Global health policy and development depends on the nature and validity of evidence, which in turn depends on appropriate research methods and analysis. This course will cover instruction in epidemiologic research, including study design, measures of disease occurrence and disease association, the different sources of error in observational research, and a consideration of epidemiology as a tool to inform health policy. The course involves numerous practical real-life examples of these principles. Students will learn how to read and critique a published epidemiologic study, understand the basic methods of observational research, and appreciate the value of validated evidence in global health.
By the end of the course, the student will be able to:
- Describe the uses of epidemiology and the different types of epidemiologic studies
- Define variable types (e.g. exposure, outcome), and how they are measured
- Know the major measures of association and effect such as rate ratio, risk ratio, odds ratio, and confidence intervals
- Describe measures of public health impact such as population attributable risk
- Describe the relative merits of different study designs and the main analytic methods available to estimate disease association (outcome) with predictor variables
- Define the sources of error in epidemiologic research (chance, bias, confounding), cite examples of each, and enumerate methodological or statistical strategies to deal with them in both the design and analysis phases
- Know Hill's postulates of causation and be able to use these to critically analyze studies and evaluate causality.
- Critically analyze a published epidemiologic paper, citing strengths, weaknesses, and validity of the inferences made
- Understand principles of stratification, randomization, and blinding in interventional studies
- Overview of observational study designs: descriptive, ecological, case control, cohort. Journal article review: ecological and descriptive case studies
- Interventional studies: the randomized clinical trial (RCT); stratification and randomization methods. Journal article review: RCT case studies; clinical and community examples
- Designing an epidemiological research study. Hypothesis seeking vs. hypothesis testing, independent and dependent variables, sampling, sample size calculation, analysis plan.
- Validity, precision and error. Sources of error in observational studies: chance, bias and confounding.
- Methods to minimize error. Dealing with bias: study design, measurement, sampling, matching. Detecting and avoiding bias in case control studies; misclassification. Review a paper, examine bias
- Sample size; power calculations; matching; restricting. Perform sample size calculation
- Ethics of epidemiologic studies and clinical trials. Consent, assent, and ethics of cross-cultural investigation.
- Meta-analysis and systematic review.
Craig Steinmaus, MD, MPH
Lectures, seminars, independent study, and exams