Application of fractional optimal control theory for the mitigating of novel coronavirus in Algeria

In this paper, we investigate the dynamics of novel coronavirus infection (COVID-19) using a fractional mathematical model in Caputo sense. Based on the spread of COVID-19 virus observed in Algeria, we formulate the model by dividing the infected population into two sub-classes namely the reported a...

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Veröffentlicht in:Results in physics 2022-08, Vol.39, p.105651-105651, Article 105651
Hauptverfasser: El hadj Moussa, Yacine, Boudaoui, Ahmed, Ullah, Saif, Muzammil, Khursheed, Riaz, Muhammad Bilal
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Sprache:eng
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Zusammenfassung:In this paper, we investigate the dynamics of novel coronavirus infection (COVID-19) using a fractional mathematical model in Caputo sense. Based on the spread of COVID-19 virus observed in Algeria, we formulate the model by dividing the infected population into two sub-classes namely the reported and unreported infective individuals. The existence and uniqueness of the model solution are given by using the well-known Picard–Lindelöf approach. The basic reproduction number R0 is obtained and its value is estimated from the actual cases reported in Algeria. The model equilibriums and their stability analysis are analyzed. The impact of various constant control parameters is depicted for integer and fractional values of α. Further, we perform the sensitivity analysis showing the most sensitive parameters of the model versus R0 to predict the incidence of the infection in the population. Further, based on the sensitivity analysis, the Caputo model with constant controls is extended to time-dependent variable controls in order obtain a fractional optimal control problem. The associated four time-dependent control variables are considered for the prevention, treatment, testing and vaccination. The fractional optimality condition for the control COVID-19 transmission model is presented. The existence of the Caputo optimal control model is studied and necessary condition for optimality in the Caputo case is derived from Pontryagin’s Maximum Principle. Finally, the effectiveness of the proposed control strategies are demonstrated through numerical simulations. The graphical results revealed that the implantation of time-dependent controls significantly reduces the number of infective cases and are useful in mitigating the infection. •A fractional COVID-19 model with detected and undetected infected cases is presented.•Estimation and sensitivity analysis of the parameters are performed.•A fractional optimal control problem based on optimal control theory is presented.•Simulation of the constant and time dependent control fractional problems are depicted.
ISSN:2211-3797
2211-3797
DOI:10.1016/j.rinp.2022.105651