Teaching
Environmental influences affect human health on local, regional and global scales through the natural, social, and economic process that connect us. At its most basic level, my teaching seeks to train students to be able to better understand how both people and risk factors are dispersed and what processes bring them together. Consequently, a large component of my teaching focuses on the use of geospatial technology: a collection of geographic information science tools used for the visualization, measurement, and analysis of earth’s features. These tools include geographic information systems (GIS), global positioning systems (GPS), and remote sensing. In terms of public health, geospatial technologies have transformed the way we model where people live and the environments they experience throughout their lives. This has significantly improved our ability to assess the environment of the person as a starting point for public health.
Courses:
Principles of Environmental Health Sciences (MUSC 2015-present)
This course is designed for public health students interested in studying the relationships between people and their environment and how it affects their well-being. This course offers a general introduction to environmental health, addressing fundamental topics and current debates. The first part of the course covers core methods and paradigms central to environmental health study. The second part of the course focuses on the practice of environmental health.
Introduction to Geographic Information Systems for Public Health (Emory University 2011-2014)
Geographic information systems (GIS) are becoming increasingly popular in all areas of public health. The focus of this course is to teach you practical GIS skills that can be applied in any public health setting. There are two goals for this course: 1) for students to develop a GIS toolkit by learning the most frequently used GIS skills; and 2) for students to learn how to apply GIS in public health setting through the exploration of applicability of GIS to public health data.
Webinars:
"A Self-Organizing Map Approach to Characterizing Complex Environmental Mixtures for Environmental Health Research". The NIEHS Exposure Science Exposure Science and Exposome Webinar Series. April 21, 2017
The complexity and dynamic nature of environmental pollution creates many challenges for health investigators seeking to illuminate health effects involving exposure to complex environmental mixtures. Identifying relevant mixtures, defining which are most important, and estimating health effects are some of the various challenges presented by this area of research. This talk will introduce the 'environmental mixtures problem' and then describe an approach that was found useful for research in this area -- the self-organizing map (SOM). This will entail a description of the SOM algorithm and its application to develop 'mixture' classification systems that can support research involving complex environmental mixtures. Application of the SOM will be illustrated using a variety of environmental data sets -- highlighting both benefits and limitations. Finally, this talk will demonstrate how to use SOM results epidemiologically in the context of an acute health effects study of air pollution. At the end of this talk viewers will have a better appreciation of the challenges presented by complex environmental data and become aware of an appealing tool to add into their 'mixtures' toolkit.
For more information on the series please see: https://www.niehs.nih.gov/news/events/pastmtg/2017/self-organizing-map/index.cfm