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10.1007/s11071-020-05774-5

http://scihub22266oqcxt.onion/10.1007/s11071-020-05774-5
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C7315126!7315126!32836807
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suck abstract from ncbi


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pmid32836807      Nonlinear+Dyn 2020 ; 101 (3): 2013-26
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  • Dynamics and control of COVID-19 pandemic with nonlinear incidence rates #MMPMID32836807
  • Rohith G; Devika KB
  • Nonlinear Dyn 2020[]; 101 (3): 2013-26 PMID32836807show ga
  • World Health Organization (WHO) has declared COVID-19 a pandemic on March 11, 2020. As of May 23, 2020, according to WHO, there are 213 countries, areas or territories with COVID-19 positive cases. To effectively address this situation, it is imperative to have a clear understanding of the COVID-19 transmission dynamics and to concoct efficient control measures to mitigate/contain the spread. In this work, the COVID-19 dynamics is modelled using susceptible?exposed?infectious?removed model with a nonlinear incidence rate. In order to control the transmission, the coefficient of nonlinear incidence function is adopted as the Governmental control input. To adequately understand the COVID-19 dynamics, bifurcation analysis is performed and the effect of varying reproduction number on the COVID-19 transmission is studied. The inadequacy of an open-loop approach in controlling the disease spread is validated via numerical simulations and a robust closed-loop control methodology using sliding mode control is also presented. The proposed SMC strategy could bring the basic reproduction number closer to 1 from an initial value of 2.5, thus limiting the exposed and infected individuals to a controllable threshold value. The model and the proposed control strategy are then compared with real-time data in order to verify its efficacy.
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