%0 Journal Article
%T Spatial Modeling of COVID-19 Occurrence and Vaccination Rate across Counties in Ohio State from Jan. 2020 to April 2023
%A Olawale Oluwafemi
%A Oluwaseun Ibukun
%A Yaw Kwarteng
%A Kehinde Adebowale
%A Yahaya Danjuma
%A Samson Mela
%J Journal of Geographic Information System
%P 80-96
%@ 2151-1969
%D 2025
%I Scientific Research Publishing
%R 10.4236/jgis.2025.171005
%X The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination tracker dashboard. GIS-based exploratory analysis was conducted to select four variables (poverty, black race, population density, and vaccination) to explain COVID-19 occurrence during the study period. Consequently, spatial statistical techniques such as Moran&#8217;s I, Hot Spot Analysis, Spatial Lag Model (SLM), and Spatial Error Model (SEM) were used to explain the COVID-19 occurrence and vaccination rate across the 88 counties in Ohio. The result of the Local Moran&#8217;s I analysis reveals that the epicenters of COVID-19 and vaccination followed the same patterns. Indeed, counties like Summit, Franklin, Fairfield, Hamilton, and Medina were categorized as epicenters for both COVID-19 occurrence and vaccination rate. The SEM seems to be the best model for both COVID-19 and vaccination rates, with R<sup>2</sup> values of 0.68 and 0.70, respectively. The GWR analysis proves to be better than Ordinary Least Squares (OLS), and the distribution of R<sup>2</sup> in the GWR is uneven throughout the study area for both COVID-19 cases and vaccinations. Some counties have a high R<sup>2</sup> of up to 0.70 for both COVID-19 cases and vaccinations. The outcomes of the regression analyses show that the SEM models can explain 68% - 70% of COVID-19 cases and vaccination across the entire counties within the study period. COVID-19 cases and vaccination rates exhibited significant positive associations with black race and poverty throughout the study area.
%K COVID-19 Prevalence
%K COVID-19 Vaccination
%K Ohio
%K Spatial Lag Model
%K Spatial Error Model
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=140911