How predictable are the locations of knife homicide in London? That question is difficult to answer based on professional experience, given the rarity of homicides in any specific location. As Mark Jackson of the Metropolitan Police Service (2010) discovered, only 12% (579) of all 4765 local census areas of London had any knife-enabled homicides over the 10 years from 2000 to 2010. Over 365 days from April 2017, our own study finds that only 1% of the 4835 local areas (2011 Census) had any of the locatable 97 knife-enabled (KE) homicides. Moreover, there were no local areas that had more than one such homicide, which means that there were no hot spots of repeated knife homicides that year (contra Sherman et al. 1989; Weisburd 2015).
There were, however, clearly identifiable hot spots of nonfatal KE assaults. It is these nonfatal knife crimes that provide a reliable, if far from perfect, basis for forecasting KE homicides over the time span of 1 year. Over two thirds (69%) of all KE homicides in 2017/2018 (which this study calls “year 2”) occurred in the 2048 local areas where one or more of the 3543 KE assaults were reported to have occurred in London in “year 1” (2016/2017). Interspersed between those hot spots, at the same time, were 2787 areas that had zero nonfatal KE assaults in 2016/2017 (year 1), and only 1% of those had a KE homicide in year 2.
Such rare events are difficult for any professional to forecast based on personal experience alone (Sutherland and Mueller-Johnson 2019). Even if police officers consult digitized crime records and maps, however, they would be misled by the failure of official statistics to count the precise behavior that kills: stabbing or cutting people with knives. Under current record-keeping systems, what the Office of National Statistics presents a wide array of crimes in which a knife was used: threats to kill, robbery, assaults without injury, etc. (ONS 2019). The only way to identify where victims of stabbing were stabbed nonfatally in England in 2019 is to read the full text of a narrative report, with no digital code available to indicate actual stabbings.
Yet it is the actual stabbing behavior that is critically important for the problem of KE homicide. Remarkably, the ratio of deaths per stabbing in London in 2016/2017 was 1 in 66 (see below), while in Chicago in 1965, it was almost identical at 1 in 55 (Zimring 1968). Given a large body of weapons crime research available in the USA (Wellford et al. 2005), our aim was to test the forecasting value of precisely counting the behavior most likely to cause death by knife.
Our objective in this article is to demonstrate whether comprehensive statistical analysis of where KE assaults have occurred in the recent past will help to forecast where KE homicides are most likely to occur in the near future. While we do not compare that forecasting method to the accuracy of forecasts based on qualitative intelligence, we note that there is presently no research evidence available on the accuracy of either method of forecasting murder. By testing the comprehensive data-driven approach over 2 years, we can at least set a benchmark of predictive accuracy for other methods to beat. We also hope to assess the value of a major investment in a rapid change of crime counting systems, in order to count, map, and analyze KE assaults separately and distinctly from all other knife crimes.
A Digital Policing Strategy
Such forecasts as we present here can become even more accurate if they are embedded into a digital policing strategy—one that uses ongoing data processing programs to update the city-wide homicide forecasts immediately upon new information being added to a forecasting model. Yet, we must recognize the substantial imitations of any forecasting of homicide risk by location. Even if we knew with 100% probability where homicides would happen in London during one of the 525,600 min a year, we would be greatly challenged to predict when they will occur across the possible targets of 525,600 min × 4835 local census areas, which is equal to 2.5 billion place minutes per year. On the other hand, if we define the challenge of evidence-based targeting as sending police to where they would be most likely to prevent homicide, a digital policing approach should offer great advantages over conventional policing. By using up-to-the-minute data on well-tested predictors, police commanders could move resources immediately to where they may produce the greatest benefits in saving lives. That challenge is especially salient with homicides committed by concealed weapons, notably knives and guns.
What predictors might work best? A digital policing strategy, in the not-too-distant future, could monitor London’s crime patterns in real time for daily forecasting of locations at the highest risk of a knife-enabled homicide. Many variables, from social media activity to the weather, could become part of a forecasting model, as discussed at a Ditchley Foundation conference chaired by Metropolitan Police Service (MPS) Commissioner Cressida Dick (Dick 2018). Yet, the entire concept of forecasting remains unfamiliar and often controversial, with frequent misunderstandings. Before a complex forecasting model is used to deploy police resources, police legitimacy would be well served by having a transparent, single-predictor basis for demonstrating the very great (and statistically predictable) differences in homicide risk levels from each local area to all others.
Counting Near-Miss Murders
The most fundamental starting point for predicting most kinds of rare events is near-misses of those events, in which the highest harm level almost occurs but does not actually happen. In air traffic safety, the near-miss concept implies that no harm occurs at all, as when two planes almost collide but do not. In policing, however, the relationship between fatal and nonfatal violence has long been understood to comprise a near-miss to a fatal injury. Using such near-misses to forecast homicide, based on long-term patterns of prior assaults (Mohler 2014), has been shown to provide substantial improvements over short-term-only analyses, especially by using most recent data in combination with longer-term patterns.
Testing Tactics in Targeted Hot Spots
Even daily updates of such forecasting, however, do not provide guidance on the particular police practices that should be employed in each high-risk location. Exactly what to do is, of course, a matter for testing, given reliable targeting of where to do it (Sherman 2013). Fortunately, in the case of weapon-enabled homicide, there is already a growing body of theory and evidence, albeit mostly from the USA. One theory dates to 1980, when two Harvard criminologists (Wilson 1980; Moore 1980) independently proposed that gun homicides could be reduced by focusing on widespread gun carrying by numerous gun carriers. The Harvard theory emerged shortly after the criminological perspective called routine activity theory (Cohen and Felson 1979), which itself built on the UK Home Office situational crime prevention literature (Mayhew et al. 1976), all of which stressed that opportunity is essential for committing a crime.
By focusing on concealed weapons as the proximate opportunity for committing most weapon-enabled homicides, the Harvard theorists suggested that police could deter decisions to carry weapons more readily than police could deter decisions to commit homicide. Wilson and Moore argued, in effect, that if illicit weapons are left at home for fear of arrest for illegal carrying, people inclined to use those weapons will have no opportunity to use them when encountering someone they might decide to attack. The deterrence of weapon carrying would thus block the opportunity to commit homicide, which would then reduce the frequency of homicide itself.
The evidence testing the Wilson-Moore theory has consistently supported its prediction. In a series of field tests in Kansas City (MO) (Sherman et al. 1995), Indianapolis (McGarrell et al. 2001), Pittsburgh (Cohen & Ludwig 2003), and St. Louis (Rosenfeld et al. 2014), police consistently found support for the target-the-carrying strategy causing a reduction in murders or weapons injuries [see also Bogota and Cali in Colombia (Villaveces et al. 2000)]. Shootings of guns, measured by either deaths, hospital treatment, or crime reports, went down in the test sites of all of these studies, relative to untreated high-shooting areas, when police targeted high-harm areas with proactive patrols and stop-search strategies. According to a systematic review of most of this work (Koper and Mayo-Wilson 2006), not one test failed to find evidence that criminal weapon usage declined when police targeted weapon carrying—in hot spot areas where weapon crime was concentrated. In each US case, this strategy began with careful analysis of where weapon-enabled homicides were most likely to occur, and concluded with intensive proactive policing of weapon carrying in those areas.
Do Near-Miss Injuries Predict Knife Homicide in London?
That proactive US strategy has been at the core of a long debate over stop and search in England and Wales. In general, however, the UK debate has neglected any discussion of two kinds of evidence. One is the evidence that stop-and-search works best when it is confined to a tiny fraction of a city where weapons crimes are most likely to occur. The US evidence showed success of using stop and search, but not just anywhere. It is all tested on precisely targeted crime hot spots, as distinct from an undifferentiated use of that tactic across any and all locations. The other evidence missing in the UK debate has been research on whether geographic concentrations of weapon-enabled homicides even exist in the UK—a crucial premise for a policy of limiting the most intrusive policing to that tiny fraction of any city in which a risk of weapon-enabled homicide is highest.
This article contributes to that second area of evidence missing from the UK debate. It is only a first, but crucial, step towards a more refined digital policing strategy for preventing homicide. This step provides what appears to be the first UK test of the hypothesis that any form of homicide can be predicted in micro-areas on the basis of prior near-misses, or nonfatal assaults using the same weapon as the fatal assaults. By using 4835 small census areas across London to pinpoint where knife carrying most commonly leads to nonfatal woundings, the article assesses whether the locations of those KE woundings can provide more accurate forecasts of future KE homicide locations.
Targeting Lower Layer Super Output Areas
In adopting this approach, this study builds upon the work of Metropolitan Police Service Detective Superintendent Mark Jackson (2010), whose Cambridge M.St. thesis first analyzed London’s homicide distribution within relatively small locations called Lower Layer Super Output Areas (LSOAs). These areas, like US Census tracts, are defined by the decennial UK Census of the Office of National Statistics. These geographical areas, in London in 2011, were home to an average of 1722 people each (based on the last census) and may be as small as 200 metres square. Nationally, each LSOA had 400 to 1200 households (Office of National Statistics 2011, 2019).
What Jackson (2010) showed with these areas was not just the concentration of knife-enabled homicide in a small number of these areas (with 88% of LSOAs across London free from any knife homicides over 10 years). He also showed that these “homicide hotspots” are themselves geographically very small. That size means that, in theory, KE homicide can be more effectively prevented by concentrating police resources at higher levels of blue uniforms or police cars per square foot (Sherman 2013).
While the MPS in 2019 is reorganizing 32 separately run operational command units (OCUs) into only 12, far larger, basic command units (BCUs), it becomes even more important for BCU commanders to have micro-level data on each LSOA. Jackson’s (2010) discovery that only 6% of LSOAs accounted for 42% of all homicides over 10 years showed the serious limitation of using large areas as operational units of analysis. Most parts of the 32 large OCUs had no homicide at all for a decade. Targeting at the LSOA level, however, revealed patterns of homicides recurring in many LSOAs year after year.
The purpose of such analysis is not a passive prediction of future homicide trends. Rather, our aim is to show how useful it would be for digital policing to produce regularly updated maps of locations where homicide is most likely to occur in the near future. This should, in principle, enable police leaders to target, and even test, more efficient and effective measures to prevent homicides with digital policing forecasts.