Spatial Modeling of COVID-19 Vaccine Hesitancy in Texas

Abstract

This thesis investigates the spatial dynamics and factors influencing COVID-19 vaccination rates across the state of Texas. Throughout the search of data in several databases, this research identifies several significant variables such as gender, education level, employment, income, insurance coverage, race and ethnicity, age, party choice, religion and flu vaccine intake, that affect vaccine acceptance. Using spatial analysis and Geographical Information Systems we reach to conclusions about the variables above described. The study reveals distinct spatial patterns of vaccine hesitancy, particularly highlighting the differences between the several areas within the state (north, south, west and east) and offers insights of the impact of socioeconomic and demographic disparities. By employing Local and Global Moran’s I statistics, hot spot analysis, and Multiscale Geographically Weighted Regression (MGWR), (using ArcGIS Pro) the research provides a nuanced understanding of the geographical variability in the COVID19 vaccine intake, in the state of Texas both for year 2021 and 2022. The findings aim to inform authority figures of public health and politics in order to create better interventions and policies. This measures would help to enhance equity vaccine distribution and improve health communication strategies. Ultimately contributing to better management of future public health crises.