IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v140y2020ics0960077920305397.html

Impact of network assortativity on epidemic and vaccination behaviour

Author

Listed:
  • Chang, Sheryl L.
  • Piraveenan, Mahendra
  • Prokopenko, Mikhail

Abstract

The resurgence of measles is largely attributed to the decline in vaccine adoption and the increase in mobility. Although the vaccine for measles is readily available and highly successful, its current adoption is not adequate to prevent epidemics. Vaccine adoption is directly affected by individual vaccination decisions, and has a complex interplay with the spatial spread of disease shaped by an underlying mobility (travelling) network. In this paper, we model the travelling connectivity as a scale-free network, and investigate dependencies between the network’s assortativity and the resultant epidemic and vaccination dynamics. In doing so we extend an SIR-network model with game-theoretic components, capturing the imitation dynamics under a voluntary vaccination scheme. Our results show a correlation between the epidemic dynamics and the network’s assortativity, highlighting that networks with high assortativity tend to suppress epidemics under certain conditions. In highly assortative networks, the suppression is sustained producing an early convergence to equilibrium. In highly disassortative networks, however, the suppression effect diminishes over time due to scattering of non-vaccinating nodes, and frequent switching between the predominantly vaccinating and non-vaccinating phases of the dynamics.

Suggested Citation

  • Chang, Sheryl L. & Piraveenan, Mahendra & Prokopenko, Mikhail, 2020. "Impact of network assortativity on epidemic and vaccination behaviour," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    • Handle: RePEc:eee:chsofr:v:140:y:2020:i:c:s0960077920305397
    DOI: 10.1016/j.chaos.2020.110143
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920305397
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2020.110143?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Jamakovic, A. & Kooij, R.E. & van Mieghem, P. & van Dam, E.R., 2006. "Robustness of networks against viruses : The role of the spectral raduis," Other publications TiSEM 1b372c5c-dc77-45bd-824d-3, Tilburg University, School of Economics and Management.
    2. Marzieh Soltanolkottabi & David Ben-Arieh & Chih-Hang Wu, 2020. "Game Theoretic Modeling of Infectious Disease Transmission with Delayed Emergence of Symptoms," Games, MDPI, vol. 11(2), pages 1-17, April.
    3. Chris T Bauch & Samit Bhattacharyya, 2012. "Evolutionary Game Theory and Social Learning Can Determine How Vaccine Scares Unfold," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-12, April.
    4. Julien Arino & P. van den Driessche, 2003. "A multi-city epidemic model," Mathematical Population Studies, Taylor & Francis Journals, vol. 10(3), pages 175-193.
    5. M. Piraveenan & M. Prokopenko & A. Y. Zomaya, 2009. "Assortativeness and information in scale-free networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 291-300, February.
    6. 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).
    7. Huang, Jiechen & Wang, Juan & Xia, Chengyi, 2020. "Role of vaccine efficacy in the vaccination behavior under myopic update rule on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xin & Tang, Xuli & Lu, Wei, 2024. "Investigating clinical links in edge-labeled citation networks of biomedical research: A translational science perspective," Journal of Informetrics, Elsevier, vol. 18(3).
    2. 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).
    3. Jeong, Wonhee & Yu, Unjong, 2022. "Effects of quadrilateral clustering on complex contagion," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    4. Chen, Jie & Tan, Xuegang & Cao, Jinde & Li, Ming, 2022. "Effect of coupling structure on traffic-driven epidemic spreading in interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Das, Saikat & Bose, Indranil & Sarkar, Uttam Kumar, 2023. "Predicting the outbreak of epidemics using a network-based approach," European Journal of Operational Research, Elsevier, vol. 309(2), pages 819-831.
    6. Tao, Li & Kong, Shengzhou & He, Langzhou & Zhang, Fan & Li, Xianghua & Jia, Tao & Han, Zhen, 2022. "A sequential-path tree-based centrality for identifying influential spreaders in temporal networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

    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. Sheryl Le Chang & Mahendra Piraveenan & Mikhail Prokopenko, 2019. "The Effects of Imitation Dynamics on Vaccination Behaviours in SIR-Network Model," IJERPH, MDPI, vol. 16(14), pages 1-31, July.
    2. Nishimura, Itsuki & Arefin, Md. Rajib & Tatsukawa, Yuichi & Utsumi, Shinobu & Hossain, Md. Anowar & Tanimoto, Jun, 2023. "Social dilemma analysis on vaccination game accounting for the effect of immunity waning," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    3. Kabir, K.M. Ariful, 2021. "How evolutionary game could solve the human vaccine dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. 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).
    5. 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.
    6. Kimberly M. Thompson, 2016. "Evolution and Use of Dynamic Transmission Models for Measles and Rubella Risk and Policy Analysis," Risk Analysis, John Wiley & Sons, vol. 36(7), pages 1383-1403, July.
    7. Arcagni, Alberto & Grassi, Rosanna & Stefani, Silvana & Torriero, Anna, 2017. "Higher order assortativity in complex networks," European Journal of Operational Research, Elsevier, vol. 262(2), pages 708-719.
    8. 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).
    9. Huang, He & Xu, Yang & Xing, Jingli & Shi, Tianyu, 2023. "Social influence or risk perception? A mathematical model of self-protection against asymptomatic infection in multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    10. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    11. Liu, Junli & Zhou, Yicang, 2009. "Global stability of an SIRS epidemic model with transport-related infection," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 145-158.
    12. 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).
    13. Mahendra Piraveenan & Mikhail Prokopenko & Liaquat Hossain, 2013. "Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
    14. Wanduku, Divine, 2017. "Complete global analysis of a two-scale network SIRS epidemic dynamic model with distributed delay and random perturbations," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 49-76.
    15. Yanling Zhang & Feng Fu, 2018. "Strategy intervention for the evolution of fairness," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-13, May.
    16. Deka, Aniruddha & Bhattacharyya, Samit, 2022. "The effect of human vaccination behaviour on strain competition in an infectious disease: An imitation dynamic approach," Theoretical Population Biology, Elsevier, vol. 143(C), pages 62-76.
    17. Sharma, Natasha & Gupta, Arvind Kumar, 2017. "Impact of time delay on the dynamics of SEIR epidemic model using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 114-125.
    18. Yunhwan Kim & Ana Vivas Barber & Sunmi Lee, 2020. "Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.
    19. Sakthivel, Rathinasamy & Suveetha, V.T. & Nithya, Venkatesh & Sakthivel, Ramalingam, 2020. "Finite-time fault detection filter design for complex systems with multiple stochastic communication and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    20. He, Jialu & Lan, Xue & Zheng, Yupeng & Zhang, Han & Liu, Chunhe, 2025. "The impact of preference selection based on influence in spatial evolutionary vaccination game," Chaos, Solitons & Fractals, Elsevier, vol. 199(P3).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:140:y:2020:i:c:s0960077920305397. 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.