Showing papers in "Crime Science in 2021"

Six months in: pandemic crime trends in England and Wales

Abstract: Governments around the world have enforced strict guidelines on social interaction and mobility to control the spread of the COVID-19 virus. Evidence has begun to emerge which suggests that such dramatic changes in people’s routine activities have yielded similarly dramatic changes in criminal behavior. This study represents the first ‘look back’ on six months of the nationwide lockdown in England and Wales. Using open police-recorded crime trends, we provide a comparison between expected and observed crime rates for fourteen different offence categories between March and August, 2020. We find that most crime types experienced sharp, short-term declines during the first full month of lockdown. This was followed by a gradual resurgence as restrictions were relaxed. Major exceptions include anti-social behavior and drug crimes. Findings shed light on the opportunity structures for crime and the nuances of using police records to study crime during the pandemic.

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

Abstract: 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.

Crime and COVID-19: effect of changes in routine activities in Mexico City

Abstract: This study aimed to determine whether crime patterns in Mexico City changed due to the COVID-19 pandemic, and to test whether any changes observed were associated with the disruption of routine activities, as measured by changes in public transport passenger numbers. The first objective was assessed by comparing the observed incidence of crime after the COVID-19 pandemic was detected in the country with that expected based on ARIMA forecasts based on the pre-pandemic trends. The second objective was assessed by examining the association between crime incidence and the number of passengers on public transport using regressions with ARIMA errors. Results indicated that most crime categories decreased significantly after the pandemic was detected in the country or after a national lockdown was instituted. Furthermore, the study found that some of the declines observed were associated with the reductions seen in public transport passenger numbers. However, the findings suggested that the changes in mobility explain part of the declines observed, with important variations per crime type. The findings contribute to the global evaluation of the effects of COVID-19 on crime and propose a robust method to explicitly test whether the changes observed are associated with changes in routine activities.

Policing and public health calls for service in Philadelphia

Abstract: This contribution outlines various spatial and temporal aspects of medical or public-health related calls for service from the public to police in Philadelphia in 2019. These incidents comprise about 8% of the police department’s workload that originates from the public. Calls appear to be highly concentrated in a few areas, and specifically the Center City and Kensington neighborhoods. They are also more likely to occur late afternoon and evening. The article shows that some medical or public health activity initially masquerades as crime or other policing work and some events eventually determined to be police/crime activity can initially appear to be public health related. About 20% of activity in this area does not appear predictable from the initial call type as handled by police dispatch.

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

Abstract: 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.

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

Abstract: 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.

Functional and dysfunctional fear of COVID-19: a classification scheme

Abstract: Worry about COVID-19 is a central topic of research into the social and economic consequences of the COVID-19 pandemic. In this paper, we present a new way of measuring worry about catching COVID-19 that distinguishes between worry as a negative experience that damages people’s quality of life (dysfunctional) and worry as an adaptive experience that directs people’s attention to potential problems (functional). Drawing on work into fear of crime, our classification divides people into three groups: (1) the unworried, (2) the functionally worried (where worry motivates proactive behaviours that help people to manage their sense of risk) and (3) the dysfunctionally worried (where quality of life is damaged by worry and/or precautionary behaviour). Analysing data from two waves of a longitudinal panel study of over 1000 individuals living in ten cities in England, Scotland and Wales, we find differing levels of negative anxiety, anger, loneliness, unhappiness and life satisfaction for each of the three groups, with the dysfunctionally worried experiencing the most negative outcomes and the functionally worried experiencing less negative outcomes than unworried. We find no difference between groups in compliance and willingness to re-engage in social life. Finally, we show a difference between the dysfunctionally worried compared with functional and unworried groups in perceptions of risk (differentiating between likelihood, control and consequence). This finding informs what sort of content-targeted messaging aimed at reducing dysfunctional worry might wish to promote. We conclude with some thoughts on the applicability of our measurement scheme for future research.

Right place, right time? Making crime pattern theory time-specific

Abstract: Crime pattern theory and the related empirical research have remained rather a-temporal, as if the timing of routine activities and crime plays no role. Building on previous geography of crime research, we extend crime pattern theory and propose that an offender’s spatial knowledge acquired during daily routine activities is not equally applicable to all times of day. We put this extended theory to a first empirical test by applying a discrete spatial choice model to detailed information from the Netherlands on 71 offences committed by 30 offenders collected through a unique online survey instrument. The offenders reported on their most important activity nodes and offence locations over the past year, as well as the specific times they regularly visited these locations. The results show that almost 40% of the offences are committed within the neighbourhoods of offenders’ activity nodes, increasing to 85% when including first-, second- and third-order neighbourhoods. Though not statistically significant in our small sample, the results further suggest that offenders are more likely to commit crime in neighbourhoods they have regularly visited at the same time of day than in neighbourhoods they have regularly visited at different times of day. Our extension of crime pattern theory is only tentatively supported. We argue for replication research with larger samples before any firm conclusions are warranted.

The effect of the COVID-19 pandemic on mental health calls for police service.

Abstract: Drawing upon seven years of police calls for service data (2014-2020), this study examined the effect of the COVID-19 pandemic on calls involving persons with perceived mental illness (PwPMI) using a Bayesian Structural Time Series. The findings revealed that PwPMI calls did not increase immediately after the beginning of the pandemic in March 2020. Instead, a sustained increase in PwPMI calls was identified in August 2020 that later became statistically significant in October 2020. Ultimately, the analysis revealed a 22% increase in PwPMI calls during the COVID-19 pandemic than would have been expected had the pandemic not taken place. The delayed effect of the pandemic on such calls points to a need for policymakers to prioritize widely accessible mental health care that can be deployed early during public health emergencies thus potentially mitigating or eliminating the need for increased police intervention, as was the case here. Supplementary Information: The online version contains supplementary material available at 10.1186/s40163-021-00157-6.

The influence of changing reward of electronic consumer goods on burglary and theft offences in Western market-based countries in the years prior to and during the crime drop

Abstract: It is widely recognised that burglary and theft offence trends have broadly moved in parallel in ‘Western’ market-based countries since the 1950s. Most researchers have focussed on the trend from the early 1990s onwards, when burglary and theft offence rates plummeted. One major proposed explanation for this trend, relates to improved security. This paper draws on the longitudinal variations in reward of electronic consumer goods to propose a complementary account. This argument is supported by criminological theory, empirical evidence, and historical trends of specific property crime offences. The paper concludes by explaining that reward and security operate in partnership to influence the opportunity for crime, which provides an optimal account for burglary and theft offence trends over the last 40 years.

Systematic review of situational prevention methods for crime against species

Abstract: Illegal activities concerning terrestrial species (TS) are responsible for a variety of health, environmental, economic and security issues The majority of academic research associated with species relates to conservation, with few publications specifically investigating the scale of crimes impacting species or how they can be prevented This article systematically reviews the available evidence about what works to prevent crime against terrestrial species Of over 29,000 documents that were returned in the first stage of the review, these were filtered to just over 100 The remaining documents were partially or fully read to identify the most relevant documents to include in the final qualitative synthesis The review results show there is a significant lack of primary research in this area, as only five articles were found that met the study inclusion criteria The identified articles focus on the effects of two types of situational crime prevention interventions: community outreach and ranger patrol frequency Community outreach was shown to have a significant impact on local poaching levels, while for patrolling the evidence suggests a positive impact on the discovery of poachers, animal carcasses and poaching paraphernalia, however, the quality of these studies varied greatly To prevent the further decline of species numbers internationally, more effort should be invested in publicising existing research into the effectiveness of prevention strategies that have not reached the wider scientific audience, as well as the funding and promotion of research into alternate methods of crime prevention

The impact of the COVID-19, social distancing, and movement restrictions on crime in NSW, Australia.

Abstract: The spread of COVID-19 has prompted Governments around the world to impose draconian restrictions on business activity, public transport, and public freedom of movement. The effect of these restrictions appears to vary from country to country and, in some cases, from one area to another within a country. This paper examines the impact of the COVID-19 restrictions imposed in New South Wales (NSW) by the State Government. We examine week-to-week changes in 13 categories of crime (and four aggregated categories) from 2 January 2017 to 28 June 2020. Rather than using the pre-intervention data to make a forecast and then comparing that with what is actually observed, we use a Box–Jenkins (ARIMA) approach to model the entire time series. Our results are broadly in accord with those of other studies, but we find no effect of the lockdown (upward or downward) on domestic assault.

Identifying seasonal spatial patterns of crime in a small northern city

Abstract: To explore spatial patterns of crime in a small northern city, and assess the degree of similarity in these patterns across seasons. Calls for police service frequently associated with crime (theft, break and enter, domestic dispute, assault, and neighbor disputes) were acquired for a five year time span (2015–2019) for the city of North Bay, Ontario, Canada (population 50,396). Exploratory data analysis was conducted using descriptive statistics and a kernel density mapping technique. Andresen’s spatial point pattern test (SPPT) was then used to assess the degree of similarity between the seasonal patterns (spring, summer, autumn, winter) for each call type at two different spatial scales (dissemination area and census tract). Exploratory data analysis of crime concentration at street segments showed that calls are generally more dispersed through the city in the warmer seasons of spring and summer. Kernel density mapping also shows increases in the intensity of hotspots at these times, but little overall change in pattern. The SPPT does find some evidence for seasonal differences in crime pattern across the city as a whole, specifically for thefts and break and enters. These differences are focused on the downtown core, as well as the outlying rural areas of the city. For the various crime types examined, preliminary analysis, kernel density mapping, and the SPPT found differences in crime pattern consistent with the routine activities theory.

Illegal fishing and compliance management in marine protected areas: a situational approach

Abstract: Protected Areas (PAs) are spatially representative management tools that impose various levels of protection for conservation purposes. As spatially regulated places, ensuring compliance with the rules represents a key element of effective management and positive conservation outcomes. Wildlife crime, and in particular poaching, is a serious global problem that undermines the success of PAs. This study applies a socio-ecological approach to understanding the opportunity structure of illegal recreational fishing (poaching) in no-take zones in Australia’s Great Barrier Reef Marine Park. We use Boosted Regression Trees to predict the spatio-temporal distribution of poaching risk within no-take Marine National Park zones. The results show that five risk factors account for nearly three quarters (73.6%) of the relative importance for poaching in no-take zones and that temporally varying conditions influence risk across space. We discuss these findings through the theoretical lens of Environmental Criminology and suggest that law enforcement strategies focus on reducing the negative outcomes associated with poaching by limiting the opportunity of would-be offenders to undertake illegal activity.

The impact of strict measures as a result of the COVID-19 pandemic on the spatial pattern of the demand for police: case study Antwerp (Belgium).

Abstract: COVID-19 impacts the daily lives of millions of people. This radical change in our daily activities affected many aspects of life, but acted as well as a natural experiment for research into the spatial distribution of 911 calls. We analyse the impact of the COVID-19 measures on the spatial pattern of police interventions. Crime is not uniformly distributed across street segments, but how does COVID-19 affect these spatial patterns? To this end, Gini coefficients are calculated and a proportion differences spatial point pattern test is applied to compare the similarity of the patterns of incidents before, during, and after the first lockdown in Antwerp, Belgium. With only essential mobility being allowed, the emergency call pattern has not significantly changed before, during or after this lockdown, however, a qualitative shift in police officer's daily work may have had an effect on the daily operation of the Antwerp police force.

A victim-centred cost–benefit analysis of a stalking prevention programme

Abstract: Research suggests that stalking inflicts great psychological and financial costs on victims. Yet costs of victimisation are notoriously difficult to estimate and include as intangible costs in cost–benefit analysis. This study reports an innovative cost–benefit analysis that used focus groups with multi-agency teams to collect detailed data on operational resources used to manage stalking cases. This method is illustrated through the presentation of one case study. Best- and worst-case counterfactual scenarios were generated using the risk assessment scores and practitioner expertise. The findings suggest that intervening in high-risk stalking cases was cost-beneficial to the state in all the case studies we analysed (even if it incurs some institutional costs borne by the criminal justice system or health) and was often cost-beneficial to the victims too. We believe that this method might be useful in other fields where a victim- or client-centred approach is fundamental.

A note on the multiplicative fairness score in the NIJ recidivism forecasting challenge

Abstract: The 2021 NIJ recidivism forecasting challenge asks participants to construct predictive models of recidivism while balancing false positive rates across groups of Black and white individuals through a multiplicative fairness score. We investigate the performance of several models for forecasting 1-year recidivism and optimizing the NIJ multiplicative fairness metric. We consider standard linear and logistic regression, a penalized regression that optimizes a convex surrogate loss (that we show has an analytical solution), two post-processing techniques, linear regression with re-balanced data, a black-box general purpose optimizer applied directly to the NIJ metric and a gradient boosting machine learning approach. For the set of models investigated, we find that a simple heuristic of truncating scores at the decision threshold (thus predicting no recidivism across the data) yields as good or better NIJ fairness scores on held out data compared to other, more sophisticated approaches. We also find that when the cutoff is further away from the base rate of recidivism, as is the case in the competition where the base rate is 0.29 and the cutoff is 0.5, then simply optimizing the mean square error gives nearly optimal NIJ fairness metric solutions. The multiplicative metric in the 2021 NIJ recidivism forecasting competition encourages solutions that simply optimize MSE and/or use truncation, therefore yielding trivial solutions that forecast no one will recidivate.

Systematic review and meta-analysis of risk terrain modelling (RTM) as a spatial forecasting method

Abstract: Several studies have tested the reliability of Risk Terrain Modelling (RTM) by focusing on different geographical contexts and types of crime or events. However, to date, there has been no attempt to systematically review the evidence on whether RTM is effective at predicting areas at high risk of events. This paper reviews RTM’s efficacy as a spatial forecasting method. We conducted a systematic review and meta-analysis of the RTM literature. We aggregated the available data from a sample of studies that measure predictive accuracy and conducted a proportion meta-analysis on studies with appropriate data. In total, we found 25 studies meeting the inclusion criteria. The systematic review demonstrated that RTM has been successful in identifying at risk places for acquisitive crimes, violent crimes, child maltreatment, terrorism, drug related crimes and driving while intoxicated (DWI). The proportion meta-analysis indicated that almost half of future cases in the studies analysed were captured in the top ten per cent of risk cells. This typically covers a very small portion of the full study area. The study demonstrates that RTM is an effective forecasting method that can be applied to identify places at greatest risk of an event and can be a useful tool in guiding targeted responses to crime problems.

In the post-COVID-19 era, is the illegal wildlife trade the most serious form of trafficking?

Abstract: Despite the immense impact of wildlife trafficking, comparisons of the profits, costs, and seriousness of crime consistently rank wildlife trafficking lower relative to human trafficking, drug trafficking and weapons trafficking. Using the published literature and current events, we make the case, when properly viewed within the context of COVID-19 and other zoonotic diseases transmitted from wildlife, that wildlife trafficking is the most costly and perhaps the most serious form of trafficking. Our synthesis should raise awareness of the seriousness of wildlife trafficking for humans, thereby inducing strategic policy decisions that boost criminal justice initiatives and resources to combat wildlife trafficking.

More crime in cities? On the scaling laws of crime and the inadequacy of per capita rankings—a cross-country study

Abstract: Crime rates per capita are used virtually everywhere to rank and compare cities. However, their usage relies on a strong linear assumption that crime increases at the same pace as the number of people in a region. In this paper, we demonstrate that using per capita rates to rank cities can produce substantially different rankings from rankings adjusted for population size. We analyze the population–crime relationship in cities across 12 countries and assess the impact of per capita measurements on crime analyses, depending on the type of offense. In most countries, we find that theft increases superlinearly with population size, whereas burglary increases linearly. Our results reveal that per capita rankings can differ from population-adjusted rankings such that they disagree in approximately half of the top 10 most dangerous cities in the data analyzed here. Hence, we advise caution when using crime rates per capita to rank cities and recommend evaluating the linear plausibility before doing so.

The new normal of web camera theft on campus during COVID-19 and the impact of anti-theft signage.

Abstract: Objective: The opportunity for web camera theft increased globally as institutions of higher education transitioned to remote learning during COVID-19. Given the thousands of cameras currently installed in classrooms, many with little protection, the present study tests the effectiveness of anti-theft signage for preventing camera theft. Methods: Examined web camera theft at a southern, public university located in the United States of America by randomly assigning N = 104 classrooms to receive either anti-theft signage or no signage. Camera theft was analyzed using Blaker's exact test. Results: Classrooms not receiving anti-theft signage (control) were 3.42 times more likely to exhibit web camera theft than classrooms receiving anti-theft signage (medium effect size). Conclusions: Using classrooms as the unit of analysis presents new opportunities for not only future crime prevention experiments, but also improving campus safety and security. Also, preventing web camera theft on campus is both fiscally and socially responsible, saving money and ensuring inclusivity for remote learners.

The effect of GPS refresh rate on measuring police patrol in micro-places

Abstract: With the increasing prevalence of police interventions implemented in micro hot-spots of crime, the accuracy with which officer foot patrols can be measured is increasingly important for the robust evaluation of such strategies. However, it is currently unknown how the accuracy of GPS traces impact upon our understanding of where officers are at a given time and how this varies for different GPS refresh rates. Most existing studies that use GPS data fail to acknowledge this. This study uses GPS data from police officer radios and ground truth data to estimate how accurate GPS data are for different GPS refresh rates. The similarity of the assumed paths are quantitatively evaluated and the analysis shows that different refresh rates lead to diverging estimations of where officers have patrolled. These results have significant implications for the measurement of police patrols in micro-places and evaluations of micro-place based interventions.

Retraction Note to : Do offenders avoid offending near home? A systematic review of the buffer zone hypothesis (Crime Science, (2020), 9, 1, (8), 10.1186/s40163-020-00118-5)

Abstract: The authors have retracted this article (Bernasco & van Dijke, 2020). After publication, Professor Kim Rossmo reported that his own analysis of the data failed to replicate the published findings. Professor Rossmo claimed that 16 of the 33 publications analyzed did not meet the authors’ own inclusion criteria. The authors attempted to replicate their own findings by re-assessing the 33 publications. Based on the results, they concluded that Professor Rossmo’s concern was fully justified. Some publications were based on simulation rather than empirical analysis. Some publications did not provide information on the complete distribution of the home-crime distance. Some publications did not measure or did not report distances with sufficient precision. In sum, the findings of the article are not reliable. The authors apologize to the readers and the Editors of Crime Science for any problems caused by drawing conclusions not sufficiently supported by evidence, and they thank Professor Rossmo for bringing the issue to their attention. During all stages—submission, review procedure, and communications after publication—the authors and Professor Rossmo have provided complete access to data and to the methods used for selecting and assessing them. Both authors agree to the retraction.

Using crime script analysis to elucidate the details of Amur tiger poaching in the Russian Far East

Abstract: Poaching is the most direct threat to the persistence of Amur tigers. However, little empirical evidence exists about the modus operandi of the offenders associated with this wildlife crime. Crime science can aid conservation efforts by identifying the patterns and opportunity structures that facilitate poaching. By employing semi-structured interviews and participants observation with those directly involved in the poaching and trafficking of Amur tigers in the Russian Far East (RFE), this article utilizes crime script analysis to break down this criminal event into a process of sequential acts. By using this framework, it is possible account for the decisions made and actions taken by offenders before, during and after a tiger poaching event, with the goal of identifying weak points in the chain of actions to develop targeted intervention strategies. Findings indicate poaching is facilitated by the ability to acquire a firearm, presence of roads that enable access to remote forest regions, availability of specific types of tools/equipment, including heat vision googles or a spotlight and a 4 × 4 car, and a culture that fosters corruption. This crime script analysis elucidates possible intervention points, which are discussed alongside each step in the poaching process.

The impact of gunshots on place-level business activity

Abstract: Gun violence can negatively affect business activity at the place-level through a variety of mechanisms. However, estimating this effect is difficult since reported crime data are biased by factors that are also associated with business health. Despite some of its limitations, data from gunshot detection technology has been shown as a new valuable source of data on gun violence (Irvin-Erickson et al. in Appl Geogr 86: 262–273, 2017a). In this study, we use gunshot detection data to explore the spatial relationship between gunshots and business activity at the neighborhood level in Washington, DC between 2010 and 2012. In this exploratory study, we create spatial buffers of 500 and 1000 feet around each block and sum up the total number of gunshots and business births, deaths, sales, and number of employees within these buffers each year and estimate a spatial fixed effects panel model. Gunshots within 1000 feet of a block increase the number of business deaths by 4.3% within that buffer on average, and gunshots within 500 feet of a block decrease the total number of service and retail businesses, the number of employees employed by businesses within that buffer, and total sales for those businesses (although not at a statistically significant rate). Gunshots on blocks with the lowest initial levels of gunshots increase business turnover and reduce the total number of businesses present by 0.5%, and gunshots on blocks with the highest initial levels of gunshots cause an increase in the number of business deaths by 7.5%. Results suggest that efforts to improve distressed neighborhoods should target both areas with lower and higher pre-existing levels of gunshots.

Antiquities in a time of conflict: a crime script analysis of antiquities trafficking during the Syrian Civil War and implications for conflict antiquities

Abstract: The Syrian Civil War created an opportunity for increased trafficking of antiquities and has resulted in a renewed awareness on the part of a global audience. The persistence of criminal and organisational networks which facilitate antiquities trafficking networks (ATNs) has been recognised as significant, leading to increased interest in the development of new and improved methods of understanding such networks. While this field of research has traditionally been dominated by relevant areas such as archaeology, law, art and museum studies, there is a noticeable gap in crime prevention research. This paper presents a crime script of Syrian antiquities trafficking networks during the Syrian Civil War which has been generated from open source journalistic data. In creating a broad crime script for such a prevalent issue, this paper aims to demonstrate the need for further crime script analysis and specifically crime prevention research more generally within the study of antiquities trafficking.

Where should police forces target their residential burglary reduction efforts? Using official victimisation data to predict burglary incidences at the neighbourhood level

Abstract: Expected crime rates that enable police forces to contrast recorded and anticipated spatial patterns of crime victimisation offer a valuable tool in evaluating the under-reporting of crime and inform/guide crime reduction initiatives. Prior to this study, police forces had no access to expected burglary maps at the neighbourhood level covering all parts of England and Wales. Drawing on analysis of the Crime Survey for England and Wales and employing a population terrain modelling approach, this paper utilises household and area characteristics to predict the mean residential burglary incidences per 1000 population across all neighbourhoods in England and Wales. The analysis identifies distinct differences in recorded and expected neighbourhood burglary incidences at the Output Area level, providing a catalyst for stimulating further reflection by police officers and crime analysts.