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Exploring the Impact of Socioeconomic and Built Environment Factors on Theft Crime Trends in Chicago During the COVID-19 Pandemic
- 1 University of Hong Kong
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Abstract
The COVID-19 pandemic has disrupted urban social and economic conditions worldwide, influencing crime trends and patterns. This study examines how socio-economic and built environment factors affect theft crime density in Chicago across different pandemic phases. Using both linear regression and machine learning models, we analyze crime data to identify key factors driving changes in theft crime trends, focusing on the role of built environment elements such as public facilities, commercial venues, and transportation hubs. Results indicate that built environment features have a significant impact on theft density, while socio-economic factors like unemployment and income inequality show variable effects across pandemic periods. These findings suggest that urban and social factors interact to influence crime patterns, with non-linear models capturing these complex relationships more effectively than traditional methods. For policymakers and urban planners, the results underscore the importance of incorporating built environment considerations into crime prevention strategies, particularly in adapting urban spaces to foster safer, more resilient communities in the post-pandemic era.
Keywords
crime prediction, built environment, socioeconomic factors, machine learning, urban planning
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Cite this article
Wang,X. (2024). Exploring the Impact of Socioeconomic and Built Environment Factors on Theft Crime Trends in Chicago During the COVID-19 Pandemic. Journal of Applied Economics and Policy Studies,14,21-30.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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