Eur. Phys. J. Plus (2020) 135: 839
https://doi.org/10.1140/epjp/s13360-020-00855-1

Regular Article

Optimal control analysis of vector-host model with saturated treatment

¹ Department of Mathematics, University of Peshawar, 25000, Peshawar, Khyber Pakhtunkhwa, Pakistan
² Faculty of Informatics and Computing, Universiti Sultan Zainul Abidin, Gang Badak Campus, Kuala Terengganu, Malaysia
³ Department of Mathematics, University of Swabi, Khyber Pakhtunkhwa, Pakistan
⁴ Informetrics Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
⁵ Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam

^e muhammad.altaf.khan@tdtu.edu.vn

Received: 21 August 2020
Accepted: 9 October 2020
Published online: 16 October 2020

Abstract

Vector-host infectious diseases remain a challenging issue and cause millions of deaths each year globally. In such outbreaks, many countries especially developing or underdevelopment faces a situation where the number of infected individuals is getting larger and the medical facilities are limited. In this paper, we construct an epidemic model to explore the transmission dynamics of vector-borne diseases with nonlinear saturated incidence rate and saturated treatment function. This type of incidence rate, as well as the saturated treatment function, is also known as the Holling type II form and describes the effect of delayed treatment. Initially, we formulate a mathematical model and then present the basic analysis of the model including the positivity and boundedness of the solution. The threshold quantity is presented and the stability analysis of the system is carried out for the model equilibria. The global stability results are shown using the Lyapunov function of Goh–Voltera type. The existence of backward bifurcation is discussed using the central manifold theory. Further, the global sensitivity analysis of the model is carried out using the Latin Hypercube sampling and the partial rank correlation coefficient techniques. Moreover, an optimal control problem is formulated and the necessary optimality conditions are investigated in order to eradicate the disease in a community. Four strategies are presented by choosing different set of controls combination for the disease minimization. Finally, the numerical simulations of each strategy are depicted to demonstrate the importance of suggesting control interventions on the disease dynamics and eradication.