Modeling the spread of COVID-19 pandemic in Morocco

TL;DR

This paper introduces a delayed mathematical model to predict COVID-19 spread in Morocco, analyzing intervention effectiveness and aiding policy development.

Contribution

It presents a novel delayed model for COVID-19 in Morocco, including parameter estimation, sensitivity analysis, and simulation of intervention impacts.

Findings

Model accurately predicts COVID-19 trends in Morocco.

Preventive measures significantly reduce infection rates.

Simulations support policy decisions for controlling the pandemic.

Abstract

Nowadays, coronavirus disease 2019 (COVID-19) poses a great threat to public health and economy worldwide. Unfortunately, there is yet no effective drug for this disease. For this, several countries have adopted multiple preventive interventions to avoid the spread of COVID-19. Here, we propose a delayed mathematical model to predict the epidemiological trend of COVID-19 in Morocco. Parameter estimation and sensitivity analysis of the proposed model are rigorously studied. Moreover, numerical simulations are presented in order to test the effectiveness of the preventive measures and strategies that were imposed by the Moroccan authorities and also help policy makers and public health administration to develop such strategies.