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Investigation of SIS epidemics on dynamic network models with temporary link deactivation control schemes


  • Received: 02 March 2022 Revised: 06 April 2022 Accepted: 12 April 2022 Published: 19 April 2022
  • Mathematical modeling of epidemic diseases is increasingly being used to respond to emerging diseases. Although conditions modeled by SIS dynamics will eventually reach either a disease-free steady-state or an endemic steady state without interventions, it is desirable to eradicate the disease as quickly as possible by introducing a control scheme. Here, we investigate the control methods of epidemic models on dynamic networks with temporary link deactivation. A quick link deactivation mechanism can simulate a community effort to reduce the risk of infection by temporarily avoiding infected neighbors. Once infected individuals recover, the links between the susceptible and recovered are activated. Our study suggests that a control scheme that has been shown ineffective in controlling dynamic network models may yield effective responses for networks with certain types of link dynamics, such as the temporary link deactivation mechanisms. We observe that a faster and more effective eradication could be achieved by updating control schemes frequently.

    Citation: Jun Hyung Bae, Sang-Mook Lee. Investigation of SIS epidemics on dynamic network models with temporary link deactivation control schemes[J]. Mathematical Biosciences and Engineering, 2022, 19(6): 6317-6330. doi: 10.3934/mbe.2022295

    Related Papers:

  • Mathematical modeling of epidemic diseases is increasingly being used to respond to emerging diseases. Although conditions modeled by SIS dynamics will eventually reach either a disease-free steady-state or an endemic steady state without interventions, it is desirable to eradicate the disease as quickly as possible by introducing a control scheme. Here, we investigate the control methods of epidemic models on dynamic networks with temporary link deactivation. A quick link deactivation mechanism can simulate a community effort to reduce the risk of infection by temporarily avoiding infected neighbors. Once infected individuals recover, the links between the susceptible and recovered are activated. Our study suggests that a control scheme that has been shown ineffective in controlling dynamic network models may yield effective responses for networks with certain types of link dynamics, such as the temporary link deactivation mechanisms. We observe that a faster and more effective eradication could be achieved by updating control schemes frequently.



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