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