Offline crime bounces back to pre-COVID levels, cyber stays high:interrupted time-series analysis in Northern Ireland

Buil Gil, David and Zeng, Yongyu and Kemp, Steven (2021) Offline crime bounces back to pre-COVID levels, cyber stays high:interrupted time-series analysis in Northern Ireland. Crime Science, 10.

Full text not available from this repository.

Abstract

Much research has shown that the first lockdowns imposed in response to the COVID-19 pandemic were associated with changes in routine activities and, therefore, changes in crime. While several types of violent and property crime decreased immediately after the first lockdown, online crime rates increased. Nevertheless, little research has explored the relationship between multiple lockdowns and crime in the mid-term. Furthermore, few studies have analysed potentially contrasting trends in offline and online crimes using the same dataset. To fill these gaps in research, the present article employs interrupted time-series analysis to examine the effects on offline and online crime of the three lockdown orders implemented in Northern Ireland. We analyse crime data recorded by the police between April 2015 and May 2021. Results show that many types of traditional offline crime decreased after the lockdowns but that they subsequently bounced back to pre-pandemic levels. In contrast, results appear to indicate that cyber-enabled fraud and cyber-dependent crime rose alongside lockdown-induced changes in online habits and remained higher than before COVID-19. It is likely that the pandemic accelerated the long-term upward trend in online crime. We also find that lockdowns with stay-at-home orders had a clearer impact on crime than those without. Our results contribute to understanding how responses to pandemics can influence crime trends in the mid-term as well as helping identify the potential long-term effects of the pandemic on crime, which can strengthen the evidence base for policy and practice.

Item Type:
Journal Article
Journal or Publication Title:
Crime Science
ID Code:
162223
Deposited By:
Deposited On:
12 Nov 2021 14:50
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Sep 2023 04:39