Knowledge of high-risk places can improve officer safety in the line-of-duty when incorporated into dispatch and calls-for-service (CFS) response procedures.
Assessment and management of risk are operational imperatives for police officers. Although the goal of many police agencies has been to be the ever-present “capable guardians,” a police officer’s presence can also become a new target of aggression and violence, making the police officer the potential victim.
Officers assess their risk of physical injury in every call for service. They are beholden to deal with criminal behaviors and hazardous situations for others while simultaneously mitigating their own potential for harm. To that specific end, police responses to CFS must be careful – given the known facts and conditions of the situation and location. In such a scenario, assessment of spatial risks is critical.
Risk terrain modeling (RTM) analysis identifies features of the landscape that create potentially dangerous settings and situational contexts. Intel from RTM allows officers to more adequately prepare for CFS and respond accordingly to any address (relative to all others) throughout their jurisdiction.
Adequate preparedness for CFS at high-risk places does not require more aggressive stances due to heightened awareness; but rather, could include policies that afford smarter dispatch protocols and tactical deployments of resources to reduce the likelihood of violence and injury for everyone involved. For instance, a trespassing call originating in a high-risk location for shootings could be similarly as dangerous as a report of a robbery-in-progress at a location that's low-risk for shootings.
Research published in the international journal Policing demonstrated how RTM articulates high-risk places for assaults against police officers. Notably, incidents of assault with a firearm (N=76) and assault resulting in serious injury (N=26) did not cluster. This means that assaults and related injuries to police officers occurred time-and-again at what appeared to be random locations. The question answered with RTM was: “do these incidents share common spatial features of the landscape where they occur?” Yes, they did. In fact, some micro-level places had over 70% greater likelihood of injuries to police officers compared to other areas.
A policy brief published by the Rutgers Center on Public Security examines spatial and situational risk factors for various types of felonious assault and mortality to police officers. It demonstrates how spatial factors diagnosed by RTM could be made actionable through risk narratives that offer a better level of situational awareness at call for service settings. For example, arterial and collector roadways, absence of median dividers, and covered roadways are spatial factors that increase the risk of violent assaults to officers during traffic stops. Spatial risk factors for injury during foot pursuit include nearby large unlocked buildings, abandoned lots, uneven terrain, tall brush, residential yards, walls, fences, swimming pools, clotheslines (backyards), sharp turns, and wide open spaces.
To mitigate risk, spatial intel from RTM can be used tactically to allocate resources or direct operations when responding to CFS at the highest-risk places within a jurisdiction. Here’s how that could happen:
For example, a normally ‘low-risk’ call type such as “trespassing” that has a response address located in a high-risk area gets the protocol applied (e.g., perhaps two officers are automatically dispatched instead of one; maybe they coordinate their response directions en route to gain multiple visual perspectives upon arrival).
Knowledge about risky places can be used by police and communications professionals to assess and manage personal injury risks at micro places throughout a patrol area. Real-time assessments within a jurisdiction can be routinely made on a call-by-call basis, thereby assessing relative risks to optimize resources and reduce ‘alert fatigue’. In this way, RTM can help police officers better anticipate their risk terrains and respond accordingly to improve personal safety. It also empowers dispatchers with new insights to help them direct safer encounters between police and the constituents they serve.
Associate Attorney General Vanita Gupta gave an impassioned shout-out to Rutgers University and the Newark Public Safety Collaborative (NPSC) during opening remarks of the U.S. Department of Justice OJP ‘Community Violence Intervention & Prevention Initiative’ national conference in St. Louis.
Watch the clip (at 32:45 - 33:30 minutes) and the entire opening ceremony via https://www.justice.gov/opa/video/community-violence-intervention-prevention-initiative-grantee-convening-opening-ceremony
Last year, our Bureau of Justice Assistance funded a new effort called "Reimagining Justice," a phrase that captures exactly what we're trying to achieve. Through a grant to the Newark Public Safety Collaborative, based out of Rutgers University, we are supporting an effort to test new community safety strategies that complement traditional enforcement measures. The mission is to put data and research into the hands of community stakeholders so they can be part of the design and development of community safety solutions.
The "Enhancing Procedural-Justness of Encounters Through Substantiation" (EPJETS) project, funded by NIJ and led by Dr. Nusret Sahin at Stockton University, focuses on improving police-community relations by increasing transparency and accountability during traffic stops.
To achieve this goal, EPJETS incorporates risk terrain modeling (RTM) to identify and map local areas of a community that are at high risk for traffic crashes and related injuries. This directs resources and informs conversations during police-community interactions.
This use of RTM is another example of data-informed community engagement (DICE), whereby data analytics steer community-focused programs and create more effective and equitable public safety. It improves procedural justice.
By engaging with people in the community and setting expectations based on local problems and related data sharing, police can build trust and strengthen community relations while also enforcing the law.