JOURNAL ARTICLE

A review of crime trends in Hong Kong during COVID-19: Empirical analysis based on ARIMA model.

  • Published In: Policing: A Journal of Policy & Practice, 2024, v. 18. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Gao, Yifan 3 of 3

Abstract

This study examines the impact of COVID-19 on crime dynamics in Hong Kong by using an autoregressive integrated moving average (ARIMA) model to compare expected and observed crime rates. It identifies significant decreases in serious assault, burglary, and theft from vehicles, alongside increases in fraud-related crimes and child abuse incidents during the pandemic. The research emphasizes the relevance of Routine Activities Theory and General Strain Theory in understanding how changes in daily routines, target availability, and emotional strain influence crime patterns. These findings provide insights for researchers, policymakers, and law enforcement to develop informed crime prevention strategies in the post-pandemic context.

Additional Information

  • Source:Policing: A Journal of Policy & Practice. 2024/01, Vol. 18, p1
  • Document Type:Article
  • Subject Area:Law
  • Publication Date:2024
  • ISSN:1752-4512
  • DOI:10.1093/police/paae070
  • Accession Number:184072923
  • Copyright Statement:Copyright of Policing: A Journal of Policy & Practice is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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