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Department of Homeland Security Bioterrorism Risk Assessment: A Call for Change (2008)
Board on Mathematical Sciences and Their Applications (BMSA)
Board on Life Sciences (BLS)

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. "Appendix D: Bioterrorism Risk Analysis with Decision Trees." Department of Homeland Security Bioterrorism Risk Assessment: A Call for Change. Washington, DC: The National Academies Press, 2008.

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Department of Homeland Security Bioterrorism Risk Assessment: A Call for Change

FIGURE D.2 BTRA modeling using decision analysis. This figure provides an alternative generation table developed in Figure D.1. However, instead of showing the 2006 BTRA modeling alternative, the dark gray shading highlights a decision analysis method for BTRA. The light gray shading identifies possible variations to the proposed decision analysis methodology. For example, instead of combining the consequences using a multiattribute value model, the consequences could be analyzed individually and not combined or be converted to dollars.

Since they are uncertain to the terrorists, U.S. decisions (e.g., interdiction) and uncertain events (e.g., detection) would be modeled using probability distributions. Any of the consequences that have credible models could be used. Decision trees can be used to find the terrorist strategy (a sequential set of decisions) that maximizes the terrorist objectives by averaging out and rolling back the decision tree. The decision tree can be solved multiple times for each single objective or can be solved once with combined consequences (Parnell, 2007). There are at least three ways of combining the consequences: converting each consequence to dollars, using a multiple attribute value model to normalize and weight the consequences, or using a multiple attribute utility model to normalize and weight the consequences. Each of the techniques has different assumptions and data requirements. All have been used on major national studies.

AN ILLUSTRATIVE BIOTERRORIST DECISION MODEL USING DECISION TREES

The 18 node event tree (with consequences) could be simplified especially if credible data are not available from subject matter experts. However, in order to use as much as possible of the existing 2006 BTRA event tree method, we directly converted the event tree to a decision tree. Using a format similar to Figure 3.4 in Chapter 3 of this report, Figure D.3 lists one possible set of assumptions that could be used to convert the DHS event tree to the bioterrorist decision tree. The figure adds new node numbers, type of node, rationale, average branches, and probability distributions to be assessed. The phases are the same but are not included due to space limitations on the page.

Several assumptions were made in Figure D.3. First, the old nodes numbers 1 (frequency of attack) and 16 (potential for multiple attacks) were deleted for the reasons discussed above. Second, we converted all terrorism decisions to decision nodes.1 That left six chance nodes: four interdiction nodes, one detection node, and one consequence node. Each of these would be uncertain to the bioterrorist. Third,

1

While agent selection is an obvious decision, some of the later decisions could be modeled as uncertain nodes early in the terrorist planning cycle. The actual nodes that would be decision or chance nodes would depend on the knowledge of subject matter experts.

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Front Matter (R1-R14)
Summary (1-5)
1 Introduction (6-10)
2 The Critical Contribution of Risk Analysis to Risk Management and Reduction of Bioterrorism Risk (11-19)
3 Description and Analysis of the Department of Homeland Security's Biological Threat Risk Assessment of 2006 (20-33)
4 Department of Homeland Security Decision Requirements for Risk Management (34-41)
5 Risk Assessment for Unknown and Engineered Biothreat Agents (42-46)
6 Improving Bioterrorism Consequence Assessment (47-50)
7 Improving the Department of Homeland Security's Biological Threat Risk Assessment and Adding Risk Management (51-60)
Appendix A: Lexicon (61-77)
Appendix B: Mathematical Characterization of the Biological Threat Risk Assessment Event Tree and Risk Assessment (78-79)
Appendix C: Computational Example Illustrating the Replacement of a Joint Distribution of Arc Probabilities with Marginal Expected Values of Individual Arc Probabilities (80-84)
Appendix D: Bioterrorism Risk Analysis with Decision Trees (85-89)
Appendix E: Optimizing Department of Homeland Security Defense Investments: Applying Defender-Attacker (-Defender) Optimization to Terror Risk Assessment and Mitigation (90-102)
Appendix F: Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example (103-110)
Appendix G: On the Quantification of Uncertainty and Enhancing Probabilistic Risk Analysis (111-115)
Appendix H: Game Theory and Interdependencies (116-121)
Appendix I: Review of BTRA Modeling (122-125)
Appendix J: Reprinted Interim Report (126-148)
Appendix K: Meeting Agendas (149-152)
Appendix L: Biographies of Committee Members (153-156)
Appendix M: Acronyms (157-158)