While the COVID-19 pandemic caused widespread mortality in the United States, its impact varied substantially across different population groups. Certain racial and ethnic groups experienced a disproportionate share of COVID-19 deaths, reflecting long-standing structural inequalities related to access to healthcare, employment conditions, housing, and chronic disease burden. This study examines data from the Centers for Disease Control and Prevention (CDC) to better understand these disparities.
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The dataset I have utilized provides a detailed breakdown of COVID-19 mortality in the United States by race and ethnicity over time. It includes provisional counts of COVID-19 deaths, the percentage distribution of those deaths across racial and ethnic groups, and corresponding population distribution measures, including weighted population estimates that account for where deaths occurred geographically.
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How did COVID-19 mortality vary across racial and ethnic groups in the United States, and what do these differences reveal about health disparities and equity? This is the overarching question that this study answers. By examining death counts, population-adjusted ratios, temporal trends, and weighted distributions, this analysis aims to provide a comprehensive picture of which communities were most affected, how disparities evolved throughout the pandemic, and what insights can inform more equitable public health responses in the future.
The dataset was cleaned and structured in Tableau to enable accurate analysis and visualization. Null and missing values in death counts, population measures, and demographic categories were addressed to ensure reliable calculations. Numeric fields, such as death counts and population percentages, were set as measures, whereas categorical fields, including race/ethnicity and time periods, were set as dimensions. Date fields were formatted for time-series analysis, and calculated fields were created to compute ratios like deaths relative to population share and weighted death percentages. Hierarchical groupings were also created to organize the data by race and ethnicity. This preparation allowed for clear comparative, temporal, and equity-focused analyses of COVID-19 mortality across various racial and ethnic groups.
