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

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

W2-B.4 Burns, CJ*; Wright, JM; Pierson, J; The Dow Chemical<br />

Company; cjburns@dow.com<br />

Panel discussion on the integration of workshop<br />

recommendations to move risk assessment <strong>for</strong>ward<br />

Open any introductory to epidemiology textbook and there will<br />

be at least one chapter devoted to comparing and contrasting<br />

study designs. Investigators must tailor their research to the<br />

expected disease prevalence, availability of exposure data,<br />

population demographics, and ethical demands of the study<br />

subjects. Further, these considerations must be made in the<br />

very real context of time, cost and expertise required to<br />

complete the study. Integrating epidemiological results into risk<br />

assessment applications is often hampered by incomplete or<br />

unavailable data or other study limitations. Additional<br />

challenges that must be overcome may include problems<br />

related to time, cost and available expertise and reliance on<br />

traditional approaches. Further, few epidemiological studies<br />

are initiated with risk assessment needs in mind; thus more<br />

cross-discipline interactions may facilitate providing relevant<br />

data and analyses that can be more readily evaluated and<br />

applied. Several approaches to characterize and reduce<br />

uncertainty, improve exposure assessment, and promote<br />

advanced epidemiological methods were recommended by the<br />

36 participants of the ILSI HESI workshop. If broadly<br />

implemented, the evaluation of causality based on<br />

epidemiological data might be improved and with it, its use in<br />

public health decision making. This panel discussion will focus<br />

on how to implement these workshop recommendations and<br />

break down barriers to their integration into everyday<br />

epidemiological evaluation and risk assessment applications.<br />

M4-H.2 Burns, WJ*; Slovic, P; Sellnow, T; Rosoff, H; John, R;<br />

Decision Research (AUTHORS 1 AND 2) UNIVERSITY OF<br />

KENTUCKY (AUTHORS 3) (AUTHORS 4 and 5);<br />

william_burns@sbcglobal.net<br />

Public response to the terrorist attacks on Boston<br />

On April 15 terrorists set off two bombs at the Boston Marathon<br />

killing 3 people and seriously injuring many others. Within days<br />

one terrorist was dead and the other apprehended. A<br />

nationwide online survey was conducted on April 16 to<br />

determine how the public was responding to this attack. A<br />

follow up survey was done with the same panel of respondents<br />

on April 30. Respondents were asked about their confidence in<br />

DHS to thwart and respond to terrorism, perceptions of<br />

terrorism risk, emotional reaction to the attack (e.g. anger,<br />

fear, sadness), their willingness to attend public events and the<br />

kind of in<strong>for</strong>mation they sought in the first 24 hours after the<br />

attack. This analysis is currently ongoing and the results will be<br />

reported during the presentation. These findings in<strong>for</strong>m risk<br />

management policy, particularly involving communication with<br />

the public during a crisis.<br />

W2-B.3 Burstyn, I; Drexel University; igor.Burstyn@drexel.edu<br />

On the future of epidemiologic methods in context of risk<br />

assessment<br />

Incorporation of epidemiologic evidence into human health risk<br />

assessment, specifically <strong>for</strong> a weight of evidence evaluation, is<br />

an important part of understanding and characterizing risks<br />

from environmental exposures. A thorough synthesis of relevant<br />

research, including epidemiology, provides a reasonable<br />

approach to setting acceptable levels of human exposure to<br />

environmental chemicals. Epidemiologic approaches <strong>for</strong> causal<br />

inference that include computational, frequentist and Bayesian<br />

statistical techniques can be applied to weight of evidence<br />

evaluations and risk characterization. While there is strong<br />

theoretical support <strong>for</strong> the utility of these approaches, their<br />

translation into epidemiologic practice and adoption to the<br />

needs of human health risk assessment is lagging. The focus of<br />

the epidemiologic methods breakout group of HESI workshop<br />

was to address methodologic enhancements and the application<br />

of these techniques to regulatory scientific evaluations. The<br />

group considered methods that are sometimes, but not<br />

frequently, used in epidemiologic studies to increase validity<br />

and more accurately portray uncertainties in results. As these<br />

results are key inputs <strong>for</strong> regulatory risk assessments, it is<br />

important to apply methodologies that appropriately represent<br />

validity and precision. Each of these broad approaches acts to<br />

improve the validity and better characterize the overall<br />

uncertainty <strong>for</strong> a single study’s findings and extends to<br />

improved characterization of epidemiologic results in weight of<br />

evidence assessments. The workshop participants expressed<br />

optimism that a widespread application of more appropriate<br />

methods of causal analysis and modeling can bring both<br />

increased application of epidemiologic results to risk<br />

assessments, and increased confidence among the stakeholders<br />

that policies based on this improved process would improve the<br />

effectiveness of interventions. The presentation will highlight<br />

the group’s recommendations and practical discussion points.<br />

M4-B.4 Butterworth, T; George Mason University;<br />

butterworthy@gmail.com<br />

BPA by the numbers: How the media framed risk<br />

The controversy over the safety of the chemical bisphenol a<br />

(BPA) has been driven by extensive media coverage, with<br />

hundreds of stories over the past six years. This presentation<br />

will look at how that coverage framed the purported risk - and<br />

how it consistently avoided the key data, quantitative and<br />

contextual, that explained that risk.<br />

December 8-11, 2013 - Baltimore, MD

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