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

SRA 2013 Annual Meeting Abstracts
T4-E.5 Bartholomew, MJ; Hooberman, B; Stewart, KN*; Okelo,
PO; Graber, G; FDA Center for Veterinary Medicine; FDA Office
of Foods and Veterinary Medicine; FDA Center for Veterinary
Medicine; FDA Center for Veterinary Medicine; AFSS
Consulting; mary.bartholomew@fda.hhs.gov
Ranking Contaminants in Swine and Poultry Feed
In addition to being responsible for the safety and effectiveness
of new animal drugs, the FDA Center for Veterinary Medicine
(CVM) has responsibility for the safety of the U. S. animal feed
supply. The Animal Feed Safety System (AFSS) was developed
to integrate a variety of activities related to the Center’s
regulatory responsibility concerning animal feed. One facet of
the AFSS is a risk-ranking model, described in the talk
Risk-Ranking Model for Hazards in Animal Feed, which is being
presented at this meeting. The model evaluates likelihood of
exposure and health consequences from exposure to
contaminants in animal feed. In this presentation we apply the
model, using examples for two food-producing animal species,
swine and poultry. Risks associated with hazards in the animal
feed for the two animal species are estimated, ranked, and
compared. The AFSS model may be used by CVM to guide
allocation of resources and other management decisions
concerning the regulation of animal feeds. Possible implications
for risk management decisions based on the findings for the
examples will be presented.
M3-D.1 Bartrand, TA*; Marks, HM; Coleman, ME; Donahue, D;
Hines, SA; Comer, JE; Taft, SC; Tetra Tech;
timothy.bartrand@tetratech.com
The Influence of Dosing Schedule on Rabbit Responses to
Aerosols of Bacillus anthracis
Traditional microbial dose response analysis and survival
analysis were used to model time of death of New Zealand
white rabbits exposed to low aerosol doses of Bacillus anthracis
spores. Two sets of experimental data were analyzed. The first
set included the times to death of hosts exposed to single doses
of B. anthracis spores. The second set provided the times to
death for rabbits exposed to multiple daily doses (excluding
weekends) of B. anthracis spores. A model predicting times to
death based on an exponential microbial dose response
assessment, superimposed with an empirically derived
incubation function using survival analysis methods was
evaluated to fit the two data sets. Several additional models for
time to death for aerosols of B. anthracis were also assessed for
comparison, including varying the determined hazard function
over time, survival models with different underlying dose
response functions, and a published mechanistic model. None
of these models provided a statistically significant improvement
in fit over the exponential-based model in which there was no
time dependent effect on the hazard function. Therefore, the
model suggests, for the dosing schedule used in this study,
long-term response of the hosts depends only on the net
accumulated dose an animal received before dying. This finding
may be due to small size of the data sets and number of animals
that died. Further research with alternative dosing schedules,
collection of immune system data (particularly innate immune
response), and alternative pathogen-host pairings is needed to
clarify the relationship of time to death and dosing schedule.
M2-C.1 Bassarak, C*; Pfister, HR; Böhm, G; Leuphana
University Lueneburg; University Bergen;
bassarak@leuphana.de
Moral aspects in the perception of societal risks
Research has long neglected aspects of morality in risk
perception. However, recently there is increasing consensus
between practitioners and researchers that epistemic risk
judgments and moral judgments are closely related. This is
particularly the case when it comes to complex societal risks
such as terrorism, nuclear power or global warming. These
ideas have been supported by a study employing the
psychometric paradigm (Slovic, 1987) where we found that
dread, a common dimension of risk perception that has been
found to be related to perceived overall risk, is highly blended
with morality. However, these data were measured explicitly
and participants were asked for moral and risk judgments on
the same occasion. In a second step, we are now interested in
the question whether it makes a difference if one is asked to
either give a moral or an epistemic risk judgment about a
societal risk. In a laboratory study, participants (N = 51) were
explicitly and implicitly asked to give either epistemic risk
judgments or moral judgments regarding six societal risk items
which were selected on the basis of preceding studies. Implicit
judgments were measured using the single target implicit
association test which is an assignment test that reports data
on errors and latencies. These data are usually transformed
into so called D-scores which can be interpreted as effect sizes
measures for association strength. An analysis of variance
suggests that D-scores are significantly higher in the morality
than in the risk condition. From that we conclude that societal
risks can be better mapped onto a moral-immoral dimension
than onto a risky-safe dimension. Finally, analyses will be
presented predicting overall explicit risk judgment with implicit
risk and morality judgments. Thus, we seek to gain insight into
what affects lay-peoples’ risk judgments and stimulate the
discussion how this knowledge may assist political decision
making making or risk communication.
P.125 Bates, ME*; Linkov, I; Clark, TL; Curran, RW; Bell, HM;
US Army Corps of Engineers - Engineer Research and
Development Center, Pacific Disaster Center;
Matthew.E.Bates@usace.army.mil
Application of multi-criteria decision snalysis to
humanitarian sssistance and disaster response site
suitability analysis
Humanitarian Assistance and Disaster Response (HADR)
managers often face the complex task of prioritizing limited
funds for investment across broad regions of varying need. In
selecting regions and sites for project investment, project
funders must assess and tradeoff site investment suitability
along multiple dimensions. For example, governmental HADR
resources might be invested to fit a combination of needs
including: investing agency mission, local community hazard
exposure, local community resilience, and projected investment
sustainability, etc., each of which can be decomposed into many
relevant sub-criteria. This poster presents a framework for
HADR site suitability analysis based on the integration of
spatial and non-spatial data from Geographic Information
Systems (GIS) and other HADR sources via Multi-Criteria
Decision Analysis, an analytical approach for integrating data
across traditionally-incommensurate criteria via value functions
and tradeoff weights. This framework is applied to a case study
using HADR data to analyze investment suitability at the
Department-level in El Salvador.
December 8-11, 2013 - Baltimore, MD