Optimal control strategies for the reliable and competitive mathematical
analysis of Covid-19 pandemic model
Abstract
To understand dynamics of the COVID-19 disease realistically, a new
SEIAPHR model has been proposed in this article where the infectious
individuals have been categorized as symptomatic, asymptomatic and
super-spreaders. The model has been investigated for existence of a
unique solution. To measure the contagiousness of COVID-19, reproduction
number R0 is also computed using next generation matrix
method. It is shown that model is locally stable at disease free
equilibrium point when R0 <1 and unstable for
R0 >1. The model has been analyzed for
global stability at both of the disease free and endemic equilibrium
points. Sensitivity analysis is also included to examine the effect of
parameters of the model on reproduction number R0.
Couple of optimal control problems have been designed to study the
effect of control strategies for disease control and eradication from
the society. Numerical results show that the adopted control approaches
are much effective in reducing new infections.