Inspired by the opportunity to work with a Social Vulnerability dataset and the recency of the COVID-19 pandemic, our team designed and implemented a dashboard that will allow policymakers to evaluate their response to the pandemic across vulnerable counties in their jurisdiction.
What it does
The dashboard shows the difference in impact COVID-19 had on counties of differing vulnerabilities. COVID-19 infections, deaths, and vaccinations across high, moderate, and low vulnerability counties are visualized to better understand the pandemic's effect on these groups. The dashboard also shows how federal pandemic-relief aid was distributed throughout the counties, to see if more vulnerable counties were receiving the aid they needed.
How we built it
We began by exploring the SVI data and understanding how each of the different metrics worked in contributing to the overall SVI. Once we understood our dataset, we rolled up SVI data from a census tract to a county level in order to join it with COVID-19 datasets. We used R for all of our data explorations, cleaning, and joining. Once we had our data postured, we imported it into Tableau and developed a dashboard that visualized various metrics. We visualized social vulnerability across the country in 2014 and its impact on vaccines, infections, and deaths during the COVID-19 pandemic. Users of the dashboard can filter by state and SVI theme for a more granular look at COVID-19's impact on any county.
Challenges we ran into
The SVI data was at a census tract level, but the readily available COVID-19 data was at the county level. Because census tracts are subdivisions of counties, we had to clean and roll up the SVI data into the county level. Additionally, we had to format and clean the county-level COVID-19 datasets.
Accomplishments that we're proud of
We are proud of our final video, our visualizations, and our dashboard! We are also proud of our ability to accurately measure SVI for every county in the US using only the data given to us at the tract level, and the hard work that it took to accomplish that.
What we learned
We learned that the NC government seems to be allocating funding appropriately based on vulnerabilities and that the impact of covid is different across vulnerability levels. Certain themes showed significant discrepancies in terms of COVID outcomes - particularly housing composition and disabilities. We also learned that it is important to narrow the scope of a short analytical project early on so that everything planned can be accomplished before the due date.
What's next for Impact of Social Vulnerability on Covid Outcomes
We will continue to monitor the covid data and see if the trends in vulnerability that we are seeing continue. We would also like to import federal funding data for the entire United States (not just NC) to see if funds were properly administered across the US.
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