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Exploring regional variability in the short-term impact of COVID-19 on property crime in Queensland, Australia

Authors
  • Payne, Jason L.1
  • Morgan, Anthony2
  • Piquero, Alex R.3, 4
  • 1 University of Wollongong, Keiraville, Australia , Keiraville (Australia)
  • 2 Australian Institute of Criminology, Canberra, Australia , Canberra (Australia)
  • 3 University of Miami, Coral Gables, USA , Coral Gables (United States)
  • 4 Monash University, Melbourne, Australia , Melbourne (Australia)
Type
Published Article
Journal
Crime Science
Publisher
Springer Berlin Heidelberg
Publication Date
Mar 08, 2021
Volume
10
Issue
1
Identifiers
DOI: 10.1186/s40163-020-00136-3
Source
Springer Nature
Keywords
License
Green

Abstract

Confronted by rapidly growing infection rates, hospitalizations and deaths, governments around the world have introduced stringent containment measures to help reduce the spread of COVID-19. This public health response has had an unprecedented impact on people’s daily lives which, unsurprisingly, has also had widely observed implications in terms of crime and public safety. Drawing upon theories from environmental criminology, this study examines officially recorded property crime rates between March and June 2020 as reported for the state of Queensland, Australia. We use ARIMA modeling techniques to compute 6-month-ahead forecasts of property damage, shop theft, residential burglary, fraud, and motor vehicle theft rates and then compare these forecasts (and their 95% confidence intervals) with the observed data for March through to June. We conclude that, with the exception of fraud, all property offence categories declined significantly. For some offence types (shop stealing, other theft offences, and residential burglary), the decrease commenced as early as March. For other offence types, the decline was lagged and did not occur until April or May. Non-residential burglary was the only offence type to significantly increase, which it did in March, only to then decline significantly thereafter. These trends, while broadly consistent across the state’s 77 local government areas still varied in meaningful ways and we discuss possible explanations and implications.

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