HLSC 2003: Introduction to Epidemiology

Dr. Currie designed this course to teach students the fundamental principles, concepts and methods of epidemiology, and has taught the course for the past 10 years at the University of Lethbridge. Dr. Currie’s goal in this course is to teach students to confidently read, understand, and critique epidemiologic studies in the areas of chronic disease and infectious disease.

Students will learn how key epidemiologic studies are developed, implemented, and analyzed including cross-sectional, ecological, case-control, and longitudinal designs; as well as randomized controlled trials and systematic reviews. Students will also learn to read, interpret, and understand the basic analytic measures produced by epidemiologic studies. By the end of this course, students will be able to:

- Describe fundamental principles, concepts, and descriptive epidemiologic measures (e.g., incidence, prevalence, mortality rates, attack rates, years of life lost).

- Identify and describe epidemiologic study designs and analytic measures (e.g., odds ratios, relative risks, sensitivity, specificity).

- Understand ethical principals in human health research.

- Review, assess causality, and critique epidemiologic studies.

PUBH 4003/5003: Advanced Epidemiology

Dr. Currie created this course to move students beyond the basics to acquire more advanced skills in epidemiologic study design, implementation, and analysis. The emphasis in this course is to move students from users of epidemiologic research to informed scientists who can independently design and carry out studies.

The course includes a 2-hour lab. Through individual and group assignments students will gain the hands-on experience needed to design epidemiologic research; the epidemiologic field methods required to support the validity, precision, and management of data collected; and the skills needed to interpret data and write skilfully about epidemiologic research in scientific journals, the private sector, and the public sector.

Dr. Currie teaches adapted versions of this course at undergraduate, Masters’ and PhD levels. All students complete the course together in one class, but receive assignments and exams of varying complexity depending on the level they have registered in (PUBH 4003, 5003, or 7003).

Prerequisite: A university-level introductory epidemiology course.

PUBH 5500: Biostatistics II

Dr. Currie developed this advanced course to teach students to map key biostatistical techniques onto the epidemiologic study designs they have learned in Introductory and Advanced Epidemiology. The course begins with an overview of linear, logistic, multinominal, and ordinal regression. Next, students learn how to analyze survival data using Cox regression, and cost/count data using general linear models (e.g., Poisson regression, negative binomial regression).

The course then moves to the analysis of experimental and longitudinal designs with an emphasis on the application of general estimating equations (GEE) and random effects models (REM) to clustered and time-dependent outcomes.

Throughout the course, students will learn how to apply cubic splines, quadratic terms, and other forms of transformation to address non-linearity; and bootstrapping to address non-normality across each regression method covered. Students also learn to how analyze mediators and effect modifiers across a variety of regression methods, and advanced methods to detect and deal with confounding (e.g., DAGs, propensity scores) and missing data (e.g., multiple imputation) in observational and experimental designs.

The course concludes with learning the techniques needed to analyze complex data that has special features such as multistage cluster sampling or inverse probability weighting. This course includes a 2-hour lab each week. Dr. Currie places a strong emphasis on the application of biostatistical techniques throughout the course with practice exercises in each lecture and group assignments in each lab using the Stata and R computer packages.

This course is open to students enrolled in Master’s, PhD or graduate certificate programs at the University of Lethbridge, and can be completed at the 5500 or 7500 level.

Prerequisite: Biostatistics I