OnPolicing Blog

As mass casualty attacks proliferate, new model to prevent them emerges

June 16, 2017

John Cohen

Professor John D. Cohen

Rutgers University

John Cohen

Professor John D. Cohen

Rutgers University

On June 14, a lone gunman open fired on a group of Congressmen practicing for an upcoming softball game, wounding six, one critically. The shooter was stopped when two Capitol Hill Police Officers engaged the gunman, killing him.

That same day, a disgruntled employee open fired on co-workers at a San Francisco UPS facility killing three and wounding two other people.

As a nation we are experiencing a significant increase in mass casualty attacks by individuals using guns, knives, motor vehicles and even bombs. Some of these attackers have self-connected to a terrorist or other ideological cause while others are motivated by some other perceived grievance.

Extensive research and analysis have revealed that many of these attackers share common behavioral and psychological characteristics, and this is important because understanding the dynamics of this offender population allows us to develop strategies to prevent these attacks in the future.

For the past two years a group at Rutgers University has worked closely with law enforcement leaders, mental health professionals, educators, faith leaders and others in the United States and Europe to better understand the psychological dynamics of mass casualty attackers and to develop an operational framework that can be used to prevent future attacks.

These efforts have revealed that mass casualty attacks can be prevented when law enforcement agencies at the local level work closely with mental health professionals and community members to identify those who are traveling down the path toward violence and intervene before that act of violence occurs.

This prevention framework includes educating the public so that they can recognize important warning signs, encouraging the public to report them and expanding the use of behavioral risk assessment methodologies as part of investigative protocols.

Importantly, it also includes the use of non-law enforcement intervention activities in the pre-criminal space so that the underlying issues that are at the root of the violent behavior are addressed before a violent act is committed.

In sum this framework prioritizes holistic and collaborative ways to detect, assess, and intervene in situations where individuals may exhibit the behaviors and indicators of mass casualty attacks in order to prevent a violent attack.

There has been significant growth in research and analysis that has revealed much about the behavioral characteristics of violent extremists and how those characteristics relate to behaviors associated with mass casualty attacks based on non-ideological motives.

A new model for preventing attacks has emerged. It is an operational model informed by long-standing behavioral risk assessment and threat management techniques employed by organizations such as the United States Secret Service, and involves expanding the use of community-based, multidisciplinary activities intended to prevent targeted violent activity and mass casualty attacks.

While this approach holds great promise for preventing mass casualty attacks, it also provides local communities a more extensive tool kit in dealing with violent behavior generally, including that which stems from law enforcement interactions with those suffering from mental illness as well.

This is not a theoretical concept. Jurisdictions across the nation have implemented such a framework.


John D. Cohen is a distinguished professor of professional practice in criminal justice at Rutgers University. He is the former acting undersecretary for the intelligence and analysis and counter-terrorism coordinator for the United States Department of Homeland Security. He has held federal, state and local law enforcement and homeland security related positions over his 32-year career, including having served as a federal agent and police officer in Southern California. For more information regarding the work cited in this post he can be emailed at john.cohen@rutgers.edu.

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John Cohen

Professor John D. Cohen

Rutgers University

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