Knowledge, Attitude, and Perception of Health and Non-Healthcare Workers Towards COVID-19 Vaccination: Machine Learning Approach
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Date
2022
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Abstract
There have been concerns globally as to whether taking COVID-19 vaccination is harmful or
not. In this study, we conducted an online survey to measure the knowledge and attitude of
people, first about COVID-19, and second about COVID-19 vaccination—various analyses
such as descriptive statistics, logistic regression, and support vector regression with k-fold
cross-validation. The support vector machine and tuned support vector machine suggest a
better fit based on cross-validation error. The results show that immigration requirements
significantly explain why an individual would accept the COVID-19 vaccine. This study
suggests that people in authority should look into people's concerns regarding taking the
COVID-19 vaccine and address them accordingly. The study aims to draw the attention of the
people to the concern that surrounds taking COVID-19 vaccination and explored various
statistical techniques to draw inference.
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Keywords
COVID-19, vaccination, logistic regression, support vector machine, machine learning