Risk Terrain Modeling (RTM) analyzes illicit drug trafficking, sales and use. RTM diagnoses seller and buyer preferences for drug markets and forecasts alternative spots or emerging settings for displacement or expansion of this behavior.
RTM has been used in the United States to profile how the physical landscape affects drug dealing (of many kinds of drugs). Open-air dealing, in particular, is a complex endeavor between buyers and sellers who are frequently strangers or only loosely acquainted. Yet they must find a way to balance a competing set of demands: access and security. In the Chicago study, drug dealers and buyers took advantage of several features of the environment to establish ideal opportunities this transaction. Different types of drugs had different ideal settings, or markets, based on specific environmental qualities. These findings inform place-based policies and intervention strategies (including policing) aimed at disrupting drug markets.
RTM has also been used to analyze and intervene at drug use locations, to forecast overdose 'hot spots', and to preemptively deploy resources to these places that are in the greatest need of intervention. Some public health oriented interventions have been to strategically deploy Narcan to city officials or business owners working in certain areas -- to enable overdose treatments quickly, and save lives; to place more sharps containers in public spaces -- to minimize littering of used syringes and accidental exposures to residents, visitors and public employees; to locate 9-1-1 call boxes (e.g., emergency cell phones) -- to enable reporting of overdoses or other emergencies; and to optimize advertising and recruitment campaigns for drug treatment and supportive services.
Students at the University of Pennsylvania produced a spatial risk model of opioid overdose events for the City of Providence, Rhode Island by examining overdose locations in relation to environmental risk factors, community protective resources, and neighborhood characteristics to offer an assessment of areas in the city where local stakeholders can strategically allocate resources to achieve the greatest impact. The Providence Safe Stations program or the Providence Healthy Communities Office can use forecasted high-risk places for overdose as a site suitability analysis or to improve outreach and communication efforts.
...because drug dealers seek strategic locations and conditions were profit margins are maximized, the risk terrains depicting these places serve as excellent place-based forecasts.
In Bogota, policies and hotspot policing practices intended to suppress illicit drug markets have resulted in sale locations becoming more dispersed. This has made monitoring and intervention even more difficult for local authorities. But new efforts at monitoring the markets of three illicit substances (cocaine, marijuana and basuco) provides valuable insights for disrupting emerging trends. Escudero and Ramírez found *drug prices* to be closely tied to certain environmental variables. And, because drug dealers seek strategic locations and conditions were profit margins are maximized, the risk terrains depicting these places serve as excellent place-based forecasts. RTM also offers actionable intel for effectively disrupting the situational contexts of these settings.
The Ideas for Peace Foundation used RTM to study microtrafficking of drugs in 5 Colombian cities (PDF reports from the Colombian Ministry of Justice): Bogota, Pasto, Medellin, Cali and Barranquilla
Environmental features can influence drug sales and use behaviors, and aggravate risks of chronic drug markets at particular places. RTM can help to diagnose these environmental vulnerabilities and identify places that are most in need of resources and risk reduction strategies.
Crime reductions are important to police agencies and the communities they serve for many reasons. One reason is that less crime saves money.
The National Institutes of Health (NIH) estimated that preventing just 6 violent crimes could save local criminal justice systems $100,000 and free up more than 9 hours of a police officer's patrol time. Recent surveys show that 2/3 of gunshot victims are uninsured, yet the average nationwide cost of treating gunshot wounds in hospital is $21,000 per person. Just 10 fewer shootings could result in over $200,000 worth of hospital cost savings, and, of course, 10 lives possibly saved.
Risk Terrain Modeling (RTM) is crime analysis that helps answer where and why crime happens. It finds important spatial patterns in your data and then it uses this diagnosis to make accurate and actionable predictions. Policing with RTM makes every dollar spent on public safety more effective. It's smart policing.
RTM is one reason given for Atlantic City's crime drop last year. The Atlantic City Police Department (ACPD) fully implemented risk-based policing with RTM in 2017, and they succeeded in achieving month-to-month crime reductions and higher case clearance rates, all while improving community relations. They were credited with a 36% reduction in violent crimes by the end of the year. This represents a potential cost savings to the local criminal justice system of over $1.6 million.
The new article, "Predicting Dynamical Crime Distribution from Environmental and Social Influences", published in Frontiers in Applied Mathematics and Statistics finds that combining risk from exposure (past events) and vulnerability (environment) when modeling crime distribution can improve crime suppression and prevention efforts by providing more accurate forecasting of the most likely locations of criminal events.
As shown in the graphic below, Risk Terrain Modeling (RTM), as a measure of spatial vulnerability to crime, outperforms event-dependent methods (I.e. recent past exposures, such as hot spots or near repeats) as a predictive analytic. But, more importantly, a combined vulnerability-exposure measure outperforms both solo methods. By large margins. This would be expected according to the Theory of Risky Places.
All models tested in the Frontiers article perform better than random, with the composite model performing better than the RTM-only model and the event-dependence-only model, in that order. The RTM-only prediction is roughly 70% better than the event-dependent prediction (I.e., hot spot, near repeat). And the composite model prediction is more than 100% better than the event-dependent prediction.
One take-away for researchers is that it’s important to consider the impact of the physical environment and how it influences outcomes resulting from human interactions at places. Since at least 1997 Abbott has claimed that "no social fact makes any sense abstracted from its context in social space and time…" He is correct. And, as such, requires researchers to operationalize more than just "crime counts" or "hot spot maps" as variables (or co-variates) in their statistical models. For instance, when researchers in Little Rock, AR used RTM to develop an aggregate risk of crime measure that they analyzed alongside a concentrated disadvantage index value, they produced a model that explained 55% of variation in neighborhood violent crime rates. This is no small feat considering that Weisburd and Piquero have commented that most criminal justice research does not often explain variations in crime by more than 20%.
For practitioners, this reaffirms the call to go farther than merely mapping and then policing hot spots. Hot spots are just signs and symptoms of environments that are highly suitable for crime, but they offer very little insights for solutions to manage crime problems. RTM adds a spatial diagnosis. By combining Risk Terrain Modeling with hot spot analysis, you learn where to go and what to focus on when we get there. You add the why to the where. And as the research proves, interpreting crime vulnerabilities and exposures together makes the best forecasts, regardless of whether crimes persist, displace, or emerge at places where they have not happened before.
Bringing the vulnerability-exposure framework into professional practice ensure that you offer police (or other stakeholders) a unique opportunity to suppress crimes immediately by allocating resources to existing problem areas, and to initiate prevention strategies at the most vulnerable (high-risk) places within hot spots. This form of risk-based policing, whereby interventions are focused on the spatial attractors/generators of crime at priority places is discussed in detail (with lots of case studies) in this forthcoming book. Additional information and research evidence can be found at www.rtmworks.com.
So, in a nutshell: Risk Terrain Modeling is a best-practice that does not have to replace existing practices. It complements them to enhance crime analysis and to produce actionable intelligence for police commanders that want to be efficient and effective problem-solvers.