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A global analysis of the impact of COVID-19 stay-at-home restrictions on crime.

Amy E NivetteRenee ZahnowRaul AguilarAndri AhvenShai AmramBarak ArielMaría José Arosemena BurbanoRoberta AstolfiDirk BaierHyung-Min BarkJoris E H BeijersMarcelo BergmanGregory BreetzkeI Alberto Concha-EastmanSophie Curtis-HamRyan DavenportCarlos DíazDiego FleitasManne GerellKwang-Ho JangJuha KääriäinenTapio Lappi-SeppäläWoon-Sik LimRosa Loureiro RevillaLorraine MazerolleGorazd MeškoNoemí PeredaMaria Fernanda Tourinho PeresRubén Poblete-CazenaveSimon RoseRobert SvenssonNico TrajtenbergTanja van der LippeJoran VeldkampCarlos J Vilalta PerdomoManuel P Eisner
Published in: Nature human behaviour (2021)
The stay-at-home restrictions to control the spread of COVID-19 led to unparalleled sudden change in daily life, but it is unclear how they affected urban crime globally. We collected data on daily counts of crime in 27 cities across 23 countries in the Americas, Europe, the Middle East and Asia. We conducted interrupted time series analyses to assess the impact of stay-at-home restrictions on different types of crime in each city. Our findings show that the stay-at-home policies were associated with a considerable drop in urban crime, but with substantial variation across cities and types of crime. Meta-regression results showed that more stringent restrictions over movement in public space were predictive of larger declines in crime.
Keyphrases
  • coronavirus disease
  • sars cov
  • healthcare
  • emergency department
  • electronic health record
  • deep learning
  • artificial intelligence