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Edge-based SEIR dynamics with recovery rate in latent period on complex networks

Author

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  • Rong Zhou

    (College of Mathematics and Information Science, Jiangxi Normal University, Nanchang, Jiangxi 330022, P. R. China)

  • Qingchu Wu

    (College of Mathematics and Information Science, Jiangxi Normal University, Nanchang, Jiangxi 330022, P. R. China)

Abstract

Disease and information spreading on social and information networks have often been described by ordinary differential equations. A recent research by the authors [Y. Wang et al., Commun. Nonlinear Sci. Numer. Simulat. 45, 35 (2017).] presented an analysis of susceptible-exposed-infected-recovered (SEIR) model with and without infectious force in latent period. We present a full analysis in the more general scenario where the exposed nodes can get vaccinated or recovered. The basic reproduction number and the final epidemic size are theoretically derived. Compared to the standard SEIR model without recovery rate in latent period, our results reveal that both the recovery rate in latent period and the length of latent period can increase the epidemic threshold and inhibit the epidemic outbreak. In addition, the model predictions agree well with the continuous-time stochastic simulations in Erdős–Rényi random graphs and scale-free configuration networks.

Suggested Citation

  • Rong Zhou & Qingchu Wu, 2020. "Edge-based SEIR dynamics with recovery rate in latent period on complex networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(04), pages 1-13, February.
    • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:04:n:s0129183120500576
    DOI: 10.1142/S0129183120500576
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