Open Journal of Mathematical Sciences

Vol. 4 (2020), Issue 1, pp. 273 – 279
ISSN: 2523-0212 (Online) 2616-4906 (Print)
DOI: 10.30538/oms2020.0118

Investigation on the temporal evolution of the covid’19 pandemic: prediction for Togo

Komi Agbokou\(^1\), Kossi Gneyou, Kokou Tcharie
Laboratoire LAMMA Laboratory, Department of Mathematics, Faculty of Sciences, University of Lomé, Togo.; (K.A & K.G & K.T)
\(^{1}\)Corresponding Author: ffomestein@gmail.com

Copyright © 2020 Komi Agbokou, Kossi Gneyou, Kokou Tcharie. 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.

Received: June 20, 2020 – Accepted: August 17, 2020 – Published: August 27, 2020

Abstract

A state of health emergency has been decreed by the Togolese government since April 01 for a period of 3 months, with the introduction of a curfew which ended on June 9, following the first case of contamination of the corona Sars- Cov-2 in Togo, case registered on March 06, 2020. This first wave of contamination started from March 19. The data observed in Togo are cases tested positive and which are cured using a protocol based on the combination of hydroxychloroquine and azithromycin. This manuscript offers a forecast on the number of daily infections and its peak (or maximum), then the cumulative numbers of those infected with the covid’19 pandemic. The forecasts are based on evolution models which are well known in the literature, which consist in evaluating the evolution of the cumulative numbers of infected and a Gaussian model representing an estimate of the number of daily infections for this first wave of contamination. over a period of 8 months from the sample of observed data.

Keywords:

Nonlinear ODE, AIC criterion, maximum likelihood, parametric estimator.