Impact of Covid-19 by Income and Population

Daniel Niedzwiedzki and Dr. Daehan Kwak School of Computer Science and Technology, Kean University, Union, NJ 07083

Since the initial outbreak in early January 2020, COVID-19 has been a major issue in the United States. Even when preventative measures were taken to minimize the threat, COVID-19 continues to spread throughout the United States and has impacted millions of lives as well as caused countless businesses to close. Highly populated areas were among the first to see exponential growth in cases during the initial outbreak and needed to quickly adapt in the attempt to contain the virus. As of December 2020, there are over thirteen million reported cases of COVID-19 within the United States. While some states have been able to flatten the curve, many are still struggling while cases keep rising. With all these cases, there must be a driving force behind why some areas are getting impacted harder than others. Recent articles and scholarly work suggest that lower income levels, as well as the density of population have significant impacts on the cases to build up quicker. 

The goal of this project is to create a real-time visual representation of COVID-19 cases in regard to population and income at a state and county level of detail. Within this project COVID-19 is represented with density circles. These markers are scaled to the proportion to depict how prevalent COVID-19 is in a particular area. Upon that, an overlay can be triggered to show the income or population level. Income and Population data are extracted directly from the website. This ensures that all data is accurate and depicted correctly. The data provides a clear view of outbreak hotspots along with income and population in a selected area. 

Additional Abstract Information

Presenter: Daniel Niedzwiedzki

Institution: Kean University

Type: Poster

Subject: Computer Science

Status: Approved

Time and Location

Session: Poster 5
Date/Time: Tue 12:30pm-1:30pm
Session Number: 4025