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Effect of infection age on an SIR epidemic model with demography on complex networks

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  • Yang, Junyuan
  • Chen, Yuming

Abstract

For the long term population behavior, demography is a very important factor impacting the disease spread. Infection age also helps us better understand the process of the disease transmission. In this paper, we incorporate these two factors in an SIR epidemic model on complex networks. Through mathematical analysis, the basic reproduction number R0 is shown to be a sharp threshold to determine whether or not the disease spreads. Precisely, if R0 is less than 1 then the disease-free equilibrium is globally asymptotically stable while if R0 is larger than 1 then the endemic equilibrium is globally asymptotically stable. Some simulations are carried out to illustrate the theoretical results.

Suggested Citation

  • Yang, Junyuan & Chen, Yuming, 2017. "Effect of infection age on an SIR epidemic model with demography on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 527-541.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:527-541
    DOI: 10.1016/j.physa.2017.03.006
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    Cited by:

    1. Fu, Minglei & Yang, Hongbo & Feng, Jun & Guo, Wen & Le, Zichun & Lande, Dmytro & Manko, Dmytro, 2018. "Preferential information dynamics model for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 993-1005.

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