A1258598358KcPHn

1
Rapid Assessment and Characterization of
Environmental Risks RACER (www.racer-pitt.com)
Gary M. Marsh, Ph.D. and Michael A. Cunningham,
M.S. University of Pittsburgh, Pittsburgh, PA
Hypothetical Examples to Illustrate Scenarios

• Rationale
• Relatively little research has focused on extent
  to which inherent limitations of environmental
  investigations impact on our ability to identify
  and characterize environmental risks
• Few software tools available that focus on
  epidemiological and statistical aspects of
  environmental investigations

• Rudimentary Model Schematic
• Concentric circles define exposure regions,
• i 1, 2, 3
• Population can be divided into j age groups
• A population of size N ( SNij) resides around
  the suspected exposure point source
• Background rates of health outcome specified, ?0j
• Background rates in exposed are elevated by the
  factor pi

Scenario 1
Scenario 2
Scenario 3

• Goals
• To help fill the research gap by evaluating the
  sensitivity of some commonly used statistical
  methods for identifying and characterizing risks
• To provide a web-based software tool that will
  enable public health officials and others to
  evaluate feasibility of conducting health
  tracking activities or targeted investigations

Question If the 3 health outcomes have been
observed in this potentially exposed population
over a 10 year period, what must the elevation to
the background risk have been to have reasonable
power to detect this true elevation?
Question If the residents of a town have been
exposed to these levels of ionizing radiation,
how can this exposure be characterized in terms
of the ability to detect a true 1.75-fold
increase in thyroid cancer incidence?
Question Assuming there are two levels of
exposure in the town (with unknown risks), what
combinations of elevated exposure risks,
proportion of population exposed, and time are
required to achieve sufficient power?
Required RACER Input

• Components of Rudimentary Empirical Model
• A community population of specified size resides
  around point source of environmental exposure
• Specify background rate of any health outcome of
  interest
• Specify exposure-response relationship for
  environmental risk
• Divide population into subpopulations by distance
  from exposure source and specify proportion of
  subpopulations exposed
• Use relative measure of effect to compare
  observed events in exposed subpopulations to
  number expected had background rates prevailed
• User can specify representative range of values
  for basic determinants of statistical
  characteristics
• Use empirical models to examine sensitivity of
  measures such as statistical power for a set of
  realistic environmental exposure scenarios

• Age-specific population and background rates
• Proportion of population exposed
• Exposure-level elevated risks

• Age-specific population and background rates
• Proportion of population exposed
• Observed health outcomes

• Age-specific population and background rates
• Specify range of proportion exposed
• Specify range of exposure elevated risks

Sample Output from RACER, Version 1.0 Beta

• RACER Analyzes Three Common Exposure Scenarios
• Scenario 1
• - Source of environmental exposure is identified
• - Proportion of population exposed and exposure-
  
• level health risks are known or estimable
• Scenario 2
• - Suspected source of environmental exposure
• - A number of health outcome are observed in a
• population over time
• Scenario 3
• - Suspected source of environmental exposure
• - Exposure level-specific populations and
• associated risks are neither known nor
• estimable

Contact Information Gary M. Marsh,
Ph.D. Professor of Biostatistics Director, Center
for Occupational Biostatistics and
Epidemiology University of Pittsburgh, Graduate
School of Public Health E-mail
gmarsh_at_cobe.pitt.edu

• The table is a portion of the data in the plot.
• After 5 more years, a true, 3.33-fold elevation
  in the background rate of this health outcome
  would be observed with a probability of
  approximately 66.

• The table is a portion of the data in the plot.
• 80 power is achieved after 29 years in this
  population.
• To reach 80 power, the 1.75-fold elevation in
  the background rates results in 28 observed
  cases in this population.

Acknowledgments Work on the RACER software
tool has been supported through the CDCs
Environmental Public Health Tracking Program
Grant 5U19EH000103-04 and the University of
Pittsburgh Academic Consortium for Excellence in
Environmental Public Health Tracking (UPACE-EPHT)

• The 3D contour plot shows the relationship
  between the overall exposure elevated RR, time,
  and the of the population exposed that result
  in 80 power.