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Comparison of two mean-field based theoretical analysis methods for SIS model

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  • Zhang, Jiaquan
  • Lu, Dan
  • Yang, Shunkun

Abstract

Epidemic spreading has been intensively studied in SIS epidemic model. Although the mean-field theory of SIS model has been widely used in the research, there is a lack of comparative results between different theoretical calculations, and the differences between them should be systematically explained. In this paper, we have compared different theoretical solutions for mean-field theory and explained the underlying reason. We first describe the differences between different equations for mean-field theory in different networks. The results show that the difference between mean-field reaction equations is due to the different probability consideration for the infection process. This finding will help us to design better theoretical solutions for epidemic models.

Suggested Citation

  • Zhang, Jiaquan & Lu, Dan & Yang, Shunkun, 2017. "Comparison of two mean-field based theoretical analysis methods for SIS model," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 209-214.
    • Handle: RePEc:eee:chsofr:v:104:y:2017:i:c:p:209-214
    DOI: 10.1016/j.chaos.2017.08.001
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    References listed on IDEAS

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    1. Wu, Qingchu & Fu, Xinchu, 2016. "Immunization and epidemic threshold of an SIS model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 576-581.
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    3. D. Q. Li & M. H. Li & J. S. Wu & Z. R. Di & Y. Fan, 2007. "Enhancing synchronizability by weight randomization on regular networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(4), pages 423-428, June.
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    1. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2022. "Multi criteria analysis of alternative energy technologies based on their predicted impact on community sustainable livelihoods capitals: A case of Uganda," Renewable Energy, Elsevier, vol. 182(C), pages 1103-1125.
    2. Wu, Qingchu & Zhou, Rong & Hadzibeganovic, Tarik, 2019. "Conditional quenched mean-field approach for recurrent-state epidemic dynamics in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 71-79.

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