Back to Search Start Over

Analyzing the Effect of Vaccination Over COVID Cases and Deaths in Asian Countries Using Machine Learning Models.

Authors :
Rustagi, Vanshika
Bajaj, Monika
Tanvi
Singh, Priya
Aggarwal, Rajiv
AlAjmi, Mohamed F.
Hussain, Afzal
Hassan, Md. Imtaiyaz
Singh, Archana
Singh, Indrakant K.
Source :
Frontiers in Cellular & Infection Microbiology; 2/8/2022, Vol. 12, p1-13, 13p
Publication Year :
2022

Abstract

Coronavirus Disease 2019 (COVID-19) is spreading across the world, and vaccinations are running parallel. Coronavirus has mutated into a triple-mutated virus, rendering it deadlier than before. It spreads quickly from person to person by contact and nasal or pharyngeal droplets. The COVID-19 database 'Our World in Data' was analyzed from February 24, 2020, to September 26, 2021, and predictions on the COVID positives and their mortality rate were made. Factors such as Vaccine data for the First and Second Dose vaccinated individuals and COVID positives that influence the fluctuations in the COVID-19 death ratio were investigated and linear regression analysis was performed. Based on vaccination doses (partial or complete vaccinated), models are created to estimate the number of patients who die from COVID infection. The estimation of variance in the datasets was investigated using Karl Pearson's coefficient. For COVID-19 cases and vaccination doses, a quartic polynomial regression model was also created. This predictor model helps to predict the number of deaths due to COVID-19 and determine the susceptibility to COVID-19 infection based on the number of vaccine doses received. SVM was used to analyze the efficacy of models generated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22352988
Volume :
12
Database :
Complementary Index
Journal :
Frontiers in Cellular & Infection Microbiology
Publication Type :
Academic Journal
Accession number :
155125436
Full Text :
https://doi.org/10.3389/fcimb.2021.806265