The existing state of knowledge confirms that tornadoes pose serious risks in the United States and continue to cause significant human and economic losses every year. Understanding the trends in tornado occurrence is necessary to assess tornado risk and improve emergency management throughout the country. Community demographic changes and space-time elements create non-random exposure to tornado hazards. Incorporation of urban-rural variables in disaster risk strategies is crucial when underrated tornado risk assessments in urban or rural areas may result in less protective action measures being taken based on perceived reduction in risk. The demographic shift into urban areas throughout the United States, with increases in population and building density, must then be considered in assessments and analyses of tornado risk. Since Aguirre et al. (1993) found an increase in tornado incidence in metropolitan counties between 1950-1990, few scholars have investigated more recent patterns of urban-rural tornado risk following the reduction of the reporting bias. This study applies statistical and geospatial methods to determine county- and regional-level geographic differences in urban-rural tornadoes between 1990-2019. Multiple urban-rural delineation schemas are applied to assess any changes in tornado occurrence using alternative spatial definitions. Bivariate Moran's I, correlation analysis, the difference of means, and analysis of variance testing reveal key differences in tornado occurrence amongst U.S. urban-rural spaces that are important to future weather risk reduction strategies. Results reveal significantly more tornadoes in urban counties within the Midwest and South census regions. Between these regions, significant geographic clustering exists in urban-rural tornado occurrence and the South contains significantly higher rates of urban tornadoes.
Studies have proved the disparities of COVID-19 case rates and death rates, but the relationship between COVID-19 vaccination and outcomes has not been well explored. This paper examines the spatial and temporal patterns of the relationships between the county-level COVID-19 daily new cases, fatalities, and full vaccinations in the United States from December 24th, 2020 through September 30th, 2021. Statistical and geospatial analyses show clear temporal and spatial patterns to the progression of COVID-19, culminating in differential impacts between urban and rural counties in the U.S. In most counties, daily new cases and deaths are significantly positively correlated, while daily new cases and vaccinations, daily new deaths, and vaccinations are negatively correlated. The negative correlation between cases and deaths was seen mostly in rural areas, and correlated with percentage of African Americans, people aged 65 and over, and Republican voters in these areas. The positive association between daily new cases and vaccinations were located in Michigan, Minnesota, Georgia, Alabama, and Virginia, and explained by the enormous surge of cases during the study period, more Republican voters, higher percentage of Blacks but lower percentage of Hispanics, and a lower percentage below poverty level. The daily new fatalities and full vaccinations were negatively associated for most counties, finding that urban areas have a stronger negative correlation than rural areas. The explanatory variables showed to have significantly different impacts in urban and rural areas. These results are critical in identifying geographic health disparities in COVID-19 vaccinations and outcomes and providing the evidentiary basis for targeting pandemic recovery and mitigation.