Spread of COVID-19 in morocco discrete mathematical modeling: optimal control strategies and cost-effectiveness analysis

Driss Kada, Abderrahim Labzai, Omar Balatif, Mostafa Rachik, El Houssine Labriji

Abstract


In this article, we study the transmission of (COVID-19) in the human population. We use the compartments model to describe the spread of this infectious disease. We divide the infected people with Covid-19 disease into three groups because the patients go through different stages, which are: infection, symptoms and serious or critical complications. We propose a discrete mathematical model with control strategies using three variables of controls u, v and w that represent respectively: Urging people to wash their hands with water and soap, cleaning and disinfecting surfaces frequently, urging people to use masks to cover the sensitive body parts and the treatment of patients infected with (COVID-19) by taking them to hospitals and quarantine sites. Pontryagin’s Maximum Principle, in discrete time, is used to characterize the optimal controls and the optimality system is solved by an iterative method. Finally, Numerical simulations are presented with and without controls. Using cost-effectiveness analysis, we will show that the control that represents treatment of patients infected with (COVID-19) by taking them to hospitals and quarantine sites is the most cost-effective strategy to control the disease.

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Published: 2020-08-17

How to Cite this Article:

Driss Kada, Abderrahim Labzai, Omar Balatif, Mostafa Rachik, El Houssine Labriji, Spread of COVID-19 in morocco discrete mathematical modeling: optimal control strategies and cost-effectiveness analysis, J. Math. Comput. Sci., 10 (2020), 2070-2093

Copyright © 2020 Driss Kada, Abderrahim Labzai, Omar Balatif, Mostafa Rachik, El Houssine Labriji. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 

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