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Unveiling epidemic spreading and control on networks with self-recovery and social support

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  • Wu, Qingchu
  • Wang, Lin

Abstract

Given the inherent complexities of individual recovery, self-recovery stems from the individual themselves, whereas social support originates from their susceptible surroundings. Utilizing the quenched mean-field method, two distinct analytical models are developed. The condition for an epidemic outbreak is established through a comprehensive analysis of stability and bifurcation. Continuous-time simulations confirm the predictive capability of these models in terms of spreading behavior. Our findings indicate that both self-recovery and social support can decrease the likelihood of an epidemic outbreak. Further simulations imply that self-recovery can eradicate the explosive transition in scale-free networks, but only dampen its magnitude in random regular networks. These insights could have profound implications for governmental strategies in increasing its publicity efforts for epidemic control.

Suggested Citation

  • Wu, Qingchu & Wang, Lin, 2025. "Unveiling epidemic spreading and control on networks with self-recovery and social support," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 678(C).
    • Handle: RePEc:eee:phsmap:v:678:y:2025:i:c:s037843712500620x
    DOI: 10.1016/j.physa.2025.130968
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    References listed on IDEAS

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