Firearm injury is one of the leading causes of death in the United States.1 Governmental legislative response has focused on background checks for firearm purchasing, and mental health conditions account for an increasing percentage of disqualifications from firearm purchase. Available evidence indicates, however, that the absolute risk of violence by individuals who are mentally ill is low and is predicted by a prior history of substance use and criminality rather than mental illness. State variations in: (1) legal criteria fr involuntary commitment and other types of mental health adjudication; (2) mental health-related disqualifications from firearms; and (3) reporting firearm-disqualifying mental health records to the background check database also create ambiguities for clinicians and law makers tasked with shaping and evaluating disqualification. Information on an effective public health approach to background check disqualification is needed. We propose an agent-based model of firearm markets that would estimate the absolute number of deaths that would be prevented under various scenarios for firearm disqualification focusing on three main areas: a) mental illness; b) substance abuse; and c) criminality. We will implement disqualification scenarios recommended by the Consortium for Risk-Based Firearms Policy, in order to provide stakeholders with the optimal public health approach to using background check legislation to prevent firearm violence.
Disqualifying high-risk individuals from purchasing a firearm at the point of sale is a critical component of a public health response to growing firearm-related injury in the United States. The optimal disqualification strategy, however, is not currently empirically based. We propose to use agent-based modeling to provide stakeholders with estimates of the public health benefit of various disqualification strategies based on history of mental illness, substance abuse, and criminality.
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