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10.1080/17513758.2020.1788182

http://scihub22266oqcxt.onion/10.1080/17513758.2020.1788182
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32696723!ä!32696723

suck abstract from ncbi


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pmid32696723      J+Biol+Dyn 2020 ; 14 (1): 590-607
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  • Optimal control strategies for the transmission risk of COVID-19 #MMPMID32696723
  • Lemecha Obsu L; Feyissa Balcha S
  • J Biol Dyn 2020[Dec]; 14 (1): 590-607 PMID32696723show ga
  • In this paper, we apply optimal control theory to a novel coronavirus (COVID-19) transmission model given by a system of non-linear ordinary differential equations. Optimal control strategies are obtained by minimizing the number of exposed and infected population considering the cost of implementation. The existence of optimal controls and characterization is established using Pontryagin's Maximum Principle. An expression for the basic reproduction number is derived in terms of control variables. Then the sensitivity of basic reproduction number with respect to model parameters is also analysed. Numerical simulation results demonstrated good agreement with our analytical results. Finally, the findings of this study shows that comprehensive impacts of prevention, intensive medical care and surface disinfection strategies outperform in reducing the disease epidemic with optimum implementation cost.
  • |*Betacoronavirus[MESH]
  • |*Models, Biological[MESH]
  • |Basic Reproduction Number/statistics & numerical data[MESH]
  • |COVID-19[MESH]
  • |Computer Simulation[MESH]
  • |Coronavirus Infections/epidemiology/*prevention & control/*transmission[MESH]
  • |Epidemics/prevention & control/statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Infection Control[MESH]
  • |Mathematical Concepts[MESH]
  • |Nonlinear Dynamics[MESH]
  • |Pandemics/*prevention & control[MESH]
  • |Pneumonia, Viral/epidemiology/*prevention & control/*transmission[MESH]
  • |Risk Factors[MESH]
  • |SARS-CoV-2[MESH]


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