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Mathematical modeling and optimal control of the COVID-19 dynamics

Zhonghua Shen, Yu‐Ming Chu, Muhammad Altaf Khan, Shabbir Muhammad, Omar A. Al‐Hartomy, M. Higazy

2021Results in Physics146 citationsDOIOpen Access PDF

Abstract

We are considering a new COVID-19 model with an optimal control analysis when vaccination is present. Firstly, we formulate the vaccine-free model and present the associated mathematical results involved. Stability results for R0<1 are shown. In addition, we frame the model with the vaccination class. We look at the mathematical results with the details of the vaccine model. Additionally, we are considering setting controls to minimize infection spread and control. We consider four different controls, such as prevention, vaccination control, rapid screening of people in the exposed category, and people who are identified as infected without screening. Using the suggested controls, we develop an optimal control model and derive mathematical results from it. In addition, the mathematical model with control and without control is resolved by the forward–backward Runge–Kutta method and presents the results graphically. The results obtained through optimal control suggest that controls can be useful for minimizing infected individuals and improving population health.

Topics & Concepts

Optimal controlVaccinationMathematical modelControl (management)Frame (networking)Computer sciencePopulationCoronavirus disease 2019 (COVID-19)Stability (learning theory)Mathematical optimizationControl theory (sociology)MathematicsMedicineVirologyArtificial intelligenceStatisticsEnvironmental healthMachine learningInfectious disease (medical specialty)PathologyDiseaseTelecommunicationsCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsSARS-CoV-2 and COVID-19 Research
Mathematical modeling and optimal control of the COVID-19 dynamics | Litcius