COVID-19 Risk Factors, Economic Factors, and Epidemiological Factors nexus on Economic Impact: Machine Learning and Structural Equation Modelling Approaches

David Opeoluwa Oyewola; Emmanuel Gbenga  Dada; Juliana Ngozi Ndunagu; Terrang  Abubakar Umar; Akinwunmi S.A

doi:10.46481/jnsps.2021.173

Authors

David Opeoluwa Oyewola
[email protected]
Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria
Emmanuel Gbenga Dada Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria
Juliana Ngozi ndunagu Department of Computer Sciences, National Open University of Nigeria, Nigeria
Terrang Abubakar Umar 5Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria
Akinwunmi S.A 5Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria

Keywords:

COVID-19 Structural Equation Modelling, Latent variables, Random forest, Boosting.

Abstract

Since the declaration of COVID-19 as a global pandemic, it has been transmitted to more than 200 nations of the world. The harmful impact of the pandemic on the economy of nations is far greater than anything suffered in almost a century. The main objective of this paper is to apply Structural Equation Modeling (SEM) and Machine Learning (ML) to determine the relationships among COVID-19 risk factors, epidemiology factors and economic factors. Structural equation modeling is a statistical technique for calculating and evaluating the relationships of manifest and latent variables. It explores the causal relationship between variables and at the same time taking measurement error into account. Bagging (BAG), Boosting (BST), Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF) Machine Learning techniques was applied to predict the impact of COVID-19 risk factors. Data from patients who came into contact with coronavirus disease were collected from Kaggle database between 23 January 2020 and 24 June 2020. Results indicate that COVID-19 risk factors have negative effects on epidemiology factors. It also has negative effects on economic factors.

Dimensions

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