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Epidemic spreading on metapopulation networks considering indirect contact

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  • Wang, Juquan
  • Han, Dun

Abstract

Since pathogens can stay on the carrier for a period of time, indirect transmission plays a nonnegligible role in the spread of diseases apart from direct human-to-human contact. We hereby propose an epidemic model on the metapopulation network, combining direct contact transmission with indirect contact transmission. A detailed theoretical analysis and simulation are employed to discuss and verify the epidemic threshold. Results show that the existence of indirect contact can promote the spread of diseases significantly. In addition, the final density of infection increases with the increase of the indirect contact transmission rate or the number of vectors, and with the decrease of the recovery rate of vectors. In the case of a heterogeneous population distribution, the epidemic threshold increases with the mobility rate which differs from the case of the homogeneous population distribution. Our framework presents a new viewpoint and theoretical reference for the study of indirect contact propagation.

Suggested Citation

  • Wang, Juquan & Han, Dun, 2023. "Epidemic spreading on metapopulation networks considering indirect contact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    • Handle: RePEc:eee:phsmap:v:619:y:2023:i:c:s0378437123002777
    DOI: 10.1016/j.physa.2023.128722
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    References listed on IDEAS

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    1. Dun Han & Qi Shao & Dandan Li, 2020. "Exploring the Epidemic Spreading in a Multilayer Metapopulation Network by considering Individuals’ Periodic Travelling," Complexity, Hindawi, vol. 2020, pages 1-9, April.
    2. Torsten Thalheim & Tyll Krüger & Jörg Galle, 2022. "Indirect Virus Transmission via Fomites Can Counteract Lock-Down Effectiveness," IJERPH, MDPI, vol. 19(21), pages 1-14, October.
    3. Zhu, Xuzhen & Liu, Yuxin & Wang, Shengfeng & Wang, Ruijie & Chen, Xiaolong & Wang, Wei, 2021. "Allocating resources for epidemic spreading on metapopulation networks," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    4. Kezban Yagci Sokat & Stefan Edlund & Kenneth Clarkson & James Kaufman, 2019. "Comparing Direct and Indirect Transmission in a Simple Model of Veterinary Disease," Mathematics, MDPI, vol. 7(11), pages 1-14, November.
    5. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    Full references (including those not matched with items on IDEAS)

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