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doi: 10.1038/s41562-021-01139-z , 10.3929/ethz-b-000501000 , 10.17863/cam.73275 , 10.21256/zhaw-22682 , 10.60692/7yxw5-nyn72 , 10.60692/6ypx0-9c728 , 10.17863/cam.71679
pmid: 34079096
pmc: PMC8298205
handle: 2445/218851 , 10138/339144 , 20.500.11850/501000 , 2263/83701
doi: 10.1038/s41562-021-01139-z , 10.3929/ethz-b-000501000 , 10.17863/cam.73275 , 10.21256/zhaw-22682 , 10.60692/7yxw5-nyn72 , 10.60692/6ypx0-9c728 , 10.17863/cam.71679
pmid: 34079096
pmc: PMC8298205
handle: 2445/218851 , 10138/339144 , 20.500.11850/501000 , 2263/83701
AbstractThe 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.
Sociology and Political Science, Economics, Quarantine/trends, Social Sciences, Transportation, Infectious disease (medical specialty), Criminology, Other Legal Research, Social Distancing, Annan rättsvetenskaplig forskning, Demographic economics, Sociology, Pathology, Disease, Delictes, COVID-19/epidemiology, 360, Geography, Modeling the Dynamics of COVID-19 Pandemic, Influence of Built Environment on Active Travel, article, Justice and Strong Institutions, TIME, FOS: Sociology, Europe, Crime/trends, Environmental health, 364: Kriminologie, Modeling and Simulation, Quarantine, Physical Sciences, Medicine, Crime, Public Health, SDG 16 - Peace, 330, Criminology; Social policy; Sociology, Physical Distancing, COVID-19 pandemic, FOS: Law, Confinament (Emergència sanitària), Article, Social policy, Middle East, SDG 3 - Good Health and Well-being, Kriminologi, Virology, REGRESSION, FOS: Mathematics, Public Health/statistics & numerical data, Humans, /4014/4013, Demography, DECLINE, Prevention, COVID-19, Outbreak, United States, Coronavirus disease 2019 (COVID-19), /4014/523, Confinement (Sanitary emergency), Socioeconomics, Impact of Social Structure on Crime and Delinquency, /4014/4002, Restrictions, Law, 2019-20 coronavirus outbreak, Mathematics
Sociology and Political Science, Economics, Quarantine/trends, Social Sciences, Transportation, Infectious disease (medical specialty), Criminology, Other Legal Research, Social Distancing, Annan rättsvetenskaplig forskning, Demographic economics, Sociology, Pathology, Disease, Delictes, COVID-19/epidemiology, 360, Geography, Modeling the Dynamics of COVID-19 Pandemic, Influence of Built Environment on Active Travel, article, Justice and Strong Institutions, TIME, FOS: Sociology, Europe, Crime/trends, Environmental health, 364: Kriminologie, Modeling and Simulation, Quarantine, Physical Sciences, Medicine, Crime, Public Health, SDG 16 - Peace, 330, Criminology; Social policy; Sociology, Physical Distancing, COVID-19 pandemic, FOS: Law, Confinament (Emergència sanitària), Article, Social policy, Middle East, SDG 3 - Good Health and Well-being, Kriminologi, Virology, REGRESSION, FOS: Mathematics, Public Health/statistics & numerical data, Humans, /4014/4013, Demography, DECLINE, Prevention, COVID-19, Outbreak, United States, Coronavirus disease 2019 (COVID-19), /4014/523, Confinement (Sanitary emergency), Socioeconomics, Impact of Social Structure on Crime and Delinquency, /4014/4002, Restrictions, Law, 2019-20 coronavirus outbreak, Mathematics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 187 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
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| downloads | 15 |

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