Call Number | 15685 |
---|---|
Day & Time Location |
M 2:30pm-5:20pm LL201 Armand Hammer Health Sciences Center |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | Christopher N Morrison |
Type | LECTURE |
Method of Instruction | In-Person |
Course Description | Spatial epidemiology is the study of geographic distributions and determinants of health in populations. The goal of this class is to introduce students to relevant theory and methods, in order to provide the foundational skills required to understand and critically analyze spatial epidemiologic studies. The course emphasizes spatial epidemiology as a sub-discipline of epidemiology while acknowledging the many scientific disciplines that shape it, including biostatistics, cartography, criminology, demography, economics, geography, psychology, and sociology. We begin by defining spatial epidemiology and exploring these multi-disciplinary roots, with particular regard to the theoretical causal mechanisms that provide a bridge between social and physical environmental conditions and population health. We then provide a basic overview of geographic information systems and their utility for descriptive spatial epidemiology—including data visualization and cluster detection—before demonstrating how to incorporate spatial structures within conventional epidemiologic study designs to examine associational and causational relationships between environmental conditions and health outcomes. Class readings describe advances in theory and methods for spatial epidemiology and related disciplines, as well as concrete examples of applications for communicable disease, non-communicable disease, and injury epidemiology. This course is intended for doctoral and 2ndyear MPH students. |
Web Site | Vergil |
Department | Epidemiology |
Enrollment | 20 students (20 max) as of 9:14PM Wednesday, November 20, 2024 |
Subject | Epidemiology |
Number | P8416 |
Section | 001 |
Division | School of Public Health |
Open To | GSAS, Public Health |
Note | Other: EPIDP8438 strongly recommended. |
Section key | 20243EPID8416P001 |