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Optimal control and sensitivity analysis for transmission dynamics of Coronavirus

Chernet Tuge Deressa, Yesuf Obsie Mussa, Gemechis File Duressa

2020Results in Physics49 citationsDOIOpen Access PDF

Abstract

Analysis of mathematical models designed for COVID-19 results in several important outputs that may help stakeholders to answer disease control policy questions. A mathematical model for COVID-19 is developed and equilibrium points are shown to be locally and globally stable. Sensitivity analysis of the basic reproductive number (R0) showed that the rate of transmission from asymptomatically infected cases to susceptible cases is the most sensitive parameter. Numerical simulation indicated that a 10% reduction of R0 by reducing the most sensitive parameter results in a 24% reduction of the size of exposed cases. Optimal control analysis revealed that the optimal practice of combining all three (public health education, personal protective measure, and treating COVID-19 patients) intervention strategies or combination of any two of them leads to the required mitigation of transmission of the pandemic.

Topics & Concepts

Sensitivity (control systems)Coronavirus disease 2019 (COVID-19)Basic reproduction numberTransmission (telecommunications)Reduction (mathematics)Transmission ratePandemicControl (management)Computer scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Optimal controlMathematical optimizationControl theory (sociology)MathematicsRisk analysis (engineering)MedicineDiseaseInfectious disease (medical specialty)Environmental healthEngineeringArtificial intelligencePathologyTelecommunicationsPopulationGeometryElectronic engineeringCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsCosmology and Gravitation Theories
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