There has been an increasing concern that African American community has been disproportionately impacted during the coronavirus pandemic. This paper analyzes why the African American community is disproportionately impacted during the coronavirus pandemic and compares the COVID-19 data with hospitalizations, real estate, school closings, and crime data. Human behavior was impacted as a result of lockdown due to COVID pandemic and it lead to a shift in crime dynamics. We analyze shifts in crime types by comparing crimes before and after the COVID pandemic in Baltimore. There was a significant decline in total crimes during the time period immediately following stay at home orders. Findings show that the disproportionality among the African American community is significantly influenced by factors such as living in more crowded housing situations, working in consumer-facing serviced industries, having higher rates of pre-existing medical conditions, and lack of insurance or a consistent care source.
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Data Visualization Tool for Covid-19 and Crime Data
Data visualization gives a visual context through maps or graphs and makes it easier for the human mind to identify trends, patterns, and outliers within large data sets. The understanding of patterns and location of crime through data visualization and data mining techniques approaches is a very useful tool which can help and support police forces. Identification of crime characteristics and types are the first step for developing further analysis. This paper describes the development of data visualization tool using Unity 3D and Maptitude GIS for visualization of Baltimore COVID-19 and crime data. This effort aims to determine parameters that influence the vulnerability of African Americans to COVID-19 during the pandemic. The study has found that the factors shown to be influential in a person’s susceptibility include neighborhood and physical environment, housing, occupation, education, income, and wealth gaps. The data collected from Baltimore incident reports and findings shared by Maryland SOA office shows that crime has increased and decreased in different areas during the time of COVID pandemic.
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- NSF-PAR ID:
- 10333251
- Date Published:
- Journal Name:
- Proceeding of the IEEE International Conference on Computational Science and Computational Intelligence, (CSCI'21),Symposium of Big Data and Data Science (CSCI-ISBD)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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