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. 2021 Jul;5(7):868-877.
doi: 10.1038/s41562-021-01139-z. Epub 2021 Jun 2.

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

Amy E Nivette  1   2 , Renee Zahnow  3 , Raul Aguilar  4 , Andri Ahven  5 , Shai Amram  6 , Barak Ariel  6   7 , María José Arosemena Burbano  7 , Roberta Astolfi  8 , Dirk Baier  9 , Hyung-Min Bark  10 , Joris E H Beijers  11 , Marcelo Bergman  12 , Gregory Breetzke  13 , I Alberto Concha-Eastman  14 , Sophie Curtis-Ham  15 , Ryan Davenport  16   17 , Carlos Díaz  18 , Diego Fleitas  12 , Manne Gerell  19 , Kwang-Ho Jang  20 , Juha Kääriäinen  21 , Tapio Lappi-Seppälä  21 , Woon-Sik Lim  20 , Rosa Loureiro Revilla  7 , Lorraine Mazerolle  3 , Gorazd Meško  22 , Noemí Pereda  23 , Maria F T Peres  8 , Rubén Poblete-Cazenave  24 , Simon Rose  7   17 , Robert Svensson  19 , Nico Trajtenberg  25 , Tanja van der Lippe  26 , Joran Veldkamp  26 , Carlos J Vilalta Perdomo  27 , Manuel P Eisner  7   28
Affiliations

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

Amy E Nivette et al. Nat Hum Behav. 2021 Jul.

Abstract

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.

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Conflict of interest statement

All authors of the article declare no competing interests relevant to the research presented in this article. The following authors declare affiliation to law enforcement or related public institutions: A.A., I.A.C.-E., S.C.-H., R.D., K.-H.J., W.-S.L. and S.R.

Figures

Fig. 1
Fig. 1. Seven-day moving average time series plots of daily numbers of crimes.
a, Assault (n = 23). b, Burglary (n = 20). c, Robbery (n = 24). d, Theft (n = 16). e, Vehicle theft (n = 20). f, Homicide (n = 25). Each time series is indexed to equal 100 on the day the first stay-at-home restrictions were implemented. The blue line indicates the average trend across all cities with available data. Zero time is the date on which stay-at-home restrictions were implemented.
Fig. 2
Fig. 2. IRR and 95% CI of stay-at-home restrictions on daily number of violent crimes.
a, Assault (n = 23). b, Robbery (n = 24). c, Homicide (n = 21). Overall summary effects estimated using random-effects meta-analytic techniques. ES, effect size. SaH (days), number of days under stay-at-home restrictions from the beginning of 2020 until the end of the respective time series from May to September 2020. Full results by city and crime can be found in Supplementary Table 17.
Fig. 3
Fig. 3. IRR and 95% CI of stay-at-home restrictions on daily number of property crimes.
a, Burglary (n = 20). b, Theft (n = 16). c, Vehicle theft (n = 20). Overall summary effects estimated using random-effects meta-analytic techniques. ES, effect size. SaH (days), number of days under stay-at-home restrictions from the beginning of 2020 until the end of the respective time series from May to September 2020. Full results by city and crime can be found in Supplementary Table 17.
Fig. 4
Fig. 4. Scatterplot depicting bivariate correlation between overall average decline in crime by city and stringency of stay-at-home restrictions (n = 27).
The overall average decline was computed using the summary effect sizes for each city reported in Supplementary Table 17, with predicted linear relationship between average decline and stay-at-home stringency index (dotted line and shaded area) and 95% confidence intervals (shaded area).
See this image and copyright information in PMC

Comment in

  • Global crime trends during COVID-19.
    Boman JH 4th, Mowen TJ. Boman JH 4th, et al. Nat Hum Behav. 2021 Jul;5(7):821-822. doi: 10.1038/s41562-021-01151-3. Nat Hum Behav. 2021. PMID: 34117455 Free PMC article.

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