Abstract
Machine learning prediction algorithms are considered powerful tools that could provide accurate insights about the spread and mortality of the novel Covid-19 disease. In this paper, a comparative study is introduced to evaluate the use of several parametric and non-parametric machine learning methods to model the total number of Covid-19 cases (TC) and total deaths (TD). A number of input features from the available Covid-19 time sequence are investigated to select the most significant model predictors. The impact of using the number of PCR tests as a model predictor is uniquely investigated in this study. The parametric regression including the Linear, Log, Polynomial, Generative Additive Regression, and Spline Regression and the non-parametric K-Nearest Neighborhood (KNN), Support Vector machine (SVM) and the Decision Tree (DT) have been utilized for building the models. The findings show that, for the used dataset, the linear regression is more accurate than the non-parametric models in predicting TC & TD. It is also found that including the total number of tests in the mortality model significantly increases its prediction accuracy.
Highlights
IntroductionCovid-19, broke out at the late of December 2019, in Wuhan, China, the virus has been spread all over the world by the Spring of 2020
Once the coronavirus pandemic, Covid-19, broke out at the late of December 2019, in Wuhan, China, the virus has been spread all over the world by the Spring of 2020
We propose a comparative study to evaluate the use of several parametric & non-parametric machine learning regression methods to model the two main folds of Covid-19 spread: the total number of confirmed cases and the total number of deaths
Summary
Covid-19, broke out at the late of December 2019, in Wuhan, China, the virus has been spread all over the world by the Spring of 2020. The coronavirus pandemic has so far followed a wave pattern, with increases in new cases followed by reductions [1]. SARS-CoV2, the coronavirus that causes Covid-19, has mutated since the beginning of the pandemic, resulting in variations of the disease symptoms [2]. The delta variation is one of these mutations. Some countries are suffering from the fourth wave of the pandemic with the severest mutated version of the virus, delta variant. The unpredictable rapid spread of the pandemic all over the world has caused unprecedented global lockdowns and overwhelmed the healthcare systems.
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