Population Health Data Analysis Courses

Courses open for registration

Core Courses

Epidemiological Statistics

This is a basic course in epidemiology, which also covers a variety of analytic topics not commonly addressed in elementary statistics courses. This course will introduce students to the field of epidemiology. Students will critically evaluate articles in the epidemiologic literature and examine epidemiologic methods including:

  • data collection
  • study design and statistical analysis
  • ratios
  • relative risk
  • contingency tables
  • logistic and Poisson regression
  • measurement error and exposure misclassification
  • imputation of missing values
  • multilevel regression models in epidemiology
Population Health and Geographic Information Systems (GIS)

In this course, students will learn about:

  • the geographic nature of population and public health
  • how geographic data are incorporated into health research
  • key considerations in spatial analysis
  • the applications of Geographic Information Systems (GIS) to health research and population and public health

Throughout the course, students will gain hands-on experience working with a wide range of spatial data and analysis methods using ArcGIS.

Working with Administrative Data

This course examines the basics of what administrative data are:

  • where they come from
  • how they can be used for research
  • what the data produced for research projects look like
  • the skills needed to work with them
  • basic statistical analysis of these data

This course also provides an overview of ethics and privacy issues related to research uses of administrative data.


Elective Courses

Health Services Program Monitoring and Evaluation

This course provides hands-on, project-based instruction on the concepts, processes and tools for monitoring and evaluating health services and programs. It covers engaging stakeholders; developing evaluation and monitoring questions; theories of change and logic models; selecting indicators and data collection methods and tools; reporting; and ethics and quality assurance in monitoring and evaluation.   By the end of the course, students will have developed an evaluation of a health service or program of their choice in order to make recommendations for improvements and facilitate decision-making in their organization.

We will explore a variety of monitoring and evaluation approaches and discuss standards of practice, ethical considerations, and continuous learning in monitoring and evaluation.  Special topics on cultural competencies will also be covered. 

Longitudinal Analysis and Multi-level Modelling of Population Health Data

This course will provide you with an introduction to—and hands-on experience specifying—multi-level modeling and longitudinal analysis. You will gain an understanding of different types of approaches including:

  • time varying and invariant predictors
  • multivariate and multi-population models with different outcomes
  • missing data, errors in measurement and measurement misclassification

This course is designed to serve the needs of researchers who will analyze and model longitudinal data in population health research.

Spatial Epidemiology and Outbreak Detection

This course provides an introduction to methods in spatial epidemiology and outbreak detection. The focus is on application rather than theory: this is not a course in spatial statistics.

The course is structured sequentially to move from spatial exploration of health data, to quantifying spatial patterns and clusters, to spatial exposure assessment and, finally, to methods for assessing risk.

Broadly, the spatial epidemiology part of the course focuses on:

  • assessing exposures through the use of a geographical information system (GIS)
  • conducting small area health studies (ecological models)
  • incorporating spatial parameters into models for individual health analyses.

The outbreak detection part of the course focuses on visualization of spatial data, disease surveillance and the use of spatial scan statistics in cluster detection.

 

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