A Survey of Machine Learning Methods to Detect COVID-19 Severity, Mortality, and Vaccines Efficacy

A Survey of Machine Learning Methods to Detect COVID-19 Severity, Mortality, and Vaccines Efficacy

  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-11
Year of Publication : 2022
Author : Abdullah M. Baqasah
DOI : 10.14445/22315381/IJETT-V70I11P204

How to Cite?

Abdullah M. Baqasah, "A Survey of Machine Learning Methods to Detect COVID-19 Severity, Mortality, and Vaccines Efficacy," International Journal of Engineering Trends and Technology, vol. 70, no. 11, pp. 28-46, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I11P204

Abstract
In this paper, we tackle the problem of COVID-19 detection. We present a survey on machine learning (ML) and deep learning (DL) methods to predict different vaccines' severity, mortality, and efficacy. For severity, we study the spread of Alpha, Beta, Delta, and Gamma in the countries where the variant first appears, such as the United Kingdom, South Africa, India, and Brazil. For mortality, we present works that study the rate of mortality caused by each variant. Finally, we present an overview of methods that respond to the question: do the five vaccines—produced by—Moderna, Pfizer, Novavax, Johnson & Johnson, and Astra Zeneca slow down the progress of COVID-19 variants?

Keywords
Coronavirus, Covid-19, Machine learning, Deep learning, Vaccine efficacy, Mortality, Severity.

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