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

SRA 2013 Annual Meeting Abstracts
P.23 Fiebelkorn, SA*; Bishop, EL; Breheny, D; Cunningham,
FH; Dillon, DM; Meredith, C; British American Tobacco, Group
R&D; clive_meredith@bat.com
Assessment of benzo(a)pyrene (a tobacco smoke toxicant)
as a driver of genotoxicity
Over 5,600 constituents have been identified in tobacco smoke,
some with well established toxicological properties. Our
proposed framework for the risk assessment of tobacco smoke
toxicants combines both computational and in vitro
experimental components. Initially we use Margin of Exposure
(MOE) calculations to segregate tobacco smoke toxicants into
high and low priority for risk management action, using
guidelines developed by the European Food Safety Authority
(EFSA). We conduct Mode of Action (MOA) analyses, using the
International Programme on Chemical Safety (IPCS)
framework, on these prioritised toxicants. Experimentally, we
then test individual priority toxicants for their activity in several
in vitro assays using the MOA for each toxicant to inform assay
selection. Here we describe our findings from use of this risk
assessment framework, using benzo(a)pyrene (BaP) as the
prototypical tobacco smoke toxicant. Following a detailed
literature search, we generated twelve MOEs for BaP ranging
from 16,805 to 2,400,000 indicating a lower priority for risk
reduction research. Our MOA analysis for BaP proposed four
key events; genotoxicity, mutation, cell proliferation and
tumour formation. From our in vitro toxicity data, the
concentrations of BaP equating to a point of departure were
1.0-1.28 µg/plate (Ames), 0.75-1.0 µg/ml (micronucleus) and
1.4-1.5 µg/ml (mouse lymphoma assay). These data confirm the
genotoxic and mutagenic potential of BaP, supporting the first
two key events in the proposed MOA. The data has
subsequently been used to generate in vitro MOEs and these
support the in vivo MOE conclusions (1,200,000-30,000,000).
Additional in vitro data sets from disease models provide
further weight of evidence for the postulated MOA key events.
Future refinement of our conclusions for BaP would include the
use of PBPK models to predict tissue dose within the
respiratory tract of smokers, and a cumulative risk assessment
on the various polycyclic aromatic hydrocarbons present in
tobacco smoke.
M4-I.3 Figueroa, RH*; Morgan, MG; Fischbeck, PS; Carnegie
Mellon University; raulf@cmu.edu
An assessment of the risks of building collapse for the
City of Nairobi based on an investigation into East
Africa’s construction quality control processes.
In developing countries, poor quality control in construction has
led to spontaneous building collapse and, in the event of even
moderate seismic activity, to major disaster. While
earthquake-resistant designs have greatly improved
international building codes that are accessible to designers
everywhere, builders in developing countries often fail to meet
acceptable standards. This paper examines the state of the
industry with respect to compliance with standards for concrete
used in structures, and assesses the risks of building collapse
under different scenarios for the city of Nairobi. The state of
the industry is assessed in two ways: 1) with a comparison of
test results reported by established laboratories in Nairobi from
a sample of new construction projects, to non-destructive-test
data collected at twenty-four construction sites; and 2) through
the elicitation of experts in construction familiar with the
Kenyan industry. The findings suggest that there is widespread
fraud and that the current quality control practices are not
effective in ensuring structural reliability. Therefore, regulators
routinely certify buildings as safe for occupation based, in part,
on inaccurate of false laboratory reports. These findings
highlight an example of laxity in quality control in the
construction industry that could be pervasive in many
developing countries, as the recent tragedy in Bangladesh and
the disaster in Haiti in 2010 suggest. The risks of collapse is
assessed by combining building inventory data, seismic
performance models of common types of building in Nairobi,
and estimates obtained by expert elicitation into a probabilistic
risk model. Thousands of dangerously weak buildings will be
built, and unless better policies are implemented, millions of
people would likely be exposed to unnecessarily higher risks for
generations. The methodology presented can be implemented
in many other regions with minimal adjustments.
T3-J.2 Finkel, AM; University of Pennsylvania Law School;
afinkel@law.upenn.edu
Lessons from risk assessment controversies for the
“job-killing regulations” debate
As our talents for collecting data, discerning causal
relationships, and refining empirical models continue to
improve, risk scientists and economists are struggling in their
own ways to provide “high-quality quantification.” Those
responsible for developing, supporting, or criticizing estimates
of regulatory costs in general, and of the effects of regulation
on jobs in particular, can either rise to or dodge the challenges
of analyzing thoroughly, humbly, transparently, objectively,
logically, and responsively (to public values and preferences).
These are all challenges that quantitative risk assessment
(QRA) has already confronted, and surmounted with varying
degrees of success, over the past several decades. This
presentation will draw out various parallels between recent
improvements in QRA and the unfinished work of improving
job-impact analysis for proposed regulations. I will focus on six
such analogies: (1) the attempts to reduce excessive
“conservatism” in estimation; (2) the supplanting of point
estimates with ranges and distributions acknowledging
uncertainty; (3) the emphasis on considering net effects, not
merely first-order ones; (4) the commitment to enumerating
and justifying all “defaults” used, including the “missing
defaults” problem identified by various National Academy
committees; (5) the moves to “harmonize” disparate effects and
aggregate them using a common currency; and (6) the
importance of considering effects across the inter-individual
spectrum of susceptibility. I conclude that economists should
strongly consider emulating the improvements in QRA, in order
to dispel some of the misinformation surrounding the
“job-killing regulations” controversy.
T4-A.4 Finkel, AM*; Berk, RA; University of Pennsylvania Law
School; afinkel@law.upenn.edu
Using statistical profiling to improve OSHA’s capability to
locate workplaces posing grave risks
The U.S. Occupational Safety and Health Administration
(OSHA) faces a daunting mismatch between the size of its
enforcement corps (roughly 2,000 inspectors nationwide) and
the number of worksites under its jurisdiction (more than 9
million). OSHA currently targets establishments for inspection
via their self-reported injury rates; this system leads the agency
to spend time visiting many “sheep in wolves’ clothing” (firms
that are fully compliant) and fails to find many true “wolves”
(firms inaccurately reporting low injury rates or that expose
workers to conditions that have not yet caused grave harm).
Predictive targeting is a non-intrusive way to listen better for
the signals that firms are sending by their day-to-day behavior.
We hypothesize that different “red flags”—in particular,
indicators of financial turmoil and evidence that firms are
flouting other regulatory requirements—are more strongly
related to the severity of workplace hazards than the injury
rates are. With a grant from the Robert Wood Johnson
Foundation, we have merged into the roughly 100,000 records
of OSHA inspections during 2008-09 two other large
enforcement databases: one that tracks dollar penalties and the
number of calendar quarters in non-compliance for three major
EPA programs (air pollution, water pollution, and hazardous
waste disposal), and one that tracks similar information for
several other Department of Labor (DOL) programs dealing
with fair wages, overtime pay, employment discrimination, and
the like. The data show that two unmeasured covariates are
strongly associated with the severity of hazardous workplace
conditions: (1) establishments with frequent non-compliance
with EPA and DOL wage/hour regulations; and (2) those located
in communities with a high percentage of minority residents.
We have recently added to the merged datafile a large
time-series of measures of credit scores, indebtedness, sales
growth, ownership changes and other financial and managerial
indicators at the establishment level, and will present results
from analysis of these characteristics.
December 8-11, 2013 - Baltimore, MD