SSJ30360
SPATIAL ANALYSIS FOR HEALTH
- Department
- Sustainability & Soc'l Justice
- Terms offered
- 1
- Data refreshed
- Jun 27, 2026
Description
This graduate-level course provides an introduction to Geographic Information Science and its application in public health research and practice. Each week incorporates a lecture and a computer lab that focuses on a health-care issue. Topics covered may include mapping disease rates, analyzing health outcomes, access to health care and health resources, environmental justice, exposure assessment, and social determinant of health. Students will learn how to visualize and analyze health-related and demographic data, and how to geocode tabular data. They will have the opportunity to develop their GIS skills using commercial and open source GIS software and to conduct their own independent research on a topic of their interest. Formerly IDCE 30360. Students who have already passed IDCE 30360 will not receive credit for SSJ 30360 and should not take this course.
Syllabi
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Offering history & forecast 2025
2025
| Year | Fall | Spring | Summer | Intersession |
|---|---|---|---|---|
| 2030 | 2030 Fall: not enough history to forecast. | 2030 Spring: not enough history to forecast. | 2030 Summer: not enough history to forecast. | 2030 Intersession: not enough history to forecast. |
| 2029 | 2029 Fall: not enough history to forecast. | 2029 Spring: not enough history to forecast. | 2029 Summer: not enough history to forecast. | 2029 Intersession: not enough history to forecast. |
| 2028 | 2028 Fall: not enough history to forecast. | 2028 Spring: not enough history to forecast. | 2028 Summer: not enough history to forecast. | 2028 Intersession: not enough history to forecast. |
| 2027 | 2027 Fall: not enough history to forecast. | 2027 Spring: not enough history to forecast. | 2027 Summer: not enough history to forecast. | 2027 Intersession: not enough history to forecast. |
| 2025 | 1 section | Not offered | Not offered | Not offered |
Future estimates combine recent offering frequency with detected multi-year cycles. Hover a cell for confidence and evidence; low-confidence estimates are marked with ~.
Meeting times
Most recent first- Tue, Thu, 10:25 AM–11:40 AM JC105 2025-1
- Fri, 4:15 PM–5:30 PM JC105 2025-2
| Term | Professor | Type | Credits | Enrollment | CRN |
|---|---|---|---|---|---|
| Fall 2025 | Yelena Ogneva-Himmelberger | Lecture | 1 | 13 of 20 enrolled | 23898 |