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Decoding COVID-19 Vaccine Hesitancy Using Multiple Regression Analysis with Socioeconomic Values
Wei Lu1, Ling Xue2, Bria Shorten1
1Department of Computer Science, Keene State College, USNH, Keene NH, The University System of New Hampshire.
Abstract:
With the growth and development of COVID-19 and its variants, reaching a level of herd immunity is critically important for national security in public health. To deal with COVID-19, the United States has implemented phased plans to distribute COVID-19 vaccines. As of November 2022, over 80% of Americans had received their first shot to guard against COVID-19, and 68.6% were considered fully vaccinated, according to the dataset provided by CDC. However, a significant number of American people still hesitate to receive a shot of the COVID-19 vaccine. This paper aims to demystify COVID-19 vaccine hesitancy by analyzing various socioeconomic characteristics among individuals and communities, including unemployment rate, age groups, median household income, and education level. A multiple regression modeling and data visualization analysis show patterns with an increasing trend of vaccine hesitancy associated with a lower median household income, a younger age group, and a lower education level, which would help policymakers to make policies accordingly to target vaccine support information and remove this hurdle to end the COVID-19 pandemic effectively.
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