Abstract

Governments face the challenge of increasing the number of people who have been infected. Millions of daily examinations are being conducted around the world to detect the disease. The pandemic is growing increasingly challenging as the number of confirmed cases increases. Governments encounter a variety of obstacles in approving the benefits of Covid-19 vaccinations. Indeed, the idea of getting vaccinated is still fuzzy, and does vaccination protect against infectious disease? There are a lot of questions floating around. The lack of clear information about the Covid-19 vaccine will stymie the growing number of people who have been immunized. Therefore, governments are being pushed to demonstrate the consequences of delaying or rejecting the Covid-19 vaccine. In this study, I examined the number of people tested, infected, and vaccinated and found out what are the factors that affected taking the vaccine specially in the United Arab Emirates. The reasons why we need to estimate the number of people who have been vaccinated. How to increase the number of people vaccinated. Also identified who the 20 countries with highest number of cases are, what motivating factors have influenced the increase in the number of people vaccinated, and what will happen after the pandemic. Increased testing of the Covid-19 virus will lead to the discovery of more infected people and encourage people to get vaccinated because infected people are suffering. More vaccination will be given to test the hypothesis that more Covid-19 testing will occur. For this study, I used a dataset collected from health ministries around the world on the number of cases, deaths, age, male/female, some diseases, and whether the infected person is a smoker or not. The world's lockdown variables, population demographics, mortality rates, infection rates, and health were collected, focusing on the 20 countries with the highest numbers of infected persons, deaths , and vaccinated persons. Infection transmission and mortality data were presented in a linear stepwise fashion using ridge and lasso regression. Factor analysis was used to investigate the overall structure of the Covid- 19 data, resulting in a theoretical model that was tested using latent variable path analysis. The mathematical model can help determine when these intervention methods are most effective for disease control and how they may impact disease dynamics. As a result, in this project, I developed a mathematical model that predicts the relationship between new cases of Covid-19 and those who have been fully vaccinated. I began my research on the pandemic environment by looking at a map of cases around the world, then looking at the top 20 countries by total number of cases and other factors, and finally doing some studies on the United Arab Emirates. During the last two years, I discovered that there have been four waves of the epidemic. It was important to conduct regular testing for citizens so that sick people could be easily identified and helped. I also discovered that some countries had more cases than others, which would allow other researchers to investigate the causes behind this and take preventative steps in similar occurrences in the future. I used linear regression to predict the new number of people who have been vaccinated, which will help stakeholders make decisions about reopening, especially in areas with large populations, such as schools, universities, ministries, and other areas.

Publication Date

5-2022

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Ioannis Karamitsos

Campus

RIT Dubai

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