Black populations in the U.S. are one demographic group that has shown to have disproportionately high rates of COVID-19 cases. Genetics are not responsible for explaining this trend, but rather societal processes that make black populations more likely to get the virus. The scatterplot displays a general trend of positive correlation between variables, indicating that as percent black population in a county increases, so do the number of COVID-19 cases. Click on the scatterplot for more information!
Another vulnerability indicator to COVID-19 has been elderly populations. Studies have found that older populations have higher rates of COVID-19 cases due to weaker immune systems and pre-existing health conditions. The trend in this scatterplot displays a negative correlation, indicating that COVID-19 cases actually decrease as elder population in a county increases. However, these results are most likely due to the spatial distribution of elders because counties with high COVID-19 cases are generally densily populated areas where elders do not live. Click on the scatterplot for more information!
Trends showing high rates of COVID-19 cases appear in areas with greater population densities, such as New York City, due to large numbers of people living in a confined space, which encourages the spread of the virus. This scatterplot displays a positive correlation between variables, indicating that as population density increases, so do the number of COVID-19 cases. Click on the scatterplot for more information!
Another vulnerability factor to the COVID-19 virus has been income. Patterns of high COVID-19 rates appear in low-income areas due to the inability to access to medical care, lack of hygiene, and poor nutrition. The trend in this scatterplot displays a positive correlation, indicating that as average household income increases in a county, so do the number of COVID-19 cases. However, this trend can be explained by high COVID-19 cases occuring in cities that generally have higher average incomes. Click on the scatterplot for more information!