COVID-19 Propagation Mathematical Modeling: The Case of Senegal

Abstract

The outburst of the CoVid-19 pandemic has raised several questions leading to a complex system in terms of modeling. Indeed, the modeling of the epidemic, at the level of a country, needs considering each of the different sources of contamination as well as the public health authorities' strategy, in a specific way. With this in mind, in the present paper, we develop a mathematical model of the CoVid-19 epidemic in Senegal. In the model, the population is subdivided into five compartments: susceptible, infected but asymptomatic, symptomatic, quarantined, and recovered immune people. In addition, due to its important impact on the propagation of the disease, we add one more variable: the number of infected objects. %\vspace{1mm} Therefore, the model corresponds to a system of six non-linear ordinary differential equations we submit to an analytical study to prove the relevancy of the model, simulate the evolution of the epidemic, and retrieve epidemiological parameters, namely the infection rate and the basic reproduction number, ${\cal R}_0$. Based on the senegalese territory CoVid-19 data, we simulate various scenarios as for the evolution of the epidemic in the country, in order to predict the peak and its magnitude with regard to the application of barrier measures. We also explore the option of collective immunity with special protection for vulnerable people. In doing so, non-available parameters are identified using some mathematical identification technics.

Analysis of COVID-19 evolution in Senegal: impact of health care capacity

“…We refer for examples to [5,7,8,14,21] and the references therein. Our work complements several studies that have been carried out on the spread of Sars-CoV-2 in Senegal [2,3,4,6,15,16,17,18]. It should be noted that the aforementioned studies did not address the impact of saturation on patients care in Senegal.…”

“…It should be noted that the aforementioned studies did not address the impact of saturation on patients care in Senegal. However, some studies on the prediction of the number of new cases for Senegal have already been carried out using machine learning [2,3,15,16] and on the impact of contaminated objects using compartmental models [6]. The paper is organized as follows.…”

Modeling Covid-19 Cases in West African Countries: A Comparative Analysis of Quartic Curve Estimation Models and Estimators

“…About related work done on COVID-19, a mathematical model with five compartments was developed to simulate the evolution of the pandemic, retrieve the infection rate and necessary production number [118]. Results of Senegal's response to COVID-19 through a state of emergency and curfew were also reviewed [119].…”