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Dynamics of fractional order delay model of coronavirus disease

Lei Zhang, Mati ur Rahman, Shabir Ahmad, Muhammad Bilal Riaz, Fahd Jarad

2021AIMS Mathematics31 citationsDOIOpen Access PDF

Abstract

<abstract><p>The majority of infectious illnesses, such as HIV/AIDS, Hepatitis, and coronavirus (2019-nCov), are extremely dangerous. Due to the trial version of the vaccine and different forms of 2019-nCov like beta, gamma, delta throughout the world, still, there is no control on the transmission of coronavirus. Delay factors such as social distance, quarantine, immigration limitations, holiday extensions, hospitalizations, and isolation are being utilized as essential strategies to manage the outbreak of 2019-nCov. The effect of time delay on coronavirus disease transmission is explored using a non-linear fractional order in the Caputo sense in this paper. The existence theory of the model is investigated to ensure that it has at least one and unique solution. The Ulam-Hyres (UH) stability of the considered model is demonstrated to illustrate that the stated model's solution is stable. To determine the approximate solution of the suggested model, an efficient and reliable numerical approach (Adams-Bashforth) is utilized. Simulations are used to visualize the numerical data in order to understand the behavior of the different classes of the investigated model. The effects of time delay on dynamics of coronavirus transmission are shown through numerical simulations via MATLAB-17.</p></abstract>

Topics & Concepts

CoronavirusTransmission (telecommunications)Coronavirus disease 2019 (COVID-19)OutbreakMATLABStability (learning theory)Isolation (microbiology)Epidemic modelSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MathematicsOrder (exchange)PandemicComputer scienceApplied mathematicsVirologyDiseaseInfectious disease (medical specialty)MedicineBiologyEconomicsTelecommunicationsEnvironmental healthPopulationBioinformaticsPathologyFinanceOperating systemMachine learningFractional Differential Equations SolutionsCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models
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