Adesina, Olumide S and Adedotun, Adedayo F. and Oladepo, Daniel S. and Adesina, Tolulope (2022) Knowledge, Attitude, and Perception of Health and Non-Healthcare Workers Towards COVID-19 Vaccination: Machine Learning Approach. International Journal of Sustainable Development and Planning, 17 (7). pp. 2015-2021.
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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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | COVID-19, vaccination, logistic regression, support vector machine, machine learning |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Mathematics |
| Depositing User: | nwokealisi |
| Date Deposited: | 10 Nov 2023 12:42 |
| Last Modified: | 10 Nov 2023 12:42 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/17559 |
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