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Quantifying the risk of mass shootings at specific locations.
Lei, Xue; MacKenzie, Cameron.
Afiliação
  • Lei X; Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, USA.
  • MacKenzie C; Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, USA.
Risk Anal ; 44(4): 868-882, 2024 Apr.
Article em En | MEDLINE | ID: mdl-37607802
ABSTRACT
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 10 - 6 - 10 - 5 $10^{-6}-10^{-5}$ , 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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article