Directed Reading: Spatial Epidemiology: Intro Methods and Applications


Course Number
CHL7001H S1
Series
7000 (Reading Courses & Research Projects)
Format
Lecture
Course Syllabus
View Syllabus
Course Instructor(s)
Erjia Ge

Spatial epidemiology is an important branch of epidemiology for the study of spatial distribution of diseases and their determinants. Spatial data analyses and geographical information system (GIS) have provided insights into the spatial dependency and processes of disease outbreaks and transmissions.

This is an introductory course regarding basic concepts, spatial analysis methods, and tools available for spatial epidemiological studies. After this course, students will be able to:

  • have basic understanding of spatial concepts, GIS terminology and methods used in spatial epidemiological studies;
  • conduct exploratory spatial data analysis for disease mapping and risk factor analysis;
  • obtain strategies for designing a formal spatial epidemiological studies;
  • employ spatial statistic approaches to inform/generate policy recommendations disease control and prevention;
  • explore the process for co-authoring a study manuscript in spatial epidemiology.

The course includes 8 lectures and 3 Guest Lectures with specific topics in Application of GIS and Spatial Methods in Malaria, Public Health Practice, and Social and Health Behavior Problems. Topics will change by years to introduce students the cutting-edge methods and technologies used in current issues. Each lecture will be paired with tutorials, including 2 GIS workshops in Map and Data Library at Robarts Library. The two GIS workshops will lead students a new journey for a direct understanding of spatial data structure, representing health data with maps, geographical information systems (GIS), and how to obtain health and geospatial data from the University and open resources.

Through this course, students will have a relatively complete understanding for population health and space. In addition, students will be able to conduct basic spatial data analysis using ArcGIS, R, and GeoDa. All these would enable students to either continue advanced studies in spatial disease modeling or work as a spatial epidemiologist in public health agency, government, or research institutes related to health.

General Requirements

No pre-requisites. This is an introductory course open for Master students with NULL ideas in spatial thinking and GIS, but interested in health issues with spatial perspectives.