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Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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SRA 2013 Annual Meeting <strong>Abstracts</strong><br />

M3-C.4 Ben-Haim, Y; Technion ; yakov@technion.ac.il<br />

What Military Strategy can Teach Us about<br />

<strong>Risk</strong>-Management and Uncertainty<br />

War entails vast risks and uncertainties. <strong>Risk</strong> managers can<br />

learn valuable lessons from the disputes among military<br />

theorists. We discuss a foundational dispute between Clauswitz<br />

and Jomini in their attempts to understand Napoleon's<br />

overwhelming military success. What was the key to his military<br />

invincibility? Clauswitz felt that it is futile to seek governing<br />

rules or patterns or laws of successful military strategy. The<br />

dominant factors in war, according to Clauswitz, are<br />

uncertainty and friction (by which he meant the inherent<br />

resistance of reality to the will of men at war). Jomini<br />

disagreed. He felt that, while war is not a science like the study<br />

of nature, it nonetheless has patterns and rules that can be<br />

discovered. He felt that he uncovered the rules that made<br />

Napoleon so successful. In modern language we would say that<br />

Jomini identified successful methods of operational art: rules<br />

<strong>for</strong> the manipulation of large field units. The main claim of this<br />

talk is that the analysis, and even more so the management, of<br />

risk, must be approached in the tradition of Clauswitz far more<br />

than of Jomini. It is the uniqueness and uncertainty of risk<br />

situations that present the special challenges that risk analysts<br />

and mangers must face. Once a risk becomes well known and<br />

thoroughly understood it is no longer a risk, and it is managed<br />

by a routine. <strong>Risk</strong>s are "risky" precisely because of the endless<br />

possibility <strong>for</strong> surprise. Sound science, careful measurement,<br />

accurate monitoring and reporting, are all crucial. Nonetheless,<br />

a successful risk professional is able to analyze and manage<br />

uncertainty, variability and surprise (info-gap theory is one<br />

tool). This is very Clauswitzian and not Jominian at all.<br />

M2-H.2 Bennett, SP*; Waters, JF; Howard, K; Baker, H;<br />

McGinn, TJ; Wong, DY; U.S. Department of Homeland Security;<br />

steve.bennett@hq.dhs.gov<br />

Indicators and warnings <strong>for</strong> biological events: enhanced<br />

biosurveillance through the fusion of pre-hospital data.<br />

The United States is vulnerable to a range of threats that can<br />

impact human, agricultural, or environmental health. Managing<br />

risks from covert or naturally-occurring, accidental, or<br />

deliberate biological events such as bioterrorism or emerging<br />

infectious disease or bioterrorism is difficult to accomplish<br />

through activities that attempt to reduce these events’<br />

likelihood of occurrence. Instead, activities that mitigate these<br />

risks largely focus on reducing, managing, or limiting the<br />

consequences of biological events once they begin to occur. To<br />

do this effectively requires the earliest possible warning that an<br />

event is occurring, as well as continuing shared situational<br />

awareness throughout the event, to enable effective decision<br />

making regarding what management actions should be taken.<br />

In this presentation, we will describe advances in the<br />

Department of Homeland Security’s National Biosurveillance<br />

Integration Center (NBIC) towards integrating and fusing early<br />

pre-hospital health data to provide early indicators and<br />

warnings. In addition, we will discuss initial concepts <strong>for</strong> the<br />

development of a risk and decision analysis framework to<br />

support the use of early warning signals and ongoing event<br />

characterization and decision support.<br />

M4-I.4 Benouar, D*; Rovins, J; University of Science and<br />

Technology Houari Boumediene (USTHB);<br />

dbenouar@gmail.com<br />

Forensic disaster investigations (FORIN), a new approach<br />

to learn lessons from disasters: A case study of the 2001<br />

Algiers (Algeria) Flood and Debris flow<br />

Disasters are increasingly being understood as ‘processes’ and<br />

not discreet ‘events’. Moreover, the causes of disasters are<br />

driven by complex engineering, socio-economic, socio-cultural,<br />

and various geophysical factors. Such interacting driving<br />

factors, occurring across a range of temporal and spatial scales,<br />

combine in numerous ways to configure disaster risks. Using<br />

some selected disasters in Africa, the dynamics of such risks<br />

and their configurations will be explored using a new approach<br />

and methodology, namely Forensic Disaster Investigations (also<br />

called FORIN studies). Forensic task is perhaps similar to<br />

solving a picture of a disaster puzzle. Initially, there are dozens<br />

or even hundreds of apparently disorganized pieces piled when<br />

examined individually, each piece may not provide much<br />

in<strong>for</strong>mation. Methodically, the various pieces are sorted and<br />

patiently fitted together in a logical context taking into account<br />

all the parameters. Slowly, an overall picture of the disaster<br />

emerges. When a significant portion of the disaster puzzle has<br />

been solved, it then becomes easier to see where the remaining<br />

pieces fit. The Integrated Research on Disaster <strong>Risk</strong><br />

programme is proposing new methodologies to examine the<br />

root issues surrounding the increase in disaster cost both<br />

human and economic.This paper attempts, as a case study, to<br />

investigate the Algiers (Algeria) floods and debris flows of 10<br />

November 2001 which caused the loss of more than 714 human<br />

lives, injured more than 312, made missing 116 and about 10<br />

000 were homeless, damaging more than 1500 housing units<br />

and scores of schools, bridges and public works. The objective<br />

is to dig more deeply into the causes of disasters in an<br />

integrated, comprehensive, transparent, and investigative or<br />

<strong>for</strong>ensic style. To establish a sound basis <strong>for</strong> analysis, FORIN<br />

relies upon the actual evidence found and applies accepted<br />

scientific methodologies and principles to interpret the disaster<br />

in all its facets. Often, the analysis requires the simultaneous<br />

application of several scientific disciplines.<br />

T4-C.1 Benromdhane, S.A.*; Hubbell, B.J.; US EPA, OAQPS;<br />

benromdhane.souad@epa.gov<br />

Air pollution mixtures and related health endpoints - A<br />

multipollutant risk assessment framework<br />

Abstract Air pollution regulatory and research strategies have<br />

largely focused on single pollutants, groups of chemically<br />

related pollutants, e.g. volatile organic compounds, or<br />

source-related pollutants, e.g. mobile source emissions.<br />

However, population exposures occur in locations with complex<br />

mixtures resulting from multiple sources of emissions and<br />

containing both gases and particles. Because most<br />

epidemiological studies focus on linear statistical models which<br />

do not account <strong>for</strong> interactions between pollutants, estimates of<br />

risk can suffer from biases and imprecision due to confounding<br />

from co-pollutants, or from incomplete model specification. This<br />

can lead to difficulties in interpreting the results <strong>for</strong> individual<br />

pollutants, and can potentially bias estimates in risk analyses<br />

conducted using those results. These biases can be in the<br />

estimates of risk <strong>for</strong> individual pollutants, as well as estimates<br />

of total risks across groups of pollutants. This presentation<br />

intends to evaluate the current single pollutant focused risk<br />

assessment paradigm and identify strengths and weaknesses<br />

that can be utilized to guide the transition to a multipollutant<br />

framework. A multipollutant conceptual scheme <strong>for</strong> toxicity<br />

characterization based on mode of action is illustrated in Figure<br />

1. This conceptual model shows how multiple pollutants could<br />

contribute additively or synergistically to a specific health<br />

endpoint. More comprehensive conceptual models based on the<br />

principles of exposure and risk analysis are needed to help<br />

in<strong>for</strong>m the development of future multipollutant epidemiology<br />

studies; these conceptual models can also <strong>for</strong>m the basis <strong>for</strong> an<br />

improved multipollutant exposure and risk analysis framework.<br />

December 8-11, 2013 - Baltimore, MD

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