|
Our course
in spatial epidemiology targets graduate and advanced undergraduate students
with backgrounds in epidemiology and public health for advanced training in
spatial epidemiology. Prerequisites are introductory probability theory and
some knowledge of biostatistics. The course theme is the inference of
disease processes from spatial disease pattern. The course consists of approximately 24 instructional hours and 24 computer lab hours. Examples provide the focus for each topic studied, and students are expected to conduct a spatial analysis project for presentation at the end of the course. Web-based instructional materials are used to support distance learning, and are keyed to appropriate software tools such as ArcView, S-Plus, Stat!, GeoMed, and Gamma. However the course is not "software-driven": instead, appropriate software is used for addressing the instructional objectives, as indicated in the course syllabus, which is being modified in consultation with several expert project consultants.
|