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Drug offence detection during the COVID-19 lockdown: a spatiotemporal study of change in a street-level drug market

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  • Payne, Jason Leslie

    (Australian National University)

  • Langfield, Cameron Thomas

    (Australian National University)

Abstract

The COVID-19 pandemic and the subsequent introduction of strict government orders to `stay-at-home' has led to a significant decline in most crime types--except, notably, illicit drug detections. However, the impact of these restrictions on open-air, or street-level, drug markets has been neglected in the study of COVID-19. In this paper, we use data from the state of Queensland, Australia, to explore how COVID-19 restrictions may have impacted the open-air drug market of Fortitude Valley in Brisbane. Using a spatiotemporal generalised additive model (GAM), we find that drug detections did not change in the Fortitude Valley region (despite significant increases across the whole state) but that this finding masked considerable reductions in and around the Fortitude Valley train station as well as in the vicinity Brunswick Street mall. It seems that any COVID-19-related decrease appears to have been offset by increases elsewhere, particularly to the streets north and south west of the main street market. These results highlight the limitations of city-wide aggregate analyses of crime during the pandemic and highlights the need for future research, including with qualitative and ethnographic methods to better understand the lived experiences of drug sellers/users and the law enforcement officers who policed these areas.

Suggested Citation

  • Payne, Jason Leslie & Langfield, Cameron Thomas, 2021. "Drug offence detection during the COVID-19 lockdown: a spatiotemporal study of change in a street-level drug market," SocArXiv 2x53n, Center for Open Science.
  • Handle: RePEc:osf:socarx:2x53n
    DOI: 10.31219/osf.io/2x53n
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    1. Langton, Samuel & Farrell, Graham & Dixon, Anthony, 2020. "Six Months In: Pandemic Crime Trends in England and Wales," SocArXiv t7ne8, Center for Open Science.
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