(229) Identifying relationships between demographic, geographic, socioeconomic status and COVID-19 disparities: Storytelling with data

Objective : We aim to identify hidden relationships between demographic, geographic, and socioeconomic factors and COVID-19 infections and deaths in the US

Methods: Data on COVID-19 cases and deaths in the US published by the Centers for Disease Control and Prevention (CDC) between March 2020 and March 2022 was collected. Both descriptive and statistical analyses were conducted to compare the disparity differences among the groups. A threshold of 95% confidence interval was used in the Kruskal-Wallis statistical test.

Results: The highest cases and deaths due to COVID-19 were found in California (CA), New York (NY), and Florida (FL). Statistical analysis showed no statistical significance in case rates between rural and urban areas, but significantly higher death rates in rural areas (p < 0.001). The analysis also showed that communities with higher poverty levels were significantly higher in cases (p = 0.002) compared to communities with lower poverty levels. Similarly, we identified that there were statistically significant higher death rates in communities with higher poverty levels compared to others with lower poverty levels (p < 0.001). In addition, the analysis also showed that communities with higher uninsured levels were significantly higher in case and death rates compared to the communities with lower uninsured levels (p < 0.001).

Conclusions: Higher cases were identified in states with higher populated densities including CA, NY, and FL. Interestingly, data showed that rural areas had higher death rates compared to metropolitan areas, but not the case rates. Furthermore, higher case and death rates were identified in communities with higher poverty and uninsured levels. The findings provide insights for public health professionals to prepare and allocate resources for future events.