ANALYTIC MODELS FOR ACTIVE SHOOTER INCIDENTS
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Authors
Sporrer, Aaron
Subjects
active shooter
mass casualty
expected casualties
analytic modeling
mass casualty
expected casualties
analytic modeling
Advisors
Kress, Moshe
Szechtman, Roberto
Date of Issue
2020-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Active shooter incidents in the United States are growing in frequency and scale. This increase has gained widespread attention, with mounting calls to authorities and policymakers to reduce the number and impact of such events. Unfortunately, studying active shooter incidents is particularly difficult. Unlike other social phenomena, the window for observation is brief, and realistic human experiments are practically unobtainable. The last decade has seen a flurry of computer simulation models attempt to fill this gap; however, without an abundance of data or corresponding analytic models for verification, their results are precarious. This thesis presents a series of analytic models that capture the central dynamics of active shooter incidents, allowing researchers to gain insight on which factors most affect the outcomes of these events. The models have potential to inform policy, enable analysis for decision-makers, and influence emergency response plans in order to ultimately save lives.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release. distribution is unlimited
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.