IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v417y2022ics0096300321008559.html
   My bibliography  Save this article

Markovian approach to tackle competing pathogens in simplicial complex

Author

Listed:
  • Nie, Yanyi
  • Li, Wenyao
  • Pan, Liming
  • Lin, Tao
  • Wang, Wei

Abstract

Recent studies on network spreading dynamics often adopt pairwise interaction to describe the simple spreading process while using higher-order interaction to describe the collective behavior of the dynamical system on the network. However, the interaction between competing pathogens usually includes both pairwise and high-order interactions. Due to dynamic correlation, it is hard to solve the theory by considering two modes of interaction. Here, we propose a theoretical analysis framework based on Microscopic Markov Chain Approach (MMCA) to solve simplicial competing spreading involving pairwise and high-order interactions. Because of the competitive mechanism in the framework, a susceptible node can only be infected by one pathogen, and contagion can spread simultaneously through pairwise interactions (1-simplices) and higher-order interactions, i.e., 2-simplices. The theory and simulation agree in good accuracy on real networks and artificial networks, which reveals the validity of the theoretical analysis and indicates that the initial density of the two pathogens and the infection rate of 1-simplices act together on the process of pathogen transmission. The effect of 1-simplices and 2-simplices infection rates of two pathogens are also included in the discussion. When the average degree of the network is fixed, in the case of a larger average number of 1-simplices incidents on a node, infection rates of pathogen A is greater than infection rates of pathogen B may result in final infection density of pathogen A greater than the final infection density of pathogen B. We discuss the influences of 1-simplices average degree and 2-simplices average degree on the final infection range. We find that with the increase of 1-simplices average degree, the pathogen may undergo a transition from outbreak to death while increasing the 2-simplices average degree is more conducive to spreading. Finally, in the study of two different seed selection strategies, we find that selecting the nodes with the highest degree as seeds can promote pathogen spreading more than randomly selecting seeds.

Suggested Citation

  • Nie, Yanyi & Li, Wenyao & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Markovian approach to tackle competing pathogens in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 417(C).
    • Handle: RePEc:eee:apmaco:v:417:y:2022:i:c:s0096300321008559
    DOI: 10.1016/j.amc.2021.126773
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321008559
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2021.126773?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. 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).
    2. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    3. Li, WenYao & Xue, Xiaoyu & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Competing spreading dynamics in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    4. M E J Newman & Carrie R Ferrario, 2013. "Interacting Epidemics and Coinfection on Contact Networks," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    5. Bjarke Mønsted & Piotr Sapieżyński & Emilio Ferrara & Sune Lehmann, 2017. "Evidence of complex contagion of information in social media: An experiment using Twitter bots," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-12, September.
    6. Iacopo Iacopini & Giovanni Petri & Alain Barrat & Vito Latora, 2019. "Simplicial models of social contagion," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    7. Unai Alvarez-Rodriguez & Federico Battiston & Guilherme Ferraz Arruda & Yamir Moreno & Matjaž Perc & Vito Latora, 2021. "Evolutionary dynamics of higher-order interactions in social networks," Nature Human Behaviour, Nature, vol. 5(5), pages 586-595, May.
    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, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Tan, Jipeng & Zhang, Man & Liu, Fengming, 2024. "Online-Offline Higher-Order Rumor Propagation Model Based on Quantum Cellular Automata Considering Social Adaptation," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    3. Li, Tianyu & Wu, Yong & Ding, Qianming & Xie, Ying & Yu, Dong & Yang, Lijian & Jia, Ya, 2024. "Social contagion in high-order network with mutation," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    4. Ma, Ning & Yu, Guang & Jin, Xin, 2024. "Dynamics of competing public sentiment contagion in social networks incorporating higher-order interactions during the dissemination of public opinion," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    5. Tian, Yang & Tian, Hui & Cui, Yajuan & Zhu, Xuzhen & Cui, Qimei, 2023. "Influence of behavioral adoption preference based on heterogeneous population on multiple weighted networks," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    6. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2023. "Pathogen diversity in meta-population networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    7. Xie, Ying & Zhou, Ping & Yao, Zhao & Ma, Jun, 2022. "Response mechanism in a functional neuron under multiple stimuli," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    8. Wu, Qingchu & Kabir, K.M. Ariful, 2023. "Compact pairwise methods for susceptible–infected–susceptible epidemics on weighted heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    9. You, Xuemei & Zhang, Man & Ma, Yinghong & Tan, Jipeng & Liu, Zhiyuan, 2023. "Impact of higher-order interactions and individual emotional heterogeneity on information-disease coupled dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

    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. Li, WenYao & Xue, Xiaoyu & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Competing spreading dynamics in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    2. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2022. "Homophily in competing behavior spreading among the heterogeneous population with higher-order interactions," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    3. Ma, Ning & Yu, Guang & Jin, Xin, 2024. "Dynamics of competing public sentiment contagion in social networks incorporating higher-order interactions during the dissemination of public opinion," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    4. Zhao, Dandan & Li, Runchao & Peng, Hao & Zhong, Ming & Wang, Wei, 2022. "Percolation on simplicial complexes," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    5. Zhang, Ziyu & Mei, Xuehui & Jiang, Haijun & Luo, Xupeng & Xia, Yang, 2023. "Dynamical analysis of Hyper-SIR rumor spreading model," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    6. Li, Xueqi & Ghosh, Dibakar & Lei, Youming, 2023. "Chimera states in coupled pendulum with higher-order interaction," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    7. Luca Gallo & Lucas Lacasa & Vito Latora & Federico Battiston, 2024. "Higher-order correlations reveal complex memory in temporal hypergraphs," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    8. Guilherme Ferraz de Arruda & Giovanni Petri & Pablo Martin Rodriguez & Yamir Moreno, 2023. "Multistability, intermittency, and hybrid transitions in social contagion models on hypergraphs," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    9. Wang, Wei & Li, Wenyao & Lin, Tao & Wu, Tao & Pan, Liming & Liu, Yanbing, 2022. "Generalized k-core percolation on higher-order dependent networks," Applied Mathematics and Computation, Elsevier, vol. 420(C).
    10. Almiala, Into & Aalto, Henrik & Kuikka, Vesa, 2023. "Influence spreading model for partial breakthrough effects on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    11. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2023. "Pathogen diversity in meta-population networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    12. Li, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    13. Zhao, Dandan & Li, Runchao & Peng, Hao & Zhong, Ming & Wang, Wei, 2022. "Higher-order percolation in simplicial complexes," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    14. Martina Contisciani & Federico Battiston & Caterina De Bacco, 2022. "Inference of hyperedges and overlapping communities in hypergraphs," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    15. Ramasamy, Mohanasubha & Devarajan, Subhasri & Kumarasamy, Suresh & Rajagopal, Karthikeyan, 2022. "Effect of higher-order interactions on synchronization of neuron models with electromagnetic induction," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    16. Lv, Xijian & Fan, Dongmei & Yang, Junxian & Li, Qiang & Zhou, Li, 2024. "Delay differential equation modeling of social contagion with higher-order interactions," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    17. Ma, Jinlong & Wang, Peng, 2024. "Impact of community networks with higher-order interaction on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    18. Iacopo Iacopini & Márton Karsai & Alain Barrat, 2024. "The temporal dynamics of group interactions in higher-order social networks," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    19. Li, Tianyu & Wu, Yong & Ding, Qianming & Xie, Ying & Yu, Dong & Yang, Lijian & Jia, Ya, 2024. "Social contagion in high-order network with mutation," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    20. Sun, Qingyi & Wang, Zhishuang & Zhao, Dawei & Xia, Chengyi & Perc, Matjaž, 2022. "Diffusion of resources and their impact on epidemic spreading in multilayer networks with simplicial complexes," Chaos, Solitons & Fractals, Elsevier, vol. 164(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:apmaco:v:417:y:2022:i:c:s0096300321008559. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.