We currently offer three self paced courses and two best practices resource documents to support researchers in health geomatics and use of specialized statistical software.

Introduction to Applied Geospatial Skills for Spatial Epidemiology Course

This course provides pre-requisite skills for entrance into PHDA 04 Spatial Epidemiology and Outbreak Detection Course.

The goal of HGEO-106 is to help you gain confidence in working with GIS, especially as it pertains to key concepts in spatial epidemiology. The applied, hands-on focus provides you with a specialized learning experience of using GIS technology within a public health context. The course is focussed on the spatial nature of data, the tools and functions used to interact with spatial data, the relationships between spatial and non-spatial data, and the associated products that can be produced including maps, graphs, and statistics.  Spatial Data comes in a variety of file formats, and this course will cover the ones you will commonly work with in the PHDA 04 course or other geospatial contexts, most notably the shapefile.

Course content has been designed to be repeatable so that you can practice and develop new skills at your own pace.  The videos, course materials, and associated reference documents can be readily accessed as a self-paced tutorial at any time to refresh your skills and knowledge.

Completion of this course will equip you with the foundational knowledge and skills required to successfully enroll in the Spatial Epidemiology and Outbreak Detection (PHDA 04) course. It can also provide useful introductory training for individuals looking to gain experience with basic geospatial tools used in spatial epidemiology studies.

Course Format

The course includes three modules that focus on the analytical functions, tasks, and the ‘why’ behind them. The actual health outcome being modelled and analyzed plays a secondary role to the underlying mechanisms used within the ArcMap functions. Each module includes a micro lab and follow up quiz to solidify your  understanding of key concepts presented and practiced in the lab.

The micro labs have been built to enhance your confidence and help you gain experience in a variety of geospatial tools. All labs consist of a video walk-through, and a step-by-step document to aid your use of the geospatial tools presented. Each lab has one quiz that follows the steps presented very closely with subtle variations along the way. Quizzes are designed to allow you to become comfortable completing tasks and familiar with GIS terminology. 

Repeating these exercises will be invaluable towards developing your GIS skills and future enrollment in the PHDA 04 course and/or related spatial epidemiology exploration and study.

Module 1

This module focusses on exploratory data analysis. This involves working with a health outcome variable to understand the dataset, the relationship between the dataset and its visual representation, and the associated techniques required for this analytic work.

Upon completion of Module 1, you will be able to:

  • Understand basic information about using the Secure Analytics Environment (SAE)
  • Maintain compliance with your Data Access Request (DAR), Engagement Agreement and Oath of Secrecy
  • Maintain compliance with the Data Innovation (DI) Program and Population Data BCs policies
  • Identify and report a breach promptly and correctly

Module 2

This module focusses on the tasks involved in a spatial exposure assessment. The assessment itself isn’t the focus of the lab work completed in this module. Instead you learn and practise with the tools used in a spatial exposure assessment. The lab work examines spatial relationships and what the resulting datasets consist of and what they represent.

Upon completion of Module 2, you will be able to:

  • Prevent unintended disclosure of protected information by using correct Statistical Disclosure Controls (SDC)
  • Identify Safe vs. Unsafe statistics
  • Apply the Principles-Based Model to outputs for release from the SAE to prepare safe outputs for release from the SAE

Module 3

This module focusses on a gentle introduction to spatial autocorrelation and regression. Regression applied in a spatial environment can seem overwhelming so this lab is designed to explore these topics in order to communicate the concepts clearly.

Upon completion of Module 3, you will be able to:

  • Prevent unintended disclosure of protected information by using correct Statistical Disclosure Controls (SDC)
  • Identify Safe vs. Unsafe statistics
  • Apply the Principles-Based Model to outputs for release from the SAE to prepare safe outputs for release from the SAE

This course provides an introduction to GIS and Epidemiology

 Topics covered include:

- Introduction to GIS platforms
- Components of GIS and Spatial Data
- Mapping Health Data Using GIS
- Information Sources and Data Structures

This course provides an Introduction to Spatial Epidemiology.

Topics include:

- Introduction to Spatial Epidemiology
- Spatial Health and Covariate Data in BC
- Grouped Data & Ecological Study Design
- Postal Codes:The Basis of Spatial Exposure Assessment
- Spatial Exposure Assessment: Principles and Limitations
- Bias, Confounding & Exposure Misclassification
- Advanced Techniques in Spatial Epidemiology

This course provides an introduction to Space-Time Disease Surveillance.

Topics include:

- Introduction & Basic Concepts
- Introduction to Surveillance
- Cluster Detection and Scan Statistics
- Data File Set-up and Getting Started
- Factors Affecting Space-Time Surveillance Methods

This resource document provides an overview of key analytical issues and best practices when mapping health data including:

  • Working with point data
  • Working with line data
  • Working with area data
  • Study area boundary and edge effects
  • Cartographic fundamentals

This resource document provides a review of case studies using freely available space-time disease surveillance software. Software packages have been categorized based on the level of user expertise required to run them.

           ● Basic

           ● Intermediate

           ● Advanced