Population dispersal and optimal control of an SEIR epidemic model

Author(s):  
T.K. Kar ◽  
Soovoojeet Jana ◽  
Manotosh Mandal
2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chernet Tuge Deressa ◽  
Gemechis File Duressa

AbstractWe consider a SEAIR epidemic model with Atangana–Baleanu fractional-order derivative. We approximate the solution of the model using the numerical scheme developed by Toufic and Atangana. The numerical simulation corresponding to several fractional orders shows that, as the fractional order reduces from 1, the spread of the endemic grows slower. Optimal control analysis and simulation show that the control strategy designed is operative in reducing the number of cases in different compartments. Moreover, simulating the optimal profile revealed that reducing the fractional-order from 1 leads to the need for quick starting of the application of the designed control strategy at the maximum possible level and maintaining it for the majority of the period of the pandemic.


2020 ◽  
Vol 25 (9) ◽  
pp. 3491-3521
Author(s):  
Hongyong Zhao ◽  
◽  
Peng Wu ◽  
Shigui Ruan ◽  

Cubo (Temuco) ◽  
2018 ◽  
Vol 20 (2) ◽  
pp. 53-66 ◽  
Author(s):  
Moussa Barro ◽  
Aboudramane Guiro ◽  
Dramane Ouedraogo

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Lijuan Chen ◽  
Shouying Huang ◽  
Fengde Chen ◽  
Mingjian Fu

AbstractIt is well known that the feedback mechanism or the individual’s intuitive response to the epidemic can have a vital effect on the disease’s spreading. In this paper, we investigate the bifurcation behavior and the optimal feedback mechanism for an SIS epidemic model on heterogeneous networks. Firstly, we present the bifurcation analysis when the basic reproduction number is equal to unity. The direction of bifurcation is also determined. Secondly, different from the constant coefficient in the existing literature, we incorporate a time-varying feedback mechanism coefficient. This is more reasonable since the initiative response of people is constantly changing during different process of disease prevalence. We analyze the optimal feedback mechanism for the SIS epidemic network model by applying the optimal control theory. The existence and uniqueness of the optimal control strategy are obtained. Finally, a numerical example is presented to verify the efficiency of the obtained results. How the topology of the network affects the optimal feedback mechanism is also discussed.


Sign in / Sign up

Export Citation Format

Share Document