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Problem - Approach

Rapid Assessment and Characterization of Environmental Risks ( RACER) - A New Software Tool - Gary M. Marsh, Ph.D. Michael Cunningham, M.S. D epartment of Biostatistics Graduate School of Public Health Pittsburgh Environmental Summit - April 18, 2007. Problem - Approach.

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Problem - Approach

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  1. Rapid Assessment and Characterization of Environmental Risks (RACER) - A New Software Tool -Gary M. Marsh, Ph.D.Michael Cunningham, M.S.Department of BiostatisticsGraduate School of Public HealthPittsburgh Environmental Summit - April 18, 2007

  2. Problem - Approach • Under what conditions and to what extent can we detect elevations in the background rate of disease that were truly caused by an environmental exposure? • 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

  3. Feasibility Factors (Statistical) • The background rate of the disease under study (i.e., the rate in the unexposed population) • The overall size of the potentially exposed population • The proportion of the population that is exposed to varying levels of the environmental hazard • The relative potencies of the various levels of exposure to elevate the background rate of disease • Observation time of exposed subpopulations and latency period of disease under study

  4. Conceptual Model: Airborne Exposure to Point Source with Proportion of Subpopulations Exposed Downwind of Source

  5. Example 1: 80% Statistical Power to Detect 1.3-Fold Excess Reached in 2.5 Years

  6. Example 2: Power as Function of MDRR and Time Period

  7. Example 3: Power as a Function of % Exposed (ew) and Time (years) - Comparison of 4 Plots RRee = 1.2 RRee = 1.4 RRee = 1.6 RRee = 1.8

  8. Possible Future RACER Enhancements • Indirect and direct standardization procedures • Extend standardization to multiple factors • Account for geographic population mobility • Time dependent exposure-elevated relative risks • Account for latency/incubation period of health endpoints • Statistical methods for spatial (clustered) data

  9. Acknowledgements The investigators wish to thank the following groups for their support and guidance: Centers for Disease Control and Prevention Environmental Public Health Tracking Program Grant # 5U19EH000103-02 (Academic Partners for Excellence in Environmental Public Health Tracking) University of Pittsburgh Academic Consortium for Excellence in Environmental Public Health Tracking (UPACE-EPHT) (a collaboration with Drexel University)

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