus would approach zero, the prediction of the fraction is accurate, and (2) if the scenario-relevant generic infection rates could be estimated accurately, the resulting model would be able to accurately forecast the evolutionary process of a pair of competing viruses.

KeywordCompeting Viruses Equilibrium Generic Infection Rate Global Attractivity Global Stability Linear Infection Rate Multilayer Network Virus Spreading Model
DOIhttps://doi.org/10.1109/TNSE.2017.2734075
URLView the original
Language英语
WOS Research AreaMathematics
WOS SubjectMathematics, Interdisciplinary Applications
WOS IDWOS:000426717000002
PublisherIEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
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Citation statistics
Cited Times [WOS]:40   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorLu-Xing Yang; Xiaofan Yang; Yuan Yan Tang
Affiliation1.Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, GA 2600, The Netherlands.
2.School of Software Engineering, Chongqing University, Chongqing, Shapingba 400044, P.R. China.
3.Department of Computer and Information Science, The University of Macau, Macau, 999078, China.
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Lu-Xing Yang,Xiaofan Yang,Yuan Yan Tang. A Bi-Virus Competing Spreading Model with Generic Infection Rates[J]. IEEE Transactions on Network Science and Engineering,2018,5(1):2-13.
APA Lu-Xing Yang,Xiaofan Yang,&Yuan Yan Tang.(2018).A Bi-Virus Competing Spreading Model with Generic Infection Rates.IEEE Transactions on Network Science and Engineering,5(1),2-13.
MLA Lu-Xing Yang,et al."A Bi-Virus Competing Spreading Model with Generic Infection Rates".IEEE Transactions on Network Science and Engineering 5.1(2018):2-13.
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