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Epidemic Dynamics of Two-Pathogen Spreading for Pairwise Models

Author

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  • Shanshan Chen

    (School of Computer Science, Shanghai University of Engineering Science, Shanghai 201620, China
    These authors contributed equally to this work.)

  • Yijun Ran

    (College of Computer and Information Science, Southwest University, Chongqing 400715, China
    These authors contributed equally to this work.)

  • Hebo Huang

    (School of Journalism and Communication, Chongqing University, Chongqing 401331, China)

  • Zhenzhen Wang

    (School of Communication, Shenzhen University, Shenzhen 518060, China)

  • Ke-ke Shang

    (Computational Communication Collaboratory, Nanjing University, Nanjing 210023, China
    These authors contributed equally to this work.)

Abstract

In the real world, pathogens do not exist in isolation. The transmission of one pathogen may be affected by the presence of other pathogens, and certain pathogens generate multiple strains with different spreading features. Hence, the behavior of multi-pathogen transmission has attracted much attention in epidemiological research. In this paper, we use the pairwise approximation method to formulate two-pathogen models capturing cross-immunity, super-infection, and co-infection phenomena, in which each pathogen follows a susceptible-infected-susceptible (SIS) mechanism. For each model, we calculate the basic reproduction number and analyze the stability of equilibria, and discuss the differences from the mean-field approach. We demonstrate that simulations are in good agreement with the analytical results.

Suggested Citation

  • Shanshan Chen & Yijun Ran & Hebo Huang & Zhenzhen Wang & Ke-ke Shang, 2022. "Epidemic Dynamics of Two-Pathogen Spreading for Pairwise Models," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1906-:d:830487
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    References listed on IDEAS

    as
    1. Maliyoni, Milliward & Chirove, Faraimunashe & Gaff, Holly D. & Govinder, Keshlan S., 2019. "A stochastic epidemic model for the dynamics of two pathogens in a single tick population," Theoretical Population Biology, Elsevier, vol. 127(C), pages 75-90.
    2. M. De la Sen & R. Nistal & S. Alonso-Quesada & A. Ibeas, 2019. "Some Formal Results on Positivity, Stability, and Endemic Steady-State Attainability Based on Linear Algebraic Tools for a Class of Epidemic Models with Eventual Incommensurate Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-22, July.
    3. Wang, Haiying & Moore, Jack Murdoch & Small, Michael & Wang, Jun & Yang, Huijie & Gu, Changgui, 2022. "Epidemic dynamics on higher-dimensional small world networks," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    4. Eames, K.T.D., 2008. "Modelling disease spread through random and regular contacts in clustered populations," Theoretical Population Biology, Elsevier, vol. 73(1), pages 104-111.
    5. Gavin J. D. Smith & Dhanasekaran Vijaykrishna & Justin Bahl & Samantha J. Lycett & Michael Worobey & Oliver G. Pybus & Siu Kit Ma & Chung Lam Cheung & Jayna Raghwani & Samir Bhatt & J. S. Malik Peiris, 2009. "Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic," Nature, Nature, vol. 459(7250), pages 1122-1125, June.
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