Targeting the Most Harmful Offenders for an English Police Agency: Continuity and Change of Membership in the “Felonious Few”

Funder: University of CambridgeAbstract Research Question How concentrated is the total harm of offences with detected offenders (identified suspects) among the complete list of all detected offenders in a given year in an English police agency, and how consistent is the list of highest-harm “felonious few” offenders from one year to the next? Data Characteristics of 327,566 crimes and 39,545 unique offenders as recorded by Northamptonshire Police in 7 years from 2010 to 2016 provide the basis for this analysis. Methods Crime and offender records were matched to harm weightings derived from the Cambridge Crime Harm Index (Sherman et al. 2016a; Sherman et al., Policing, 10(3), 171–183, 2016b). Descriptive statistics summarize a concentration of harm identifying the felonious few, changes over time in membership of the “few”, offender typologies and tests for escalation of severity, frequency and intermittency across repeated offences. Findings Crime harm is much more concentrated among offenders than crime volume: 80% of crime harm that is identified to an offender is linked to a felonious few of just 7% of all detected offenders. While chronic repeat offenders are the majority contributors to harm totals of this group, those with the most general range of offence types contribute the most harm. Individual members of the felonious few rarely maintain that position year on year; over 95% of each year’s list is composed of individuals not present in previous years. Within individual crime histories, we observe a pattern of de-escalation in crime harm per offence over time. “One-time” offenders, those with just one crime record, typically made up a third of the felonious few in both number and harm contribution. Conclusions These findings demonstrate the potential to target a small number of repeat offenders for harm reduction strategies using a metric of total crime severity, not just volume, despite a substantial portion of crime harm caused by one-time offenders that may be largely unpredictable. </jats:sec

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Detecting spatial movement of intra-region crime patterns over time

Many of the traditional measures of the degree to which crime patterns change over space and time have limitations. In particular most are unable to determine any change in spatial crime pattern within an areal unit. Usually studies measure the change in crime levels in contiguous areas (expressed as discrete sub-divisions of a study area), but this can become problematic due to difficulties such as the Modifiable Areal Unit Problem (MAUP). This paper describes a technique developed to allow researchers to examine intra-study region changes in crime patterns between two time periods without the need to aggregate crime counts to within-city areal boundaries. The method presented uses a random point nearest neighbor test combined with a Monte Carlo simulation. The process resolves problems of patterning and the MAUP that are common with a number of spatial displacement and pattern movement studies. This technique is demonstrated with example data from a city-wide police burglary crackdown in the Australian capital. KEY WORDS: displacement; police crackdown; nearest neighbor; MAUP; point pattern change; Australia

A temporal constraint theory to explain opportunity-based spatial offending patterns

hosted a

Research Article Aoristic analysis: the spatial interpretation of unspeci � c temporal events

Abstract. Temporal limitations of GIS databases are never more apparent than when the time of a change to any spatial object is unknown. This paper examines an unusual type of spatiotemporal imprecision where an event occurs at a known location but at an unknown time. Aoristic analysis can provide a temporal weight and give an indication of the probability that the event occurred within a de � ned period. Visualisation of temporal weights can be enhanced by modi � cations to existing surface generation algorithms and a temporal intensity surface can be created. An example from burglaries in Central Nottingham (UK) shows that aoristic analysis can smooth irregularities arising from poor database interrogation, and provide an alternative conceptualisation of space and time that is both comprehensible and meaningful. 1