Given the exceptional impacts of COVID-19 infection on the United States, this capstone project for agraduate-level urban data science course seeks to identify some of the underlying socioeconomic factors driving its unprecedented spread.
Analysis was done primarily using Python, using a variety of data sources and statistical methods. Regression analyses were also performed to develop a better understanding of which factors have the most impact. This could prove useful in implementing more effective resource allocation and improved policy responses. Identifying the key determinants of the spread of the pandemic can also aid planners, policy-makers, and public health authorities in their efforts to prepare for future outbreaks, especially for those in the most vulnerable socioeconomic groups.
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