Author: Srivastav, Akhil Kumar; Ghosh, Mini; Li, Xueâ€Zhi; Cai, Liming
                    Title: Modeling and optimal control analysis of COVIDâ€19: Case studies from Italy and Spain  Cord-id: l6rqafwu  Document date: 2021_3_24
                    ID: l6rqafwu
                    
                    Snippet: Coronavirus disease 2019 (COVIDâ€19) is a viral disease which is declared as a pandemic by WHO. This disease is posing a global threat, and almost every country in the world is now affected by this disease. Currently, there is no vaccine for this disease, and because of this, containing COVIDâ€19 is not an easy task. It is noticed that elderly people got severely affected by this disease specially in Europe. In the present paper, we propose and analyze a mathematical model for COVIDâ€19 virus
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: Coronavirus disease 2019 (COVIDâ€19) is a viral disease which is declared as a pandemic by WHO. This disease is posing a global threat, and almost every country in the world is now affected by this disease. Currently, there is no vaccine for this disease, and because of this, containing COVIDâ€19 is not an easy task. It is noticed that elderly people got severely affected by this disease specially in Europe. In the present paper, we propose and analyze a mathematical model for COVIDâ€19 virus transmission by dividing whole population in old and young groups. We find diseaseâ€free equilibrium and the basic reproduction number (R (0)). We estimate the parameter corresponding to rate of transmission and rate of detection of COVIDâ€19 using real data from Italy and Spain by least square method. We also perform sensitivity analysis to identify the key parameters which influence the basic reproduction number and hence regulate the transmission dynamics of COVIDâ€19. Finally, we extend our proposed model to optimal control problem to explore the best costâ€effective and timeâ€dependent control strategies that can reduce the number of infectives in a specified interval of time.
 
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