Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test

Kalantari, Minoo; Yaghmaei, Bamshad; Ghezelbash, Somaye

doi:10.1080/13658816.2016.1174867

Cited by 13 publications

(5 citation statements)

References 41 publications

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“…Based on the intensity and the distance distribution of the events, K function can detect if the point patterns are completely random, clustered, or regular (inhibition between events). Point pattern analysis using K function has been widely used in statistics and geography and has gained increasing use in criminology in recent years [e.g., 63 – 65 ]. One specific feature of K function analysis that has been relatively neglected or underreported in previous studies is the scale of clusters, which can be used to guide the determination of scale for crime studies.…”

Section: Methodsmentioning

confidence: 99%

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

2022

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A key issue in the spatial and temporal analysis of residential burglary is the choice of scale: spatial patterns might differ appreciably for different time periods and vary across geographic units of analysis. Based on point pattern analysis of burglary incidents in Columbus, Ohio during a 9-year period, this study develops an empirical framework to identify a useful spatial scale and its dependence on temporal aggregation. Our analysis reveals that residential burglary in Columbus clusters at a characteristic scale of 2.2 km. An ANOVA test shows no significant impact of temporal aggregation on spatial scale of clustering. This study demonstrates the value of point pattern analysis in identifying a scale for the analysis of crime patterns. Furthermore, the characteristic scale of clustering determined using our method has great potential applications: (1) it can reflect the spatial environment of criminogenic processes and thus be used to define the spatial boundary for place-based policing; (2) it can serve as a candidate for the bandwidth (search radius) for hot spot policing; (3) its independence of temporal aggregation implies that police officials need not be concerned about the shifting sizes of risk-areas depending on the time of the year.

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Section: Methodsmentioning

confidence: 99%

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

2022

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“…It is important to note that this particular spatial bandwidth is larger than what has been used in many previous repeat/near repeat studies on the communicability of burglary risk, but was also in line with these same studies in terms of using average block distance. Various sensitivity tests including ANN and Ripley's K function were also used to help identify an appropriate spatial bandwidth for the repeat and near repeat analysis with results suggesting a 1000 m bandwidth to test potential within block spillover was most appropriate [36,37]. Given the physical layout of the Chaoyang district, the distance between events was calculated using Manhattan distance, as opposed to Euclidean distance or "as the crow flies".…”

Section: Methodsmentioning

confidence: 99%

The Impact of “Strike Hard” on Repeat and Near-Repeat Residential Burglary in Beijing

Chen

Kurland

2020

IJGI

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“Strike Hard” is an enhanced law-enforcement strategy in China that aims to suppress crime, but measurement of the crime-reducing effect and potential changes in the spatiotemporal concentration of crime associated with “Strike Hard” remain unknown. This paper seeks to examine the impact, if any, of “Strike Hard” on the spatiotemporal clustering of burglary incidents. Two and half years of residential burglary incidents from Chaoyang, Beijing are used to examine repeat and near-repeat burglary incidents before, during, and after the “Strike Hard” intervention and a new technique that enables the comparison of repeat and near repeat patterns across different temporal periods is introduced to achieve this. The results demonstrate the intervention disrupted the repeat pattern during the “Strike Hard” period reducing the observed ratio of single-day repeat burglaries by 155%; however, these same single-day repeat burglary events increased by 41% after the cessation of the intervention. Findings with respect to near repeats are less remarkable with nominal evidence to support that the intervention produced a significant decrease, but coupled with other results, suggest that spatiotemporal displacement may have been an undesired by-product of “Strike Hard”. This study from a non-Western setting provides further evidence of the generalizability of findings related to repeat and near repeat patterns of burglary and further highlights the limited preventative effect that the “Strike Hard” enhanced law enforcement campaign had on burglary.

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“…The Knox test ( 16) is a method that is used frequently to detect this kind of interaction. It has been used in many areas, such as criminology (17), medical and public health (18), and epidemiology (19)(20)(21)(22). Its basic principle and form are as follows: the null hypothesis of the Knox method is that the occurrence of diseases is spatial-temporal clustering.…”

Section: Knox Testmentioning

confidence: 99%

Spatial-temporal clustering of an outbreak of SARS-CoV-2 Delta VOC in Guangzhou, China in 2021

Zhang

et al. 2022

Front. Public Health

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BackgroundIn May 2021, the SARS-CoV-2 Delta variant led to the first local outbreak in China in Guangzhou City. We explored the epidemiological characteristics and spatial-temporal clustering of this outbreak.MethodsBased on the 153 cases in the SARS-CoV-2 Delta variant outbreak, the Knox test was used to analyze the spatial-temporal clustering of the outbreak. We further explored the spatial-temporal clustering by gender and age groups, as well as compared the changes of clustering strength (S) value between the two outbreaks in Guangzhou.ResultsThe result of the Knox analysis showed that the areas at short distances and brief periods presented a relatively high risk. The strength of clustering of male-male pairs was higher. Age groups showed that clustering was concentrated in cases aged ≤ 18 years matched to 18–59 years and cases aged 60+ years. The strength of clustering of the outbreak declined after the implementation of public health measures. The change of strength of clustering at time intervals of 1–5 days decreased greater in 2021 (S = 129.19, change rate 38.87%) than that in 2020 (S = 83.81, change rate 30.02%).ConclusionsThe outbreak of SARS-CoV-2 Delta VOC in Guangzhou has obvious spatial-temporal clustering. The timely intervention measures are essential role to contain this outbreak of high transmission.

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Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test

Cited by 13 publications

References 41 publications

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

The Impact of “Strike Hard” on Repeat and Near-Repeat Residential Burglary in Beijing

Spatial-temporal clustering of an outbreak of SARS-CoV-2 Delta VOC in Guangzhou, China in 2021

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