Impact studies of nationwide measures COVID-19 anti-pandemic: compartmental model and machine learning

Mouhamadou A.M.T. Baldé, Coura Baldé, Babacar M. Ndiaye

Abstract


In this paper, we deal with the study of the impact of nationwide measures COVID-19 anti-pandemic. We drive two processes to analyze COVID-19 data considering measures. We associate level of nationwide measure with value of parameters related to the contact rate of the model. Then a parametric solve, with respect to those parameters of measures, shows different possibilities of the evolution of the pandemic. Two machine learning tools are used to forecast the evolution of the pandemic. Finally, we show comparison between deterministic and two machine learning tools.

Full Text: PDF

Published: 2020-10-06

How to Cite this Article:

Mouhamadou A.M.T. Baldé, Coura Baldé, Babacar M. Ndiaye, Impact studies of nationwide measures COVID-19 anti-pandemic: compartmental model and machine learning, Commun. Math. Biol. Neurosci., 2020 (2020), Article ID 68

Copyright © 2020 Mouhamadou A.M.T. Baldé, Coura Baldé, Babacar M. Ndiaye. 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.

Commun. Math. Biol. Neurosci.

ISSN 2052-2541

Editorial Office: office@scik.org

 

Copyright ©2020 CMBN