A Socioeconomic Edge Effect: Rational Crime in Small Areas of Sharp Socioeconomic Contrast

2020 ◽  
pp. 002242782094500
Author(s):  
Robert Drew Heinzeroth
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Economic Incentive ◽  
Future Research ◽  
Census Block ◽  
Pattern Theory ◽  
Crime Pattern Theory ◽  
Dependent Variables ◽  
Block Groups ◽  
Crime Pattern

Objectives: To determine whether criminogenic “edges,” as defined by crime pattern theory, exist at points of sharp contrast of socioeconomic status (SES). Methods: The study uses a quasi-experimental design with pattern matching logic. A series of negative binomial regression models separately examine five different crimes with an economic incentive as dependent variables, and five crimes without an economic incentive as nonequivalent dependent variables, to determine whether census block groups of predominantly and comparatively higher SES than the wider surrounding area experience greater reported rational crime than would otherwise be expected. Results: The census block groups of comparatively higher SES located within and/or near areas of predominantly lower SES experienced one of the five crimes with an economic incentive, robberies by firearm, 40 percent more frequently than would otherwise be expected. Conclusions: The study’s findings are partially consistent with its hypothesis, which is grounded in crime pattern, rational choice, routine activities, and social disorganization theories. The findings encourage future research that may extend the definition of an “edge” under crime pattern theory as well as research at the intersection of criminological theories.

scholarly journals Block-Level Analysis of the Attractors of Robbery in a Downtown Area

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402096367
Author(s):  
Kingsley U. Ejiogu
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Geographic Mobility ◽  
Negative Binomial Regression Model ◽  
American Time Use Survey ◽  
Pattern Theory ◽  
Crime Pattern Theory ◽  
Time Use Survey ◽  
Block Level ◽  
Street Robbery

This article examines the predictions of crime pattern theory in a unique neighborhood type. It tested potential crime attracting facilities against street robbery data from 2009 to 2013 in the Police Districts I & II in Downtown Houston. The analysis modeled the four daily human routine periods described in the American Time Use Survey (ATUS). Generalized linear simultaneous negative binomial regression model was used to determine the size of the influence of the variables (beta coefficients) and their significance for each model outcome. The findings show some distinct patterns of street robbery due to the immediate and lagged effects of the variables relatable to the study environment’s unique setting. Two variables, geographic mobility, and barbershops were particularly significant across three of the outcome models. The results suggest that the physical and social structure of neighborhoods determined by land-use regulations would enhance understanding of the time-based influence on robbery patterns due to crime-attracting facilities.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association Between Federal Value-Based Incentive Program Implementation and Hospital-Onset C. difficile Infection Rates

2020 ◽  
Vol 41 (S1) ◽  
pp. s133-s133
Author(s):  
Mohammad Alrawashdeh ◽  
Chanu Rhee ◽  
Heather Hsu ◽  
Grace Lee
Keyword(s):  
Program Implementation ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Neutralization Assay ◽  
Nucleic Acid Amplification ◽  
Teaching Hospitals ◽  
Future Research ◽  
Testing Methods ◽  
Toxigenic Culture ◽  
The Impact

Background: The Hospital-Acquired Conditions Reduction Program (HACRP) and Hospital Value-Based Purchasing (HVBP) are federal value-based incentive programs that financially reward or penalize hospitals based on quality metrics. Hospital-onset C. difficile infection (HO-CDI) rates reported to the CDC NHSN became a target quality metric for both HACRP and HVBP in October 2016, but the impact of these programs on HO-CDI rates is unknown. Methods: We used an interrupted time-series design to examine the association between HACRP/HVBP implementation in October 2016 and quarterly rates of HO-CDI per 10,000 patient days among incentive-eligible acute-care hospitals conducting facility-wide HO-CDI NHSN surveillance between January 2013 and March 2019. Generalized estimating equations were used to fit negative binomial regression models to assess for immediate program impact (ie, level change) and changes in the slope of HO-CDI rates, controlling for each hospital’s predominant method for CDI testing (nucleic acid amplification including PCR (NAAT), enzyme immunoassay for toxin (EIA), or other testing method including cell cytotoxicity neutralization assay and toxigenic culture). Results: Of the 265 study hospitals studied, most were medium-sized (100–399 beds, 55%), not-for-profit (77%), teaching hospitals (70%), and were located in a metropolitan area (87%). Compared to EIA, rates of HO-CDI were higher when detected by NAAT (incidence rate ratio [IRR], 1.55; 95% CI, 1.41–1.70) or other testing methods (IRR, 1.47; 95% CI, 1.26–1.71). Controlling for CDI testing methods, HACRP/HVBP implementation was associated with an immediate 6% decline in HO-CDI rates (IRR, 0.94; 95% CI, 0.89–0.99) and a 4% decline in slope per year-quarter thereafter (IRR, 0.96; 95% CI, 0.95–0.97) (Fig. 1). Conclusions: HACRP/HVBP implementation was associated with both immediate and gradual improvements in HO-CDI rates, independent of CDI testing methods of differing sensitivity. Future research may evaluate the precise mechanisms underlying this improvement and if this impact is sustained in the long term.Funding: NoneDisclosures: None

Personalized crime location prediction

2016 ◽  
Vol 27 (3) ◽  
pp. 422-450 ◽  
Author(s):  
MOHAMMAD A. TAYEBI ◽  
UWE GLÄSSER ◽  
MARTIN ESTER ◽  
PATRICIA L. BRANTINGHAM
Keyword(s):  
Law Enforcement ◽  
Urban Crime ◽  
Crime Analysis ◽  
Urban Landscapes ◽  
Location Prediction ◽  
Prevention Strategies ◽  
Pattern Theory ◽  
Activity Spaces ◽  
Crime Pattern Theory ◽  
Crime Pattern

Crime reduction and prevention strategies are vital for policymakers and law enforcement to face inevitable increases in urban crime rates as a side effect of the projected growth of urban population by the year 2030. Studies conclude that crime does not occur uniformly across urban landscapes but concentrates in certain areas. This phenomenon has drawn attention to spatial crime analysis, primarily focusing on crime hotspots, areas with disproportionally higher crime density. In this paper, we present CrimeTracer1, a personalized random walk-based approach to spatial crime analysis and crime location prediction outside of hotspots. We propose a probabilistic model of spatial behaviour of known offenders within their activity spaces. Crime Pattern Theory concludes that offenders, rather than venture into unknown territory, frequently select targets in or near places they are most familiar with as part of their activity space. Our experiments on a large real-world crime dataset show that CrimeTracer outperforms all other methods used for location recommendation we evaluate here.

Geoprofiling Terrorism

2018 ◽  
Author(s):  
Kim Rossmo
Keyword(s):  
Spatial Relationship ◽  
Environmental Criminology ◽  
Improvised Explosive Devices ◽  
Geographic Profiling ◽  
Pattern Theory ◽  
Crime Pattern Theory ◽  
Improvised Explosive ◽  
Explosive Devices ◽  
Crime Pattern

A number of recent research projects have explored applications of geographic profiling to counterterrorism and counterinsurgency. These efforts analyzed geospatial patterns of terrorist cells (e.g., the spatial relationship between safe houses and weapon storage sites), tested the ability of these techniques to locate terrorist bases from minor crimes and seditious graffiti, and examined the utility of geoprofiling for locating preparation sites used by insurgents for improvised explosive devices and rocket attacks. In appropriate cases, geoprofiling models have utility for prioritizing geo-intelligence and identifying logistic bases of terrorist operations. This chapter first discusses environmental criminology and the geography of crime. It then covers the basics of geographic profiling, its various applications, and the role of geospatial intelligence and crime pattern theory in counterterrorism. Finally, it examines the geospatial and temporal patterns of terrorism to show how geoprofiling can be used to analyze seditious graffiti, insurgency attacks, cyberterrorism, and bioterrorism.

Does Future Orientation Moderate the Relationship Between Impulse Control and Offending? Insights From a Sample of Serious Young Offenders

2019 ◽  
Vol 18 (2) ◽  
pp. 156-178 ◽  
Author(s):  
Damon M. Petrich ◽  
Christopher J. Sullivan
Keyword(s):  
Impulse Control ◽  
Negative Binomial ◽  
Future Orientation ◽  
Negative Binomial Regression ◽  
Self Control ◽  
Future Research ◽  
Young Offenders ◽  
Behavioral Strategies ◽  
Pathways To Desistance ◽  
The Relationship

Researchers have recently begun to examine motivational factors as moderators of the relationship between self-control and offending behavior. The current study extends prior work by investigating whether three aspects of future orientation (aspirations, expectations, and the use of future-oriented cognitive and behavioral strategies) play such a role. Drawing on 7 years of data from the Pathways to Desistance study ( N = 1,333), we use hybrid effects negative binomial regression models to assess how within-individual changes in future orientation and impulse control are independently and jointly related to the offending variety of serious young offenders. Although impulse control and three components of future orientation had significant main effects on offending, no interaction between these components emerged in our results. Implications for future research are discussed.

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