Analyzing COVID-19 Vaccination Resistance
Start Date
29-4-2022 3:20 PM
Location
Alter Hall 307
Abstract
The Health Gap, a medical and community engagement non-profit, partnered with the Xavier University Center for Population Health from November to December 2020, right around the time the COVID-19 vaccine was being released. Through their collaboration, survey data was collected in Hamilton County and the surrounding Cincinnati area with the objective of uncovering and understanding what demographics are more likely to have hesitancy to get the vaccine, what variables contribute to this resistance, as well as to increase awareness, build knowledge, and expand capacity to mitigate the impact of COVID-19 on vulnerable black and brown populations. Professor Ronis-Tobin of the Xavier Population Health Department gave me access to the survey data that was collected for the purposes of a Business Analytics Final Project. Over the course of the semester, I have been sifting through, analyzing, interpreting, and visualizing the data using Microsoft Excel and Tableau with the objective of making a recommendation to the City of Cincinnati as to where it would be most beneficial to dedicate resources to try and raise the vaccination percentage in the area, as well as understand some of the reasons that people have hesitancies to get the vaccination and what demographics are more resistant to the vaccination. Variables were looked at such as income level, education level, and zip-code regarding responses to survey questions such as “How likely are you to get the vaccine”, “Do you believe COVID-19 is a serious threat to your health”, and “Do you believe the vaccine is safe”. These variables also were analyzed in relationship to perceived mask effectiveness, social distancing effectiveness and perceived protective versus preventative components of the vaccine. The results so far that were uncovered are unsurprising as this data is a little over a year old and has already been harnessed to make decisions, however it is reassuring to see that the data coincides with the societal perceptions of vaccination resistance. The data posits, for the most part, demographics that have lower levels of income and education seem to have a higher resistance to the vaccination, believe it is less safe, and that it is not as serious as a threat compared to people with higher levels of education and income. Interestingly, the highest education levels are the people who seem to believe that masks are not incredibly effective, positive perceptions of social distancing is nearly linear in relation to education level. All these results have helped me decide who the city of Cincinnati could look to target with ad campaigns or further information regarding the vaccine. Looking at geographic components has helped me come to my recommendation as to where the city of Cincinnati could best dedicate resources, possibly by instituting free classes or information sessions to further educate people to the benefits of getting the vaccination or hosting vaccine booths with information being presented to anybody who shows visual or verbal hesitancy. I briefly want to thank Professor Ronis-Tobin for giving me access to the data and helping me through this process of analysis, as well as Professor Ariyachandra for pushing me this entire semester and molding me into a better and more complete researcher and data analyst.
Analyzing COVID-19 Vaccination Resistance
Alter Hall 307
The Health Gap, a medical and community engagement non-profit, partnered with the Xavier University Center for Population Health from November to December 2020, right around the time the COVID-19 vaccine was being released. Through their collaboration, survey data was collected in Hamilton County and the surrounding Cincinnati area with the objective of uncovering and understanding what demographics are more likely to have hesitancy to get the vaccine, what variables contribute to this resistance, as well as to increase awareness, build knowledge, and expand capacity to mitigate the impact of COVID-19 on vulnerable black and brown populations. Professor Ronis-Tobin of the Xavier Population Health Department gave me access to the survey data that was collected for the purposes of a Business Analytics Final Project. Over the course of the semester, I have been sifting through, analyzing, interpreting, and visualizing the data using Microsoft Excel and Tableau with the objective of making a recommendation to the City of Cincinnati as to where it would be most beneficial to dedicate resources to try and raise the vaccination percentage in the area, as well as understand some of the reasons that people have hesitancies to get the vaccination and what demographics are more resistant to the vaccination. Variables were looked at such as income level, education level, and zip-code regarding responses to survey questions such as “How likely are you to get the vaccine”, “Do you believe COVID-19 is a serious threat to your health”, and “Do you believe the vaccine is safe”. These variables also were analyzed in relationship to perceived mask effectiveness, social distancing effectiveness and perceived protective versus preventative components of the vaccine. The results so far that were uncovered are unsurprising as this data is a little over a year old and has already been harnessed to make decisions, however it is reassuring to see that the data coincides with the societal perceptions of vaccination resistance. The data posits, for the most part, demographics that have lower levels of income and education seem to have a higher resistance to the vaccination, believe it is less safe, and that it is not as serious as a threat compared to people with higher levels of education and income. Interestingly, the highest education levels are the people who seem to believe that masks are not incredibly effective, positive perceptions of social distancing is nearly linear in relation to education level. All these results have helped me decide who the city of Cincinnati could look to target with ad campaigns or further information regarding the vaccine. Looking at geographic components has helped me come to my recommendation as to where the city of Cincinnati could best dedicate resources, possibly by instituting free classes or information sessions to further educate people to the benefits of getting the vaccination or hosting vaccine booths with information being presented to anybody who shows visual or verbal hesitancy. I briefly want to thank Professor Ronis-Tobin for giving me access to the data and helping me through this process of analysis, as well as Professor Ariyachandra for pushing me this entire semester and molding me into a better and more complete researcher and data analyst.
