IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v119y2019icp180-187.html
   My bibliography  Save this article

Effect of information spreading to suppress the disease contagion on the epidemic vaccination game

Author

Listed:
  • Kabir, K.M. Ariful
  • Kuga, Kazuki
  • Tanimoto, Jun

Abstract

The information awareness about contagious diseases have an influential effect on an individual's decision to suppress the diffusion of infections. In this work, a new mathematical framework for a vaccination game combined with susceptible-infected-recovered (SIR) and unaware-aware (UA) situation is considered. Altering wearing mask or taking protection against diseases, we consider the information spreading effect that might be represented the situation of self-protection. The information spreading is supposed only for local situation for a season, but has a very significant effect to reduce the infection through a generation. Within this concept, unaware and aware states are taken for susceptible, infected and vaccinated individuals for an infinite and well mixed population. Moreover, three different strategy updating rules concerning whether an individual committing or not vaccination: individual based, strategy based and direct selection are studied to show the comparison by depicting as full phase diagram. Finally, it can be seen that information spreading can subdue the spreading of epidemic within a population.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:119:y:2019:i:c:p:180-187
    DOI: 10.1016/j.chaos.2018.12.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077918303291
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2018.12.023?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. Bin Wu & Feng Fu & Long Wang, 2011. "Imperfect Vaccine Aggravates the Long-Standing Dilemma of Voluntary Vaccination," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-7, June.
    2. Li, Chao & Wang, Li & Sun, Shiwen & Xia, Chengyi, 2018. "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 512-523.
    3. Iwamura, Yoshiro & Tanimoto, Jun, 2018. "Realistic decision-making processes in a vaccination game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 236-241.
    4. Zhen Wang & Marko Jusup & Lei Shi & Joung-Hun Lee & Yoh Iwasa & Stefano Boccaletti, 2018. "Exploiting a cognitive bias promotes cooperation in social dilemma experiments," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    5. repec:nas:journl:v:115:y:2018:p:30-35 is not listed on IDEAS
    6. Tanimoto, Jun, 2018. "Effect of noise-perturbing intermediate defense measures in voluntary vaccination gamesAuthor-Name: Ida, Yuki," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 337-341.
    7. Fukuda, Eriko & Kokubo, Satoshi & Tanimoto, Jun & Wang, Zhen & Hagishima, Aya & Ikegaya, Naoki, 2014. "Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 68(C), pages 1-9.
    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. Kabir, K.M. Ariful & Tanimoto, Jun, 2019. "Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 41-55.
    2. Kabir, K.M. Ariful, 2021. "How evolutionary game could solve the human vaccine dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Kabir, KM Ariful & Kuga, Kazuki & Tanimoto, Jun, 2020. "The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    4. 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.
    5. Kulsum, Umma & Alam, Muntasir & Kamrujjaman, Md., 2024. "Modeling and investigating the dilemma of early and delayed vaccination driven by the dynamics of imitation and aspiration," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    6. Alam, Muntasir & Tanaka, Masaki & Tanimoto, Jun, 2019. "A game theoretic approach to discuss the positive secondary effect of vaccination scheme in an infinite and well-mixed population," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 201-213.
    7. 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).
    8. Ullah, Mohammad Sharif & Higazy, M. & Kabir, K.M. Ariful, 2022. "Dynamic analysis of mean-field and fractional-order epidemic vaccination strategies by evolutionary game approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    9. Cui, Guang-Hai & Li, Jun-Li & Dong, Kun-Xiang & Jin, Xing & Yang, Hong-Yong & Wang, Zhen, 2024. "Influence of subsidy policies against insurances on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    10. Cui, Guang-Hai & Wang, Zhen & Li, Jun-Li & Jin, Xing & Zhang, Zhi-Wang, 2021. "Influence of precaution and dynamic post-indemnity based insurance policy on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    11. Meng, Xueyu & Lin, Jianhong & Fan, Yufei & Gao, Fujuan & Fenoaltea, Enrico Maria & Cai, Zhiqiang & Si, Shubin, 2023. "Coupled disease-vaccination behavior dynamic analysis and its application in COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    12. Liu, Chuang & Zhou, Nan & Zhan, Xiu-Xiu & Sun, Gui-Quan & Zhang, Zi-Ke, 2020. "Markov-based solution for information diffusion on adaptive social networks," Applied Mathematics and Computation, Elsevier, vol. 380(C).
    13. Wang, Qingqing & Du, Chunpeng & Geng, Yini & Shi, Lei, 2020. "Historical payoff can not overcome the vaccination dilemma on Barabási–Albert scale-free networks," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    14. Benyun Shi & Guangliang Liu & Hongjun Qiu & Yu-Wang Chen & Shaoliang Peng, 2019. "Voluntary Vaccination through Perceiving Epidemic Severity in Social Networks," Complexity, Hindawi, vol. 2019, pages 1-13, February.
    15. Alam, Muntasir & Ida, Yuki & Tanimoto, Jun, 2021. "Abrupt epidemic outbreak could be well tackled by multiple pre-emptive provisions-A game approach considering structured and unstructured populations," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    16. Kabir, K.M. Ariful & Tanimoto, Jun, 2021. "The role of pairwise nonlinear evolutionary dynamics in the rock–paper–scissors game with noise," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    17. Deng, Zheng-Hong & Wang, Zi-Ren & Wang, Huan-Bo & Xu, Lin, 2021. "The evolution of cooperation in multi-games with popularity-driven fitness calculation," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    18. 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).
    19. Li, Qiu & Li, MingChu & Lv, Lin & Guo, Cheng & Lu, Kun, 2017. "A new prediction model of infectious diseases with vaccination strategies based on evolutionary game theory," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 51-60.
    20. Li, Zhibin & Jia, Danyang & Guo, Hao & Geng, Yini & Shen, Chen & Wang, Zhen & Li, Xuelong, 2019. "The effect of multigame on cooperation in spatial network," Applied Mathematics and Computation, Elsevier, vol. 351(C), pages 162-167.

    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:chsofr:v:119:y:2019:i:c:p:180-187. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.