Abstract
The COVID-19 pandemic has had a great impact on the world, with the United States experiencing a disproportionately high burden in terms of infections and deaths compared to other nations. The virus has disrupted daily life across the country and highlighted longstanding health inequalities. Therefore, this study aims to analyze the correlation between total COVID-19 cases and deaths with various demographic variables such as median age, education level, race, ethnicity, income, unemployment rate, disability status, and insurance coverage. The goal is to identify groups of people who are disproportionately affected by the COVID-19 virus and the factors that contribute to this inequality. To achieve this, the study collects data from all 50 states in the United States, using authoritative sources such as the U.S. Census Bureau and the Bureau of Labor. Then, ETL process (Extract, Transform, and Load) is performed to obtain clean and refined datasets and compile them into a final table for correlation analysis. With the help of this study, public health officials and policymakers could initiate the development of targeted interventions to ensure that everybody has the same opportunity to achieve good health, regardless of their demographic, economic, and social status.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1462-1468 |
| Number of pages | 7 |
| ISBN (Electronic) | 9798350327595 |
| DOIs | |
| State | Published - 2023 |
| Event | 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 - Las Vegas, United States Duration: 24 Jul 2023 → 27 Jul 2023 |
Publication series
| Name | Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 |
|---|
Conference
| Conference | 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 |
|---|---|
| Country/Territory | United States |
| City | Las Vegas |
| Period | 24/07/23 → 27/07/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 10 Reduced Inequalities
Keywords
- Correlation Analysis
- Covid-19
- Data Mining
- Data Visualization
- Health Disparities
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