Evaluation and Prediction of Covid-19 Disease Spread across Sixteen West Africa Countries Using a Machine Learning Approach
Michael Segun Olajide
Department of Computer Science, Adeyemi College of Education, Ondo, Nigeria
Corresponding Author: 1olajidems@aceondo.edu.ng
Adekola Alex Ajayi
Department of Computer Science, Adeyemi College of Education, Ondo, Nigeria
Corresponding Author: ajayiaa@aceondo.edu.ng
Oladoyin Anthony Abiodun
Department of Computer Science, Adeyemi College of Education, Ondo, Nigeria
Corresponding Author: o.a.abiodun@lancaster.ac.uk
Oluwagboyega Peter Afolabi
Department of Computer Science, Adeyemi College of Education, Ondo, Nigeria
Corresponding Author:afolabiop@aceondo.edu.ng
Abstract :
The covid-19 pandemic disease created a great scare and massive economic, social, political, and international challenges. Many lives were lost, and economic crisis coupled with crippling industrial activities. This work aims to assess the tragedy, take into account the depth of its spread, and make intelligent guesses and predictions that will help all parties take appropriate steps to stop the disease. Using the Covid-19 time series dataset, an analysis was conducted to reveal the confirmed, active, recovery, and death cases of Covid-19 cases in the 16 West African countries. Using three machine learning algorithms: Polynomial Regression (PR), Support Vector Machine (SVM), and Neural Network (NN) to carry out prediction, the polynomial regression model gave the best result when considering the generated results among the three techniques employed for the study.
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