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Title: Data Analysis of Crime and Rates of Hospitalization due to COVID-19
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.  more » « less
Award ID(s):
1923986 2032344 2131116 2026412
NSF-PAR ID:
10333254
Author(s) / Creator(s):
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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