GEOG 591
GIS for Analysis of Health

Welcome to GEOG 591 - GIS for Analysis of Health


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Quick Facts about GEOG 591

  • Instructor: Justine Blanford
  • Course Structure: Online, 10-12 hours a week for 10 weeks
  • Overview: Choosing and applying analytical methods for analyzing health and disease, including point pattern analysis, surface analysis, overlay analysis, cluster and regression analysis. Prerequisite: GEOG 484

    Geography 591 is an elective course for Penn State's Online Master of GIS. This section is being offered to students around the globe through Penn State's World Campus. It is a "paced" course, which means that there is an established start and end date and that you will interact with other students throughout the course. The course is 10 weeks in length (plus a required "Orientation Week" preceding the start of the course), at a rate of 1 lesson per week. The course is organized around six weekly projects and a more substantial term project pursued through all ten weeks of the course, with milestones through the term. Weekly assignments include associated readings, quizzes, and discussions about the readings, methods and tools used to analyze health and disease.

    This is a course about the process and application of statistical and spatial methods used to map, model and analyze health and disease. The techniques introduced are often mathematically complex, but while these aspects are covered in the course, the emphasis is on the choice and application of appropriate methods for the analysis of health and disease often encountered in applied geography as well as developing a framework in which to approach the analysis. Weekly projects are hands-on, using geographic information systems or other appropriate computational tools, so that students appreciate the practical complexities involved, but also develop an understanding of the limitations of these methods.

    Through the weekly projects, students acquire familiarity with use of a single method or family of methods in standard desktop tools, so that they can focus on aspects of that method and develop a thorough understanding of its potential and of its limitations and how the method(s) can be used for tackling a specific health or disease problem. Topics range across data surveillance and infrastructure planning, modeling vector-borne diseases, planning for recovery through an evaluation of healthcare accessibility, cluster analysis, predicting health outcomes, and responding to outbreaks and epidemics. The term project is intended to allow students to formulate a research problem in a topic area of their own choosing, to gather and organize appropriate available datasets, and to understand how a variety of methods among those covered in the course can be applied in combination to thoroughly explore real questions. Students will be asked to engage with their peers' work during the project planning stage. They will also be encouraged to consider developing customized tools to automate repetitive analysis tasks, if they have previous programming experience.