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Course Description

This course deals with health data involving both space and time. There are three main approaches that we will study:
  • When data represent infectious disease cases in a particular region, we will use compartmental models, such as the S-I-R (Susceptible, Infections, Removed) model and its generalizations.
  • When data represent environmental factors taken at irregularly spaced sites, we will use kriging and its generalizations.
  • When data represent disease cases in predefined regions (e.g., counties) we will use conditional autoregressive models across time.
Throughout the course, we will use COVID-19 data for illustration.

Course Outline

  • Infectious Disease Modeling
  • Introduction to Spatio-Temporal Models
  • Fitting Spatio-Temporal Models
  • Disease Mapping in Space and Time

Learner Outcomes

  • Analyze the spread of diseases across time
  • Build and analyze models to assess the health of populations across time and geographic regions
  • Communicate results of spatial and spatio-temporal models applied to health data

Prerequisites

GEO5610 - Spatial Epidemiology and Disease Mapping or equivalent experience.

Duration

30 Hours | 5 Days or 10 Nights
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