Post on 21-Jan-2016
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Traci Hale, Battelle Memorial Institute
Committee on Methodological Improvement to the Department of Homeland Security’s 2006 Bioterrorism Risk Assessment
10 February 2007
Traci Hale, Battelle Memorial Institute
Committee on Methodological Improvement to the Department of Homeland Security’s 2006 Bioterrorism Risk Assessment
10 February 2007
2008 DHS Bioterrorism Risk Assessment:
Planned Improvements
2008 DHS Bioterrorism Risk Assessment:
Planned Improvements
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General overview of plans
The 2008 Risk Assessment will include: An expanded list of agents to be assessed (to include anti-agricultural,
engineered, and emerging agents) An expansion of scenarios for each target-type and associated revisions to
the Event Tree Review and improvement of all consequence models Improved data regarding mitigation strategies, and improved medical
mitigation models Improved calculation engine to decrease run times and simplify
configuration files Implementation of formalized elicitation process to obtain SME judgments
in specific subject areas Expansion of economic modeling to include indirect costs as well as
additional direct costs Expansion of tailored risk assessments and sensitivity studies
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Agent Production
ScenarioConsequences
Mitigation
Selection Probability
Agent Mass
Bioagent
DisseminationEfficiency
Event Detection
InitiationFrequency
RISK
Selection Probability
Selection Probability
ScenarioProbability
Agent ReleaseModeling
AgentRisk
Ranking
EventTree
Quantification
AGENTRELEASE
TargetThreat Group
MitigationResponse
Dispersion
SUSCEPTIBLEINFECTED
ILL &
INFECTIOUS
RECUPERATING
UNTREATED
prob of infection
avg incubation time
No Treatment
DYING
Become
Infected
initial
infection
Are Dying
Susceptible
Vaccinated
prob contact
is susc
Spontaneous
Recovery
Are Treated
RECOVERED\IMMUNE
SUSC REC'ing
PROPHYL
Become Ill
RECEIV'NG
TREATEMENT Recuperation
Inf Receive
Prophyl
Susc Receive
Prophyl
Infected
Vaccinated
INF REC'ing
PROPHYL
DEAD
Die
End Susc
Prophyl
Ineff Treat
End Inf
Prophyl
Recovercontacts
per day
+contagious
e
K
K
1 2 3
4
5
6
7
8
9
10
10
A
C
C
D
D
E
E
F
G
H
HJ
J
B
*
a
b
c
d
DiseaseSpread
Scenario Analysis and Consequence Modeling
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Branch Probabilities and Uncertainty Management
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Consequence Uncertainty
For the 2006 Risk Assessment epistemic uncertainty in the consequence results was not considered Aleatory uncertainty, reflecting variation in results arising from
unknowable details of bioterrorism attack scenarios, was embedded in the consequence models
Aleatory uncertainty is reflected in the scenario specific consequence distributions
Consequence uncertainty was omitted due to the overwhelming processing requirements
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For the 2008 Risk Assessment epistemic uncertainty in consequence results will be implemented
Improvements in the risk assessment software allowing specification of user defined functions that accept uncertainty parameters for components of the consequence calculation are the required improvement. For example:
Number of illnesses conditional on threat organization, target, surrogate, and mode of dissemination, [RI|MRE,TO,Target,Surrogate,ModeD,<uncertainty parameters>]
Percentage of fatalities mitigated by public health response conditional on number of illnesses, target, and event detection, [MFI|CI, Target, EventDetect, <uncertainty parameters>]
Moving Risk Assessment computing to a Linux cluster platform was required to make the computations required for consequence uncertainty feasible
Consequence Uncertainty
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Consequence Calculation Equations
AREACFCIECE
RFATTACKSIINFMFICICF
RFATTACKSIINFMEIPSRVRMREATTACKSPSRVRMREIINFCI
MMADPSRQFRQFAMRMRE
PSPSTPSR
VFVFVTVR
QFQFQFQFQFMTMR
,,|
,,|*
,,|,,|,,|
,|6
62
54321
Symbol Description Symbol Description
MT Target mass AREA Area requiring decontamination
QF1-QF6 Factors to explain production/processing/storage/etc. losses ATTACKS Number of simultaneous attacks
VT Target volume RF Percentage of index infected who become untreated fatalities
VF1,VF6 Factors to explain concentration/formulation volume changes MEI Epidemiological spread and prophylaxis factor
PST Target percent solids MFI Public health system mortality prevention efficacy
PS6 Factor to explain formulation percent solids change CI Illness consequences
QFR Respirable fraction CF Fatalitiy consequences
QFA Active fraction E Economic cost
IINF Number of index infected CE Economic consequences
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Subject Matter Expert and Stakeholder Interactions
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Subject Matter Experts and Stakeholder Interactions
Subject Matter Expert / Stakeholder interactions are taking several forms: Formal elicitations
START (bioagent selection probabilities) Selected psychologists from the IC (bioagent selection
probabilities) BTISWG (interdiction, frequency of initiation, bioagent selection,
multiple attack probabilities) Informal elicitations
BTISWG panel discussion of target, dissemination, and production probabilities
Stakeholder Working Group meetings IBRAWG (review and vet attack scenarios, production data,
medical mitigation data)
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Subject Matter Experts and Stakeholder Interactions
IBRAWG Includes CDC, NIH, FDA, USDA, EPA, and the intelligence community, created to “provide interagency input guidance and to the DHS BTRAP. This
Working Group will assist DHS in identifying agents and scenarios for the 2008 Bioterrorism Risk Assessment and will provide technical review of risk assessment input and assumptions, establishing subgroups for this purpose if necessary. The IBRAWG will be a source of technical advice and expertise, and will serve as an interagency forum for sharing, reviewing, and vetting risk assessment data and results as they are generated.”
To date, this group has been responsible for the selection of the 2008 biological agent list, has provided input for attack scenarios, and has provided significant contributions which will play a role in consequence and mitigation modeling.
BTISWG Includes members of the intelligence community created for the express purpose of providing classified intelligence/threat information
and data to the Risk Assessment. This group will be responsible for the assignments of probability concerning terrorist decisions through both formal Subject Matter Expert elicitations as well as informal discussions.
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Subject Matter Experts and Stakeholder Interactions
These Working Groups provide the stakeholders with the opportunity to review and discuss attack and mitigation input scenarios
and input data reach consensus regarding broad spectrum issues (such
as selection of the 2008 bioagent list) voice any issues or concerns regarding the assessment
while still in progress
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Indoor Aerosol Dispersion Modeling
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Indoor Aerosol Dispersion Modeling
In October 2006, the release of a biological agent in a subway system was specifically identified by DHS as a high priority attack scenario to address In the 2006 assessment, the subway attack scenario was
considered, but only as one of several small enclosed building surrogates
For the 2008 assessment, the subway (and other surrogates) will be individually assessable on the Event Tree
The model for the subway attack scenario will include the transfer of biological agent from the point of dissemination to additional downstream subway stations via movement of air in the subway cars and through the tunnels
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Foodborne and Waterborne Contamination Modeling
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Foodborne and Waterborne Contamination Modeling
Food Contamination Assessment Joint efforts are being initiated with BTSafety
BT Safety is participating in a collaborative effort with several federal agencies, including FDA, USDA, CDC and DHS NCFPD to develop a simulation model to estimate the impact of food supply contamination
This model is planned to be modified and incorporated into the DHS Risk Assessment calculation engine
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Foodborne and Waterborne Contamination Modeling
Water Contamination Assessment Joint efforts are being initiated with EPA
To generate a more realistic decay model To calculate a more accurate mixing parameter based on
comparisons of the Risk Assessment mathematical model with EPA-held hydraulic models of real public water systems
Continuing discussions with EPA staff regarding other aspects of the Water Contamination scenarios, including building system contamination and post-attack decontamination
Stakeholder input (FDA, USDA, NCFPD, EPA) is considered critical to a successful assessment
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Medical Mitigation and Epidemiological Modeling
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Medical Mitigation and Epidemiological Modeling
Substantial changes are in progress for the modeling of the public health response and spread of contagious diseases following a bioterrorism event As described yesterday, SEIR modeling is being applied
Model and data review In late February, a review of the SEIR model and input data
will be performed by experts identified by DHS. In early March, IBRAWG members will review models and
input data as well Risk perception
The SEIR model incorporates effects of ‘worried well’ Impacts on available supplies time to treatment due to increased distribution times
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Anti-agricultural Scenarios
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Anti-agricultural Scenarios
Joint efforts with Lawrence Livermore National Laboratories and Texas A&M LLNL MESA model Texas A&M FAZD model
Incorporates stakeholder input from USDA (APHIS, ARS, CREES) DHS FAZD LLNL BKC
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Economic Analysis
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Economic Analysis
Economic consequences are significantly affected by the impact of risk perception on human behavior
CREATE (primarily Adam Rose, Peter Gordon, Jim Moore, and Bumsoo Lee) collaborating on development of I-O models to capture bioterrorism attack economic impacts
CREATE (primarily Adam Rose) developing CGE models for a small set of surrogates to compare with I-O models
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Economic Analysis
Direct Costs: Economic models have four components:
Human health (Agent specific) Hospitalization, treatments, etc.
Fatalities One year of lost final demand
Decontamination (Agent and surrogate specific) Lost usage of buildings, clean-up, animal disposal
‘Conceptual model’ (Agent and surrogate specific) Risk perception based losses, e.g., reduced air travel
after airport or airplane attacks
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Economic Analysis
Indirect Costs: Fatality and conceptual model costs implemented in I-O primarily
by reductions in final demand. Some specific surrogates (for example, Mall) transfer
demand from industry impacted (for example, Clothing and Entertainment) to another industry (for example, On-line shopping)
Human health and decontamination costs are assumed to be funded by the government Positive impacts to medical and decontamination industries, Non-defense government spending is reduced (budget cuts)
and household spending is reduced (taxes) to pay for public health response and decontamination.
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Tailored Risk Assessments and Sensitivity Studies
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Tailored Risk Assessments and Sensitivity Studies
Increased capacity for tailored assessments and sensitivity studies Faster computing through hardware upgrades and software
improvements
Example tailored assessments requested Use of high Ro agent, similar to measles
Injection of high expertise terrorists
Example sensitivity studies under consideration Impact of additional modeling detail
Water modeling using a hydraulic simulation of a public water system versus the analytical model
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Calculation Engine Improvements to Enable Quick-turn around Tailored Assessments
Speed Improvements: Movement of code from .Net C# to ANSI standard C/C++
Gets rid of .Net overhead Porting of code from Windows to Linux
Gets rid of Windows overhead Parallelizing code
Employs multiple processors to perform calculations more quickly
Conceptual Improvements: Configuration files redesigned
Better mapping of component consequence distributions to all scenarios to which they apply
Development of user routines More convenient drawing of consequence components from distributions
conditional on other consequence components and uncertainty parameters Compartmentalizing intermediate consequence calculations
Speeds tailored risk assessments and sensitivity studies by allowing computations to start from point at which results change
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2008 Bioterrorism Risk Assessment Planned Improvements Associated with NAS Issues
*Data updating approach Data replacement and Bayesian updating
Stakeholder/SME Interactions Bioagent selection, scenario definition, model and data review, direct
elicitation input *Standardize lexicon *Non-traditional agents *Data quality matrix Incorporation of risk perception
Indirect costs and worried well Sensitivity Studies
Performed based on specific DHS requests or to further investigate internally-identified areas of interest
* indicates activities which will be discussed in detail during the NAS response discussions