ldecola.net/edu/umbc/health/syllabus_679.html
Meets fortnightly, 2011 Sept 10 to Nov 19, 9:00-11:30 AM
Location: Shady Grove Kendall 3215
| DATE | TOPIC | LAB | READING* |
ASSIGNMENT |
|---|---|---|---|---|
| Sep 10 | Epidemiology | Counts, proportions, and risk | Epidemiology
Relative risk |
|
| Sep 24 | Health dynamics | Measles data Growth simulation |
Time series | 1. Temporal |
| Oct 8 | Health events | Asthma cases | Point patterns | |
| Oct 22 | Gridded data | Land cover and plague | ESRI help | 2. Point pattern analysis |
| Nov 5 | Areal data | Lyme disease | ||
| Nov 19 | Presentations | 3. submit by Nov 17 present on Nov 19 |
LDECOLA@COMCAST.NET
DATA to Insight, Reston VA
Phone: 01 703 709-6972
hours: 10:00-18:00 Eastern Time (GMT-5)
Be familiar with fundamental epidemiological variables
Understand simple dynamic processes relevant to public health
Make and interpret spatial data about health events and rates
Be able to manage basic public health datasets
Interactive presentations
In-class lab exercises
Three assignments
Readings
Final project presented in the last class
ArcGIS
Spreadsheet (e.g. Excel)
R language (recommended)
*We'll generally use Wikipedia articles and other public domain assets. Here are a few books I find useful:
Bivand, R., E. J. Pebesma, et al. (2008). Applied spatial data analysis with R. New York, Springer. Challenging text but with many excellent datasets.
Ellen K. Cromley and Sara L. McLafferty (2011) GIS and Public Health, 2nd ed, NYC: Guilford Press, ISBN 978-1-60918-750-7. Excellent reference in a new edition.
Haggett, P (2000) The Geographical Structure of Epidemics Oxford: Oxford Univ Press. Compact but broad survey by an elder in the field.
Stolley, P D and T Lasky (1995) Investigating disease patterns: the science of epidemiology New York: Scientific American Library, WH Freeman. Lavishly illustrated and clearly written.
Waller, L. A. and C. A. Gotway (2004). Applied spatial statistics for public health data. Hoboken, N.J, John Wiley & Sons. A comprehensive text with many useful datasets.
