IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v188y2021icp268-279.html
   My bibliography  Save this article

Interplay between epidemic and information spreading on multiplex networks

Author

Listed:
  • Zhu, Linhe
  • Liu, Wenshan
  • Zhang, Zhengdi

Abstract

Every outbreak of a serious infectious disease has the potential to pose unprecedented challenges to humanity. Understanding how epidemic spreads among populations is a key step in preventing and controlling it to spread. In this paper, for modeling the epidemic spreading and its associated information spreading, we put forward a novel coupled two-layered networking framework. One layer deals with the modeling of an SI1I2R process, where each node in the network may be in four states: susceptible, mildly infected, severely infected and recovery. Whereas, for the other layer, the transmission dynamics can be represented by an unaware–aware–refractory (UAT) model, which is significantly different from the classical unaware–aware–unaware (UAU) process since there exist individuals who are unwilling to share information. Moreover, we set a group of discrete time Microscopic Markov equations and derive the epidemic threshold. Finally, some numerical simulations are carried out to validate the analytical results. This work is of great significance to prevent epidemic, and it can be applicable in guiding the input on disease-related information on complex networks.

Suggested Citation

  • Zhu, Linhe & Liu, Wenshan & Zhang, Zhengdi, 2021. "Interplay between epidemic and information spreading on multiplex networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 268-279.
    • Handle: RePEc:eee:matcom:v:188:y:2021:i:c:p:268-279
    DOI: 10.1016/j.matcom.2021.04.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037847542100135X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2021.04.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Zhishuang & Guo, Quantong & Sun, Shiwen & Xia, Chengyi, 2019. "The impact of awareness diffusion on SIR-like epidemics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 134-147.
    2. Miao Peng & Zhengdi Zhang & C. W. Lim & Xuedi Wang, 2018. "Hopf Bifurcation and Hybrid Control of a Delayed Ecoepidemiological Model with Nonlinear Incidence Rate and Holling Type II Functional Response," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-12, June.
    3. Huo, Liang’an & Guo, Hongyuan & Cheng, Yingying & Xie, Xiaoxiao, 2020. "A new model for supply chain risk propagation considering herd mentality and risk preference under warning information on multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Kabir, K.M. Ariful & Kuga, Kazuki & Tanimoto, Jun, 2019. "Effect of information spreading to suppress the disease contagion on the epidemic vaccination game," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 180-187.
    5. Zhu, Linhe & Liu, Wenshan & Zhang, Zhengdi, 2020. "Delay differential equations modeling of rumor propagation in both homogeneous and heterogeneous networks with a forced silence function," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    6. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, He & Chen, Yahong & Yan, Zhijun, 2021. "Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model," Applied Mathematics and Computation, Elsevier, vol. 398(C).
    2. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    3. Zhu, Linhe & Huang, Xiaoyuan, 2021. "Modeling the dynamics of multi-cluster information propagation in presence of time delay," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    4. Dong, Yafang & Huo, Liang'an & Zhao, Laijun, 2022. "An improved two-layer model for rumor propagation considering time delay and event-triggered impulsive control strategy," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    5. Jia Wang & Zhiping Wang & Ping Yu & Peiwen Wang, 2022. "The SEIR Dynamic Evolutionary Model with Markov Chains in Hyper Networks," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    6. Yin, Qian & Wang, Zhishuang & Xia, Chengyi & Dehmer, Matthias & Emmert-Streib, Frank & Jin, Zhen, 2020. "A novel epidemic model considering demographics and intercity commuting on complex dynamical networks," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    7. Meng, Xueyu & Cai, Zhiqiang & Si, Shubin & Duan, Dongli, 2021. "Analysis of epidemic vaccination strategies on heterogeneous networks: Based on SEIRV model and evolutionary game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    8. Sang, Chun-Yan & Liao, Shi-Gen, 2020. "Modeling and simulation of information dissemination model considering user’s awareness behavior in mobile social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    9. Tao, Xiangyu & Zhu, Linhe, 2021. "Study of periodic diffusion and time delay induced spatiotemporal patterns in a predator-prey system," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    10. Huo, Liang’an & Chen, Sijing, 2020. "Rumor propagation model with consideration of scientific knowledge level and social reinforcement in heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    11. Kabir, K.M. Ariful & Tanimoto, Jun, 2019. "Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 229-239.
    12. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    13. An, Xuming & Ding, Li & Hu, Ping, 2020. "Information propagation with individual attention-decay effect on activity-driven networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    14. Zhang, Jing & Wang, Xiaoli & Xie, Yanxi & Wang, Meihua, 2022. "Research on multi-topic network public opinion propagation model with time delay in emergencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. Wu, Jiang & Zuo, Renxian & He, Chaocheng & Xiong, Hang & Zhao, Kang & Hu, Zhongyi, 2022. "The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    16. Wang, Jianwei & Xu, Wenshu & Chen, Wei & Yu, Fengyuan & He, Jialu, 2021. "Information sharing can suppress the spread of epidemics: Voluntary vaccination game on two-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    17. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The effect of individual attitude on cooperation in social dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    18. Zenghui Yue & Haiyun Xu & Guoting Yuan & Yan Qi, 2022. "Modeling knowledge diffusion in the disciplinary citation network based on differential dynamics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7593-7613, December.
    19. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    20. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The interplay of behaviors and attitudes in public goods game considering environmental investment," Applied Mathematics and Computation, Elsevier, vol. 382(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:188:y:2021:i:c:p:268-279. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.