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Appendix B: Threat Fusion Models

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Appendix C: Biosurveillance Model Files

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This dissertation considers the viability of applying Value of Information (VoI) methods in complex systems for policy analysis, concluding that these methods can be applied, but that different methods are appropriate in different cases. VoI is value to a decisionmaker of the difference information makes for a decision, or what a decisionmaker should pay for information. Compared to present practice, specific value of information techniques can potentially improve policy analysis and decision making. To that end, a methodology for policy applications of VoI is presented that can simplify practical application.

The dissertation applied computational methods for VoI to two case studies in disparate domains: biosurveillance and detection of violent extremists. Each of the case studies outlines how Bayesian methods can be used to evaluate VoI, including a novel formulation for considering additional information sources in the systems. The case studies are used both to consider the relative benefits and drawbacks of these approaches in policy decision making, and to identify potential challenges. Approaches for identifying and avoiding these challenges and for selecting appropriate methods are integrated into the overall methodology, which is presented in the final chapter.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    An Overview of Policy Decisions for VoI Questions

  • Chapter Three

    Threat Fusion Case Study

  • Chapter Four

    Influenza Case Study

  • Chapter Five

    Methodology for Policy Applications of VoI

  • Appendix A

    Mathematical Formulation of VoI Problem Types

  • Appendix B

    Threat Model Bayesian Networks

  • Appendix C

    Stan Influenza Model and Data Files

Research conducted by

This document was submitted as a dissertation in March 2018 in partial fulfillment of the requirements of the doctoral degree in public policy analysis at the Pardee RAND Graduate School. The faculty committee that supervised and approved the dissertation consisted of Paul Davis (Chair), Steven Popper, and Kathryn Laskey.

This report is part of the RAND Corporation dissertation series. Pardee RAND dissertations are produced by graduate fellows of the Pardee RAND Graduate School, the world's leading producer of Ph.D.'s in policy analysis. The dissertations are supervised, reviewed, and approved by a Pardee RAND faculty committee overseeing each dissertation.

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