Introduction to Space-Time Disease Surveillance (HGEO 103)
The video below gives a preview of the course.
This course provides participants with an understanding of different methods and associated statistical concepts involved in space-time disease surveillance. The course focuses on spatial analysis of disease data in a GIS environment, spatial statistics, and scenarios for cluster analysis and cluster detection.
This course has four key learning objectives:
- To describe what disease surveillance is and how it fits into spatial epidemiology
- To identify how and for what purposes space-time disease surveillance methods are used
- To use SaTScan software for temporal, spatial and space-time surveillance
- To summarize common issues related to statistical surveillance
The training will cover the following:
- Introduction and basic concepts
- Introduction to surveillance
- Cluster detection and scan statistics
- Data file set-up and getting started
- Factors affecting space-time surveillance methods
This course has been redesigned from its original inception as a face-to-face workshop to broaden knowledge mobilization in this subject area. Course delivery includes voiceover Power Point information with associated reference guides, web links and online tutorials using sample data sets accessed within a zipped file.
The self paced course is divided into 7 modules, followed by 4 data analysis tutorials and related resource links. Each module varies in review time from 10 to 40 minutes with a total training time of approximately 2 hours 45 minutes. The 3 tutorials, that require you to download free SaTScan software for use with the training dataset provided, can be completed within 1 ½ to 3 hours – depending on individual skill level.
You may wish to complete the modules all together or as separate training sessions over a period of several days or weeks to best fit your schedule or learning preferences.
Colin Robertson has a PhD in Geography from the University of Victoria. He is presently an Assistant Professor at Wilfrid Laurier University. His current research interests include exploring the use of volunteered geographic information in environmental research, spatial and space-time modelling of emerging disease risk, and spatial model validation techniques.
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