Course Sequence - MSPH in Epidemiology
Fall 1
Includes 10 credit hours of required courses and variable credit hours of RSPH core courses or electives.
This course is designed to teach students the fundamentals of applied statistical data analysis. Students successfully completing this course will be able to: choose appropriate statistical analyses for a variety of data types; perform exploratory data analyses; implement commonly used one and two-sample hypothesis testing and confidence interval methods for continuous variables; perform tests of association for categorical variables; conduct correlation and simple linear regression analyses; produce meaningful reports of statistical analyses and provide sound interpretations of analysis results. Students will be able to implement the statistical methods learned using SAS and JMP software on personal computers.
The lab portion of BIOS 500 is designed with two purposes in mind: 1) to illustrate concepts and methods presented in the lectures using hands-on demonstrations and 2) to introduce SAS, a widely used statistical software package, as a data analysis tool. By the end of the semester, you should be able to produce and interpret statistical output for methods learned in BIOS 500 lecture.
Prerequisite/concurrent: BIOS 500. Emphasizes the concepts and premises of the science of epidemiology. Methods of hypothesis formulation and evaluation are stressed. Techniques for quantifying the amount of disease (or other health indicator) in populations are introduced, followed by discussion of epidemiologic study designs useful for identifying etiologic factors and other relevant correlates of disease. Students gain facility with the calculation of basic epidemiologic measures of frequency, association, and impact. The concepts of random variability, bias, and effect modification are examined in detail. The use of stratified analysis, including Mantel-Haenszel techniques, is explored. Inferences from study results are discussed. Students are required to analyze and critique studies from the current medical and scientific literature.
Online Asynchronous. 1 hour online module addressing 4 of the 12 CEPH required Foundational Knowledge items. The module will begin with an introduction to a "Public Health Perspective followed by the 4 items of foundational knowledge.
Spring 1
Includes 9 credit hours of required courses and variable credit hours of RSPH core courses or electives.
Prerequisites: BIOS 500 or permission of instructor. For EPI students Only taken in the spring semester of their first year. The course covers fundamental concepts in applied simple and multiple linear regression analyses, one- and two-way analysis of variance and binary logistic regression. Concepts in survival analysis will also be introduced. Students will learn when and how to apply these methods. The emphasis will be on practical data analysis skills rather than statistical theory; however, wherever possible and feasible, mathematical details of regression models will be presented. In-class data analysis examples will employ SAS and R software. Homework assignments, quizzes and exams will include data analyses using SAS and R, as well as other questions designed to reinforce concepts and assess foundational competencies. Teaching assistant office hours will consist of organized review/recitation sessions, and will also include opportunities for student questions.
Department of Biostatistics and Bioinformatics
The purpose of this course is to provide students with practical skills and knowledge for designing, starting and implementing epidemiologic studies in research and practice.
Department of Epidemiology
Prerequisites EPI 530, BIOS 500, EPI 534, and BIOS 591P concurrent. MSPH and PhD students only.
This course builds on the fundamental epidemiologic concepts introduced in EPI 530: Epidemiologic Methods I. Specifically, causality, bias (including confounding, information bias, and selection bias), and concepts of mediation and interaction will be revisited in greater depth. By the end of the course, students will be able to do the following: formulate research questions to evaluate causality; evaluate the strengths and limitations of epidemiologic studies; assess how the strengths and limitations of a study affect interpretation of study results; utilize epidemiologic methods to address confounding; identify epidemiologic methods to address selection bias and information bias; and calculate measures to assess interaction.
Department of Epidemiology
PUBH students will join students from health professional programs across the Woodruff Health Sciences Center to receive didactic training to perform effectively on interprofessional teams and to apply leadership and management principles to address a relevant public health issue. Interprofessional teams will compete in a health challenge competition designed to address public health and clinical issues of importance to the Atlanta community.
Fall 2
Includes 4 credit hours of required courses and at least 5 credit hours of RSPH core courses or electives.
Prerequisites: EPI 530, 533/534, 539/540/545, BIOS 500, and 591P. Covers concepts, methods, and application of key mathematical modeling approaches used to evaluate multivariable data from epidemiologic studies: logistic regression, Cox regression, collinearity, modeling strategy for determining a best model, goodness of fit, and ROC curves. The course also teaches a broader philosophy and approach for constructing the appropriate models for answering the question under study.
Spring 2
Includes 4 credit hours of required courses and variable credit hours of RSPH core courses or electives.
EPI 530, 545, and 550 and/or instructor permission.
This course covers epidemiologic concepts in further depth than previous methods courses and provides an overview of advanced topics in the analysis of epidemiologic data. The course reviews basic concepts behind cohort studies, and introduces students to fundamental survival analysis concepts, including risk and survival, hazards, competing risks, cause-specific and sub-distribution risk, risk difference, and risk ratio estimators. Generalized linear models for conditionally and marginally adjusted risk differences and ratios, as well as methods for correct variance estimation. Concepts of time-dependent confoundinng, and methods that can be used to analyze complex longitudinal data (IP weighting, marginal standardization). This is a required course for students in the MSPH and PhD Epidemiology program.
Department of Epidemiology
An Applied Practice Experience (APE) is a unique opportunity that enables students to apply practical skills and knowledge learned through coursework to a professional public health setting that complements the student's interests and career goals. The APE must be supervised by a Field Supervisor and requires approval from an APE Advisor designated by the student's academic department at RSPH.
Department of Epidemiology
Enables students to apply the principles and methods learned in an academic setting through the preparation of a monograph that embodies original research applicable to public health, incorporating a hypothesis that has been successfully evaluated with appropriate statistical and epidemiological techniques and is potentially publishable and has public health impact.