Spatial-Temporal Exposure Assessment Modeling

The Spatial-Temporal Exposure Assessment Modeling Initiative brings together a group of scientists with complementary backgrounds and areas of expertise. They will provide the synergy needed to develop broad spatial-temporal statistical models that study and characterize the impact of environmental exposures on human disease at the population level, in particular in NC rural and agricultural communities. They will interact with the other CHHE research group initiatives in attempt to link issues of exposure to molecular/cellular mechanisms of disease pathogenesis and susceptibility amongst individuals in rural settings.  New methods for recording the locations of health data due to recent advances in Geographical Information Systems (GIS) and Global Positioning Systems (GPS) have permitted new types of disease and exposure mapping and spatial modeling of association of environmental stressors and health data, as well as new approaches to support disease prevention and control activities in public health. This has generated considerable interest in the development of statistical modeling for location-referenced and areal health data.  We will use statistical frameworks to bring together GIS capabilities, climate and weather, deterministic models for air pollution capable of providing information about air pollution in rural areas without monitoring stations, geocoded health data, and novel spatial modeling approaches for risk assessment and exposure modeling.  A major focus of the exposure modeling initiative will be to improve upon existing methods, by introducing Bayesian multivariate spatio-temporal statistical models that characterize simultaneously complex spatial and temporal dependence structures in the environmental stressors, and health outcomes, while taking into account different sources of uncertainty in models and data.  Novel spatial regression models will be developed  for better characterization of risk.  The spatial-temporal exposure assessment modeling initiative is led by Dr. Montserrat Fuentes, PhD, who is a Professor in the Department of Statistics.

Montserrat Fuentes  Director, Spatial Temporal Exposure Assessment Modeling

Dr. Montserrat Fuentes

Viney Aneja, PhD Professor, Department of Marine Earth and Atmospheric Science

Chris Frey, PhD Professor,  Department of  Environmental and Civil Engineering

Brian Reich, PhD Assistant Professor, Department of Statistics

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