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Spatiotemporal Health Analytics Group

Spatiotemporal methods and applications in exposure science and toxicology

Kyle P. Messier, Ph.D.
Kyle P. Messier, Ph.D.
Stadtman Investigator
Tel 984-287-3215
kyle.messier@nih.gov
530 Davis Dr
Keystone Building
Durham, NC 27713

Research Summary

Spatiotemporal Health Analytics Group

Spatiotemporal models are a class of statistical methods that explicitly account for spatial and/or temporal autocorrelation in data. In other words, a researcher can use these types of models to look for patterns and to predict variables, such as exposures or disease, at new locations. Spatiotemporal models have a rich history in many disciplines including mining, forestry, engineering, exposure science, and epidemiology. The Spatiotemporal Health Analytics Group is developing spatiotemporal methods and applications in environmental and human health exposure science while also exploring innovative applications in toxicology.

Currently, the Spatiotemporal Health Analytics Group is interested in:

  • Exposure science connections to toxicology through
    • Aggregate Exposure Pathway to Adverse Outcome Pathway (AEP to AOP)
    • Pathology Image Analysis
    • Spatial Transcriptomics
    • Toxicokinetic and Physiologically-based Pharmacokinetic modeling
  • Scalable spatiotemporal models for exposure assessment
  • Spatiotemporal applications in socioeconomic and racial disparities

The group is led by Kyle P. Messier, Ph.D. Messier is a Stadtman Tenure-Track Investigator in the Division of the National Toxicology Program (DNTP). He also holds a joint appointment with the National Institute of Minority Health and Health Disparities (NIMHD) in Bethesda, Maryland. Messier received a B.S. in Environmental Studies from the University of North Carolina at Asheville and a M.S. and Ph.D. from the University of North Carolina at Chapel Hill.

Selected Publications

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