A Stab in the Dark?

Tompson, Lisa; Bowers, Kate

doi:10.1177/0022427812469114

Cited by 54 publications

(16 citation statements)

References 29 publications

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“…Crime patterns vary by place and can fluctuate over short time periods. Studies on the temporal patterns of crime have focused on seasonal patterns such as time of year, day of week, holidays, and hours of darkness [1][2][3]. Event generated perturbations in crime patterns have been less studied.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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This paper uses resilience as a lens through which to analyse disasters and other major threats to patterns of criminal behaviour. A set of indicators and mathematical models are introduced that aim to quantitatively describe changes in crime levels in comparison to what could otherwise be expected, and what might be expected by way of adaptation and subsequent resumption of those patterns. The validity of the proposed resilience assessment tool is demonstrated using commercial theft data from the COVID-19 pandemic period. A 64 per cent reduction in crime was found in the studied city (China) during an 83-day period, before daily crime levels bounced back to higher than expected values. The proposed resilience indicators are recommended as benchmarking instruments for evaluating and comparing the global impact of COVID-19 policies on crime and public safety.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…10 11 Some studies suggest that the incidence of violence can be influenced by temporal factors that seem to affect people in different circumstances, spaces and times. [12][13][14] It is important to identify factors playing a significant role in the timing of violence for specific populations, in order to anticipate the occurrence of violence and guide prevention strategies.…”

Section: Introductionmentioning

confidence: 99%

The relationship between pay day and violent death in Guatemala: a time series analysis

et al. 2016

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Objective To assess if violent deaths were associated with pay days in Guatemala. Design Interrupted time series analysis. Setting Guatemalan national autopsy databases. Participants Daily violence-related autopsy data for 22 418 decedents from 2009 to 2012. Data were provided by the Guatemalan National Institute of Forensic Sciences. Multiple pay-day lags and other important days such as holidays were tested. Outcome measures Absolute and relative estimates of excess violent deaths on pay days and holidays. Results The occurrence of violent deaths was not associated with pay days. However, a significant association was observed for national holidays, and this association was more pronounced when national holidays and pay days occurred simultaneously. This effect was observed mainly in males, who constituted the vast majority of violent deaths in Guatemala. An estimated 112 (coefficient=3.12; 95% CI 2.15 to 4.08; p<0.01) more male violent deaths occurred on holidays than were expected. An estimated 121 (coefficient=4.64; 95% CI 3.41 to 5.88; p<0.01) more male violent deaths than expected occurred on holidays that coincided with the first 2 days following a pay day. Conclusions Men in Guatemala experience violent deaths at an elevated rate when pay days coincide with national holidays. Efforts to be better prepared for violence during national holidays and to prevent violent deaths by rescheduling pay days when these days co-occur with national holidays should be considered.

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“…To model the temporal regularity of crime, most approaches in the literature use time-series analysis and its various tools such as spectral analysis [33][34][35][36][37] , spatial correlation 38 , regression analysis [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57] , cross correlation 58 , and spatial point pattern tests [59][60][61] . These approaches assume a temporal regularity of crime activity limited within fixed regional localities.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal variations in the urban rhythm: the travelling waves of crime

Oliveira¹,

Ribeiro²,

Bastos-Filho³

et al. 2018

EPJ Data Sci.

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In the last decades, the notion that cities are in a state of equilibrium with a centralised organisation has given place to the viewpoint of cities in disequilibrium and organised from bottom to up. In this perspective, cities are evolving systems that exhibit emergent phenomena built from local decisions. While urban evolution promotes the emergence of positive social phenomena such as the formation of innovation hubs and the increase in cultural diversity, it also yields negative phenomena such as increases in criminal activity. Yet, we are still far from understanding the driving mechanisms of these phenomena. In particular, approaches to analyse urban phenomena are limited in scope by neglecting both temporal non-stationarity and spatial heterogeneity. In the case of criminal activity, we know for more than one century that crime peaks during specific times of the year, but the literature still fails to characterise the mobility of crime. Here we develop an approach to describe the spatial, temporal, and periodic variations in urban quantities. With crime data from 12 cities, we characterise how the periodicity of crime varies spatially across the city over time. We confirm one-year criminal cycles and show that this periodicity occurs unevenly across the city. These 'waves of crime' keep travelling across the city: while cities have a stable number of regions with a circannual period, the regions exhibit non-stationary series. Our findings support the concept of cities in a constant change, influencing urban phenomena-in agreement with the notion of cities not in equilibrium. 4/11

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A Stab in the Dark?

Cited by 54 publications

References 29 publications

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

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

The relationship between pay day and violent death in Guatemala: a time series analysis

Spatio-temporal variations in the urban rhythm: the travelling waves of crime

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