IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v495y2025ics0096300325000451.html
   My bibliography  Save this article

Mitigating infection in prey through cooperative behavior under fear-induced defense

Author

Listed:
  • Kabir, K.M. Ariful

Abstract

This study investigates an eco-epidemiological model that incorporates disease dynamics in prey populations while considering the impact of predator-induced fear on prey species. A pairwise evolutionary game theory model, which incorporates prey species behavior to mitigate infection, is also examined. Prey individuals can employ two behavioral tactics, cooperation, and defection, to reduce infection. The behavioral changes in prey are described using a game dynamic model based on replicator equations, where the gain depends on pairwise dyadic interactions. Without predator species, the prey population is assumed to grow logistically, with the disease affecting only the prey. The prey population is divided into susceptible prey and infected prey. Predators, which are not infected by the disease, feed on both susceptible and infected prey. The presence of predators induces fear in the prey, making them more vigilant and reducing their contact with infected individuals. This decreased contact lowers the chance of infection among susceptible prey. Infected prey, being more watchful, are unaffected by the fear of predators. The equilibrium points of the system and their stability are analyzed. As the level of fear increases, the system shifts from limit cycle oscillations to a steady state. While increasing fear levels do not eradicate the disease, they do reduce the amplitude of the infected prey population. The system's stability changes with varying infection rates, leading to predator extinction when the infection rate in prey is sufficiently high despite predators not being infected. This study reveals that fear and behavioral control strategies can contribute to eradicating the disease. Increasing levels of fear have a passive effect on reducing the infected population, while control behavior has an active impact, highlighting a critical insight that strengthens the model. These findings enhance the understanding of the system's dynamic behavior.

Suggested Citation

  • Kabir, K.M. Ariful, 2025. "Mitigating infection in prey through cooperative behavior under fear-induced defense," Applied Mathematics and Computation, Elsevier, vol. 495(C).
    • Handle: RePEc:eee:apmaco:v:495:y:2025:i:c:s0096300325000451
    DOI: 10.1016/j.amc.2025.129318
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300325000451
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2025.129318?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. 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.
    2. Fernando P. Santos & Francisco C. Santos & Jorge M. Pacheco, 2018. "Social norm complexity and past reputations in the evolution of cooperation," Nature, Nature, vol. 555(7695), pages 242-245, March.
    3. Saifuddin, Md. & Biswas, Santanu & Samanta, Sudip & Sarkar, Susmita & Chattopadhyay, Joydev, 2016. "Complex dynamics of an eco-epidemiological model with different competition coefficients and weak Allee in the predator," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 270-285.
    4. Bozkurt, Fatma & Yousef, Ali & Abdeljawad, Thabet & Kalinli, Adem & Mdallal, Qasem Al, 2021. "A fractional-order model of COVID-19 considering the fear effect of the media and social networks on the community," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Sudeshna Mondal & G. P. Samanta & Juan J. Nieto & Eberhard O. Voit, 2021. "Dynamics of a Predator-Prey Population in the Presence of Resource Subsidy under the Influence of Nonlinear Prey Refuge and Fear Effect," Complexity, Hindawi, vol. 2021, pages 1-38, July.
    6. Jana, Soovoojeet & Kar, T.K., 2013. "Modeling and analysis of a prey–predator system with disease in the prey," Chaos, Solitons & Fractals, Elsevier, vol. 47(C), pages 42-53.
    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. "Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 229-239.
    2. Zhao, Jie & Wang, Zhen & Yu, Dengxiu & Cao, Jinde & Cheong, Kang Hao, 2024. "Swarm intelligence for protecting sensitive identities in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    3. Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2022. "Migration based on environment comparison promotes cooperation in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    4. Zhou, Chen & Zhu, Yuying & Zhao, Dawei & Xia, Chengyi, 2024. "An evolutionary trust game model with group reputation within the asymmetric population," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    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. 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.
    7. 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.
    8. Juneja, Nishant & Agnihotri, Kulbhushan, 2018. "Conservation of a predator species in SIS prey-predator system using optimal taxation policy," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 86-94.
    9. Xu, Yuxin & Gao, Fei, 2024. "A novel higher-order Deffuant–Weisbuch networks model incorporating the Susceptible Infected Recovered framework," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    10. Zhang, Zhipeng & Wu, Yu’e & Zhang, Shuhua, 2022. "Reputation-based asymmetric comparison of fitness promotes cooperation on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    11. Laura Schmid & Farbod Ekbatani & Christian Hilbe & Krishnendu Chatterjee, 2023. "Quantitative assessment can stabilize indirect reciprocity under imperfect information," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    12. Quan, Ji & Nie, Jiacheng & Chen, Wenman & Wang, Xianjia, 2022. "Keeping or reversing social norms promote cooperation by enhancing indirect reciprocity," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    13. 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).
    14. Zhen Wang & Ruiqi Song & Chen Shen & Shiya Yin & Zhao Song & Balaraju Battu & Lei Shi & Danyang Jia & Talal Rahwan & Shuyue Hu, 2024. "Overcoming the Machine Penalty with Imperfectly Fair AI Agents," Papers 2410.03724, arXiv.org, revised May 2025.
    15. Yang, Guoli & Wu, Yu'e & Cavaliere, Matteo, 2024. "Information-driven cooperation on adaptive cyber-physical systems," Applied Mathematics and Computation, Elsevier, vol. 466(C).
    16. Kejriwal, Saransh & Sheth, Sarjan & Silpa, P.S. & Sarkar, Sumit & Guha, Apratim, 2022. "Attaining herd immunity to a new infectious disease through multi-stage policies incentivising voluntary vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    17. Mondal, Bapin & Ghosh, Uttam & Sarkar, Susmita & Tiwari, Pankaj Kumar, 2024. "A generalist predator–prey system with the effects of fear and refuge in deterministic and stochastic environments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 225(C), pages 968-991.
    18. Shirsendu Podder & Simone Righi, 2023. "Complexity of Behavioural Strategies and Cooperation in the Optional Public Goods Game," Dynamic Games and Applications, Springer, vol. 13(4), pages 1219-1235, December.
    19. Mendonça, J.P. & Brum, Arthur A. & Lyra, M.L. & Lira, Sérgio A., 2024. "Evolutionary game dynamics and the phase portrait diversity in a pandemic scenario," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    20. Alessandra F. Lütz & Marco Antonio Amaral & Ian Braga & Lucas Wardil, 2023. "Invasion of Optimal Social Contracts," Games, MDPI, vol. 14(3), pages 1-14, May.

    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:apmaco:v:495:y:2025:i:c:s0096300325000451. 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.