Measuring the resilience of criminogenic ecosystems to global disruption: A case-study of COVID-19 in China

The ecological impact of the COVID-19 pandemic on crime trends in Kerman Province of Iran

The COVID-19 pandemic has significantly impacted crime rates in Kerman province, Iran, revealing divergent patterns compared to global trends. This ecological study utilized the Poisson regression model and interrupted time-series Poisson regression model to analyze data collected from the Iranian Legal Medicine Organization (ILMO) database and the Kerman Criminal Investigation Department of Police database, focusing on theft, conflicts, and homicide rates in this region. Our findings indicate that in 2020, the incidence rate ratio of conflicts increased compared to previous years. Before the pandemic, thefts were on the rise, while homicides were decreasing. However, with the onset of the pandemic, thefts initially decreased, and homicides experienced a notable increase. Subsequently, both thefts and homicides showed a declining trend. By the end of 2020, thefts were significantly lower than expected based on pre-pandemic data, while homicides were slightly higher. Initial fluctuations in crime rates may be related to quarantine measures and the challenges faced during the pandemic, while subsequent changes might be influenced by governmental interventions. Understanding the complex relationship between public health emergencies and criminal activities is crucial for informing policymaking and crime prevention efforts.

Disentangling the Impact of Covid-19: An Interrupted Time Series Analysis of Crime in New York City

The Covid-19 stay-at-home restrictions put in place in New York City were followed by an abrupt shift in movement away from public spaces and into the home. This study used interrupted time series analysis to estimate the impact of these changes by crime type and location (public space vs. residential setting), while adjusting for underlying trends, seasonality, temperature, population, and possible confounding from the subsequent protests against police brutality in response to the police-involved the killing of George Floyd. Consistent with routine activity theory, we found that the SAH restrictions were associated with decreases in residential burglary, felony assault, grand larceny, rape, and robbery; increases in non-residential burglary and residential grand larceny motor vehicle; and no change in murder and shooting incidents. We also found that the protests were associated with increases in several crime types: felony assault, grand larceny, robbery, and shooting incidents. Future research on Covid-19's impact on crime will need to account for these potentially confounding events.

Analyzing the Impact of COVID-19 Lockdowns on Violent Crime

Existing research suggests that COVID-19 lockdowns tend to contribute to a decrease in overall urban crime rates. Most studies have compared pre-lockdown and post-lockdown periods to lockdown periods in Western cities. Few have touched on the fine variations during lockdowns. Equally rare are intracity studies conducted in China. This study tested the relationship between violent crime and COVID-19 lockdown policies in ZG City in southern China. The distance from the isolation location to the nearest violent crime site, called "the nearest crime distance", is a key variable in this study. Kernel density mapping and the Wilcoxon signed-rank test are used to compare the pre-lockdown and post-lockdown periods to the lockdown period. Panel logistic regression is used to test the fine variations among different stages during the lockdown. The result found an overall decline in violent crime during the lockdown and a bounce-back post-lockdown. Violent crime moved away from the isolation location during the lockdown. This outward spread continued for the first two months after the lifting of the lockdown, suggesting a lasting effect of the lockdown policy. During the lockdown, weekly changes in COVID-19 risk ratings at the district level in ZG City also affected changes in the nearest crime distance. In particular, an increase in the risk rating increased that distance, and a drop in the risk rating decreased that distance. These findings add new results to the literature and could have policy implications for joint crime and pandemic prevention and control.

The Effect of COVID-19 on Police Activities: Traffic Stops, Arrests, and Use of Force

COVID-19 may affect police activities (i.e., traffic stops, arrests, and use of force) due to public compliance with COVID-19 restrictions, changes in individuals’ daily activities, and health threats posed by COVID-19. The purpose of this research is to examine the effects of COVID-19 on police activities and the trends in these activities in Burlington, Vermont. The data that measured arrests, traffic stops, and use of force were obtained from the Burlington Police Department website and covered the period from December 10, 2018 through June 14, 2021. Then, the daily time-series data for arrest rate, use of force rate, and traffic stop rate were created (N = 918; 459 days pre-COVID-19 and 459 days during COVID-19). The results showed that COVID-19 statistically significantly increased traffic stops and arrests, but not use of force on the day immediately following the implementation of the COVID-19 restrictions and then remained stable over time. However, no significant change was detected in the trends of arrests, traffic stops, and use of force before and during the COVID-19 period. COVID-19 had a significant immediate and lasting effect on traffic stops and arrests, but not use of force.

Illegal waste fly-tipping in the Covid-19 pandemic: enhanced compliance, temporal displacement, and urban-rural variation

Objective

Illegal dumping of household and business waste, known as fly-tipping in the UK, is a significant environmental crime. News agencies reported major increases early in the COVID-19 pandemic when waste disposal services were closed or disrupted. This study examines the effect of lockdowns on illegal dumping in the UK.

Method

A freedom of information request was sent to all local authorities in the UK asking for records of reported incidents of fly-tipping for before and after the first national lockdown. ARIMA modelling and year-on-year comparison was used to compare observed and expected levels of fly-tipping. Urban and rural local authorities were compared.

Results

A statistically significant decline in fly-tipping during the first lockdown was followed by a similar increase when lockdown ended. The effects largely cancelled each other out. There was pronounced variation in urban-rural experience: urban areas, with higher rates generally, experienced most of the initial drop in fly-tipping while some rural authorities experienced an increase.

Conclusion

Waste services promote compliance with laws against illegal dumping. When those services were disrupted during lockdown it was expected that fly-tipping would increase but, counter-intuitively, it declined. This enhanced compliance effect was likely due to increased perceived risk in densely populated urban areas. However, as lockdown restrictions were eased, fly-tipping increased to clear the backlog, indicating temporal displacement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40163-022-00170-3.

Down with the sickness? Los Angeles burglary and COVID-19 restrictions

Objectives

To provide a partial test of routine activities theory through a spatio-temporal analysis of the impacts of COVID-19 restrictions on burglary in Los Angeles.

Methods

Spatial point pattern tests, clustering, and non-parametric permutations tests were used to identify changes in burglary in the highest restriction period of 2020 as well as comparison periods for the past 10 years while controlling for the zoning within Los Angeles.

Results

COVID-19 restrictions significantly increased crime in commercial/industrial areas while it reduced crime in residential areas.

Conclusions

The predictions of routine activities theory were supported in regard to the importance of capable guardianship. Findings indicate that not only were the areas expected to see an increase in capable guardianship shown to have reduced crime, but that crime more generally across the city became more commercially oriented in terms of zoning as more individuals were confined to residential areas.

Anti-social behaviour in the coronavirus pandemic

Anti-social behaviour recorded by police more than doubled early in the coronavirus pandemic in England and Wales. This was a stark contrast to the steep falls in most types of recorded crime. Why was ASB so different? Was it changes in 'traditional' ASB such as noisy neighbours, or was it ASB records of breaches of COVID-19 regulations? Further, why did police-recorded ASB find much larger early-pandemic increases than the Telephone Crime Survey for England and Wales? This study uses two approaches to address the issues. The first is a survey of police forces, via Freedom of Information requests, to determine whether COVID-regulation breaches were recorded as ASB. The second is natural language processing (NLP) used to interrogate the text details of police ASB records. We find police recording practice varied greatly between areas. We conclude that the early-pandemic increases in recorded ASB were primarily due to breaches of COVID regulations but around half of these also involved traditional forms of ASB. We also suggest that the study offers proof of concept that NLP may have significant general potential to exploit untapped police text records in ways that inform policing and crime policy.

Spatio-temporal stratified associations between urban human activities and crime patterns: a case study in San Francisco around the COVID-19 stay-at-home mandate

Crime changes have been reported as a result of human routine activity shifting due to containment policies, such as stay-at-home (SAH) mandates during the COVID-19 pandemic. However, the way in which the manifestation of crime in both space and time is affected by dynamic human activities has not been explored in depth in empirical studies. Here, we aim to quantitatively measure the spatio-temporal stratified associations between crime patterns and human activities in the context of an unstable period of the ever-changing socio-demographic backcloth. We propose an analytical framework to detect the stratified associations between dynamic human activities and crimes in urban areas. In a case study of San Francisco, United States, we first identify human activity zones (HAZs) based on the similarity of daily footfall signatures on census block groups (CBGs). Then, we examine the spatial associations between crime spatial distributions at the CBG-level and the HAZs using spatial stratified heterogeneity statistical measurements. Thirdly, we use different temporal observation scales around the effective date of the SAH mandate during the COVID-19 pandemic to investigate the dynamic nature of the associations. The results reveal that the spatial patterns of most crime types are statistically significantly associated with that of human activities zones. Property crime exhibits a higher stratified association than violent crime across all temporal scales. Further, the strongest association is obtained with the eight-week time span centred around the SAH order. These findings not only enhance our understanding of the relationships between urban crime and human activities, but also offer insights into that tailored crime intervention strategies need to consider human activity variables.

How Do Collective Efficiency and Norms Influence the Social Resilience of Iranian Villagers Against the COVID-19? The Mediating Role of Social Leadership

The main purpose of the present research was to investigate the effects of collective efficacy and norms on the social resilience against the COVID-19 with the mediating role of social leadership. To this end, a cross-sectional survey was carried out in the Kerman and Fars provinces of Iran. Finally, 206 villagers were selected as the sample for collecting the required information. The research tool was a close-ended questionnaire whose validity and reliability was evaluated and confirmed. The results of testing direct hypotheses using structural equation modeling revealed that collective efficacy, social leadership, and norms had significant positive effects on social resilience against the COVID-19 pandemic. Comparison of the standardized effects demonstrated that collective efficacy is the most powerful predictor of the social resilience of villagers. Furthermore, testing indirect (mediation) hypotheses revealed that social leadership can successfully mediate the effect of collective efficacy on social resilience against the COVID-19. Investigating the moderated indirect hypotheses showed that governmental supports moderated the effect of collective efficacy on social resilience. Taken together, the independent variables could account for 62% of social resilience variance change. In the end, the practitioners, decision-makers, and interveners of the COVID-19 management programs in rural communities were provided with some applicable recommendations to be able to foster social resilience against the COVID-19.

In a world called catastrophe: the impact of COVID-19 on neighbourhood level crime in Vancouver, Canada

OBJECTIVES

To test for statistically significant change in crime rates across neighbourhoods in Vancouver, Canada, resulting from social restrictions within the natural experiment of the COVID-19 pandemic.

METHODS

Differential local Moran's I is used to identify statistically significant change in crime patterns across Vancouver's neighbourhoods because of COVID-19. These changes are analysed with variables from social disorganization theory constructs using ANOVA.

RESULTS

At the neighbourhood level, all crime types have significant change during COVID, but not always at the city level. Different neighbourhoods have different changes in crime despite these changes appearing to be constant at the city level; local effects asre important to consider. Variables representing the constructs of social disorganization theory are able to predict these changes.

CONCLUSIONS

COVID-19 has changed the patterns of crime in Vancouver, but most often in theoretically expected ways. Local changes are critical to understand crime during a pandemic.

Offline crime bounces back to pre-COVID levels, cyber stays high: interrupted time-series analysis in Northern Ireland

Much research has shown that the first lockdowns imposed in response to the COVID-19 pandemic were associated with changes in routine activities and, therefore, changes in crime. While several types of violent and property crime decreased immediately after the first lockdown, online crime rates increased. Nevertheless, little research has explored the relationship between multiple lockdowns and crime in the mid-term. Furthermore, few studies have analysed potentially contrasting trends in offline and online crimes using the same dataset. To fill these gaps in research, the present article employs interrupted time-series analysis to examine the effects on offline and online crime of the three lockdown orders implemented in Northern Ireland. We analyse crime data recorded by the police between April 2015 and May 2021. Results show that many types of traditional offline crime decreased after the lockdowns but that they subsequently bounced back to pre-pandemic levels. In contrast, results appear to indicate that cyber-enabled fraud and cyber-dependent crime rose alongside lockdown-induced changes in online habits and remained higher than before COVID-19. It is likely that the pandemic accelerated the long-term upward trend in online crime. We also find that lockdowns with stay-at-home orders had a clearer impact on crime than those without. Our results contribute to understanding how responses to pandemics can influence crime trends in the mid-term as well as helping identify the potential long-term effects of the pandemic on crime, which can strengthen the evidence base for policy and practice.

Measuring the impact of the COVID-19 lockdown on crime in a medium-sized city in China

ABSTRACT

OBJECTIVES

The study examines the variation in the daily incidence of eight acquisitive crimes: automobile theft, electromobile theft, motorcycle theft, bicycle theft, theft from automobiles, pickpocketing, residential burglary, and cyber-fraud before the lockdown and the duration of the lockdown for a medium-sized city in China.

METHODS

Regression discontinuity in time (RDiT) models are used to test the effect of the lockdown measures on crime by examining the daily variation of raw counts and rate.

RESULTS

It is indicated that in contrast to numerous violent crime categories such as domestic violence where findings have repeatedly found increases during the COVID-19 pandemic, acquisitive crimes in this city were reduced during the lockdown period for all categories, while "cyber-fraud" was found more resilient in the sense that its decrease was not as salient as for most other crime types, possibly due to people's use of the internet during the lockdown period.

CONCLUSIONS

The findings provide further support to opportunity theories of crime that are contingent upon the need for a motivated offender to identify a suitable target in physical space.

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

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.

Small area variation in crime effects of COVID-19 policies in England and Wales

Purpose

The aim of this study is to examine small area variation in crime trajectories during the COVID-19 pandemic in England and Wales. While we know how police-recorded crime responded to lockdown policies at the 'macro' level, less is known about the extent to which these trends were experienced uniformly at localized spatial scales.

Methods

Longitudinal k-means clustering is used to unpick local area variation in police notifiable offences across England and Wales. We describe the clusters identified in terms of their spatial patterning, opportunity structures and crime type profile.

Results

We find that in most small areas, crime remained fairly stable throughout the pandemic. Instead, a small number of meso-level areas contributed a disproportionately large amount to the macro-level trend. These were typically city centers with plentiful pre-pandemic crime opportunities, dominated by theft and shoplifting offences.

Conclusion

Findings offer support for opportunity theories of crime and for a mobility theory of crime during the pandemic. We explore potential implications for policy, theory and further research.

The U-shaped crime recovery during COVID-19: evidence from national crime rates in Mexico

The existing empirical evidence suggests a reduction in aggregate crime as a consequence of the COVID-19 lockdown. However, what happens when lockdown measures are relaxed? This paper considers how the COVID-19 pandemic affects crime rates throughout Mexico when the stay-at-home orders end. We use national crime data from Mexico's National Public Security System, which reports municipality-level rates on assault & battery, theft & property crime, fraud, drug crimes & extortion, and homicides. Our results show that the majority of crimes follow a U-shaped trend-when the lockdown ends-crimes rise back to pre-pandemic levels.

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

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.