of North Carolina School of Public Health
EPID600/EPID160, Principles of Epidemiology for Public Health
Course content (enrolled students - please see the Sakai website)
The course is organized into topic modules (see below). Each lasts about a week.
A weekly 50-70 minute lecture provides an overview of the topic. These are available as online recordings with slide presentations and as Powerpoint slides with full text speaker notes.
Small group discussions
For students taking EPID600 on campus, a weekly 2-hour "lab" provides a summary of key points for each topic, presented by a teaching assistant, followed by a small group (6-11 students) discussion of a case-study. For students taking EPID600 online, monthly summaries by teaching assistants are presented as "live meetings" online. Small group discussions use an online discussion forum. The case studies are a major component of EPID600.
There are two take-home examinations, a midterm and a final examination. Examinations consist mostly of multiple choice questions, with a sprinkling of calculation and open-ended short-answer questions. Examinations are time-limited and designed to be answered without use of aids other than a calculator, but they are administered as open-book, open-note, open-web.
Aschengrau, Ann, and George R. Seage. Essentials of epidemiology in public health. Jones and Bartlett, 2nd edition, 2007. Victor J. Schoenbach. Understanding the fundamentals of epidemiology: an evolving text, www.epidemiolog.net is a free, on-line supplementary text.
All course materials other than the textbook are online. There is no coursepack to purchase.
All course information can be accessed through a Sakai course website. Most of this information is also available on this (open) website.
Introduction to epidemiology
Definition, uses, and features of epidemiology.
Assessing health in populations. Basic demographic concepts - birth, fertility, and mortality rates; age and sex-structure of populations and population pyramids. Dynamics of population growth and effects on age distribution.
Incidence and Prevalence
Measures of disease frequency in populations - cumulative incidence, incidence rate, prevalence, fatality rate, and age standardization. Denominators for rates and proportions.
Natural history of disease; Population screening
Nature of disease, concept of natural history, spectrum of disease. Requiremensts for effective population screening programs. Sensitivity, specificity, and predictive value.
Causal comparisons, counterfactual model of causal inference, counterfactual comparison and substitute population. Experimental and observational epidemiologic study designs. Clinical and community intervention trials, advantages of randomization. Issues of generalizability.
Features and characteristics of cohort (follow-up) studies. The concept of relative risk. Risk (cumulative incidence) differences and ratios, rate differences and ratios, attributable risk.
Case-control studies as a window into an underlying cohort. Odds ratios and their relation to cumulative incidence and risk ratios. Estimation of relative risk from case-control data.
Cross-sectional studies, Ecologic studies
Population surveys, illustrated with the National Health Interview Survey. Complex survey sampling. Characteristics, advantages and disadvantages, design, and analysis of cross-sectional and ecologic studies.
Sources of error in epidemiologic studies. Concepts of variability, reliability, internal validity, external validity, and bias. Random versus systematic error. The kappa statistic. Understanding selection bias.
Problems in measurement and classification, bias resulting from errors in measurement. Differential versus non-differential error mechanisms.
Multicausality and confounding
Revisiting the counterfactual model of causation. Confounding results from differences between the substitute population and the counterfactual comparison. Illustrations of confounding and ways to deal with it. Potential confounders vs. actual confounders.
Data analysis and interpretation, Causal inference
Role of assumptions and models in data collection and analysis. Importance of data management in epidemiologic studies. Issues in data analysis. Inferring causality from epidemiologic data. Bradford-Hill criteria for causal inference.
Students will hear a guest lecture (live or recorded) from Dr. David Weber and work through an online outbreak exercise.
Overview and Role of epidemiology in public health
Ten fundamentals of epidemiology. Several mega-determinants of current and future health, and the role of epidemiology in addressing them.
Updated 7/24/2004vs, 5/24/2005vs, 8/22/2009vs, 5/14/2017