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Activity Number: 450
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 3:05 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #317846
Title: Bivariate Left-Censored Bayesian Model for Predicting Exposure: Preliminary Analysis of Worker Exposure During the Deepwater Horizon Oil Spill
Author(s): Caroline Groth* and Sudipto Banerjee and Gurumurthy Ramachandran and Mark R. Stenzel and Dale P. Sandler and Aaron Blair and Richard K. Kwok and Patricia Stewart and Lawrence S. Engel
Companies: University of Minnesota and UCLA and University of Minnesota and Exposure Assessment Applications, LLC and National Institute of Environmental Health Sciences and National Cancer Institute and National Institute of Environmental Health Sciences and Stewart Exposure Assessments, LLC and The University of North Carolina at Chapel Hill
Keywords: Bayesian Statistics ; Deepwater Horizon Oil Spill ; Bivariate Left-Censoring ; Exposure Assessment ; Correlation ; total hydrocarbons
Abstract:

In 2010, the Deepwater Horizon oil rig exploded, resulting in the release of over four million barrels of oil into the Gulf of Mexico over the ensuing three months. The Gulf STUDY is an epidemiological study investigating potential adverse health effects in workers who participated in the oil spill response and clean-up. Our goal is to estimate exposures to benzene, ethylbenzene, toluene, xylene (BTEX), total hydrocarbons (THC), and hexane in specific clean-up jobs for later use in a GuLF STUDY job-exposure matrix. Although over 25,000 air samples were collected during the spill, for many jobs a large percentage of measurements were below the analytic methods' limit of detection. Here we use THC, a composite of the volatile components of oil with a lower degree of censoring, to develop linear models for estimating BTEX and hexane air concentrations. A novel Bayesian hierarchical linear model allows us to model exposures for multiple jobs simultaneously while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposures for job-groups on the Development Driller III, a vessel charged with drilling one of the relief wells.


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