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Predicting the dynamical behavior of COVID-19 epidemic and the effect of control strategies

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  • Shakhany, Mohammad Qaleh
  • Salimifard, Khodakaram

Abstract

This paper uses transformed subsystem of ordinary differential equation seirsmodel, with vital dynamics of birth and death rates, and temporary immunity (of infectious individuals or vaccinated susceptible) to evaluate the disease-free DFEX¯DFE,and endemic EEX¯EE equilibrium points, using the Jacobian matrix eigenvalues λi of both disease-free equilibrium X¯DFE, and endemic equilibrium X¯EE for COVID-19 infectious disease to show S, E, I, and R ratios to the population in time-series. In order to obtain the disease-free equilibrium point, globally asymptotically stable (R0≤1), the effect of control strategies has been added to the model (in order to decrease transmission rateβ, and reinforce susceptible to recovered flow), to determine how much they are effective, in a mass immunization program. The effect of transmission rates β (from S to E) and α (from R to S) varies, and when vaccination effectρ, is added to the model, disease-free equilibrium X¯DFE is globally asymptotically stable, and the endemic equilibrium pointX¯EE, is locally unstable. The initial conditions for the decrease in transmission rates of β and α, reached the corresponding disease-free equilibrium X¯DFE locally unstable, and globally asymptotically stable for endemic equilibriumX¯EE. The initial conditions for the decrease in transmission ratesβandα, and increase in ρ, reached the corresponding disease-free equilibrium X¯DFE globally asymptotically stable, and locally unstable in endemic equilibriumX¯EE.

Suggested Citation

  • Shakhany, Mohammad Qaleh & Salimifard, Khodakaram, 2021. "Predicting the dynamical behavior of COVID-19 epidemic and the effect of control strategies," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
  • Handle: RePEc:eee:chsofr:v:146:y:2021:i:c:s0960077921001752
    DOI: 10.1016/j.chaos.2021.110823
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    Cited by:

    1. Zuo, Chao & Ling, Yuting & Zhu, Fenping & Ma, Xinyu & Xiang, Guochun, 2023. "Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis," Applied Mathematics and Computation, Elsevier, vol. 447(C).
    2. Prem Kumar, R. & Santra, P.K. & Mahapatra, G.S., 2023. "Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 741-766.
    3. Gandzha, I.S. & Kliushnichenko, O.V. & Lukyanets, S.P., 2021. "Modeling and controlling the spread of epidemic with various social and economic scenarios," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).

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