Mass shootings are horrific events that annually take scores of innocent lives in the United States. Federal, state, and local governments as well as educational, religious, and private-sector organizations propose and enact polices and strategies to protect people from and during active shooter situations. A probabilistic risk assessment of a mass shooting for a specific organization, jurisdiction, or location can be the first step toward evaluating the effectiveness of risk mitigation strategies and determining which strategies might be most appropriate for a location. This article proposes a novel hierarchical method to assess the probability of a mass shooting at specific locations based on available historical data. First, the method generates a probability distribution over the annual number of mass shootings in the United States. Second, the article uses this national number of mass shootings to determine the risk for each state. Third, the state risk assessment is decomposed to calculate the probability of a mass shooting in a specific location such as a school. Multiple ways to assess the risk are presented, leading to slightly different probability assessments for a location. Results indicate that annual probability of a mass shooting in the largest high school in California is on the order of , and the annual probability of a mass shooting in the largest high school in Iowa is about half as likely as in the California school.
Keywords: mass shootings; probabilistic risk assessment; simulation; zero‐inflated Poisson regression.
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