Modelization of Covid-19 pandemic spreading: A machine learning forecasting with relaxation scenarios of countermeasures.

Journal: Journal of infection and public health

Published Date: Apr 1, 2021

Abstract

BACKGROUND & OBJECTIVE: Mathematical modeling is the most scientific technique to understand the evolution of natural phenomena, including the spread of infectious diseases. Therefore, these modeling tools have been widely used in epidemiology for predicting risks and decision-making processes. The purpose of this paper is to provide an effective mathematical model for predicting the spread of Covid-19 pandemic.

Authors

Moulay A Lmater

Mobility and Modeling Laboratory, Faculty of Sciences and Techniques, Hassan 1(st) University, 26 100 Settat, Morocco.
Mohamed Eddabbah

ISPITS - Higher Institute of Nursing and Health Techniques, Ministry of Health, 40 000 Marrakech, Morocco.
Tariq Elmoussaoui

INPT - National Institute of Posts and Telecommunications, 10100 Rabat, Morocco.
Samia Boussaa

ISPITS - Higher Institute of Nursing and Health Techniques, Ministry of Health, 40 000 Marrakech, Morocco. Electronic address: samiaboussaa@gmail.com.

Keywords

Belgium COVID-19 Humans Machine Learning Models, Theoretical Morocco Netherlands Pandemics Russia

External Resources

View on PubMed Access via DOI PubMed (33743367)

Modelization of Covid-19 pandemic spreading: A machine learning forecasting with relaxation scenarios of countermeasures.

Abstract

Authors

Keywords

External Resources

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