Course Descriptions
Core Courses (Required of all Students)
EPID-5001 Epidemiology I: Principles of Epidemiology ( 3 credits)
Epidemiology overview and history; distributions of disease by time, place and person; association and causality; ecological studies; cross-sectional studies and surveys; case-control studies; analysis of case-control studies; types of bias in case-control studies; cohort studies; analysis of cohort studies; bias in cohort studies; population attributable risk; confounding factors; effect modification (interaction); analysis for confounding and interaction; multivariate analysis; sensitivity, specificity and screening; public health practice and prevention; special issues in cancer epidemiology, infectious disease epidemiology and genetic epidemiology. This course includes a discussion session.
EPID-5002 Epidemiology II: Advanced Methods in Epidemiology ( 3 credits)
This is a core course required for all students in the M.S. in Epidemiology program.
EPID-5003 Biostatistics I: Introductory Biostatistics ( 3 credits)
This course is designed for introductory biostatistical theory and application for students pursuing a master’s degree in fields outside of the Department of Biostatistics, Bioinformatics, and Biomathematics. Students first learn the four pillars of exploring and displaying data appropriately, exploring relationships between two variables, issues of gathering sample data, and understanding randomness and probability. On these pillars, students then can develop the platform for statistical inference including proportions and means, multiple regression, and ANOVA.
EPID-5005 Biostatistics II: Applied Biostatistics ( 3 credits)
This course is designed for applied biostatistical theory and application for epidemiology. Students are expected to have understanding of EPID 503 material. More advanced modeling for linear models, general linear models, ANOVA and ANCOVA, logistic regression, survival analysis, and sample size planning are included.
EPID-5006 Computer Software Lab II ( 1 credit, lab)
This is an advanced course in statistical software and computation for applied applications of biostatistics methods in epidemiological research.
EPID-5007 Introduction to Social and Behavioral Health & Health Disparities Research (3 credits)
This is a core course required for all students in the M.S. Epidemiology program. The course will be divided into two modular courses per semester: (A) Part I: Health Behavior Theory, Research Design and Methods; and (B) Part II: Principles and Practice of Health Disparities Research. This course introduces students to individual-, interpersonal-, and community-level theories of behavior commonly used in public health science, as well as to methods for instrument development, testing, and measurement of health behavior from multiple perspectives. It also introduces students to concepts of health disparities and health equity, provides a broad overview of existing health disparities in the US and globally, and introduces students to quantitative methods in health disparities research.
EPID-5008 Introduction to Cancer Epidemiology ( 1.5 credits)
This course provides students with an overview of the dimensions of the public health impacts of cancer on populations. Through didactic and participatory instruction, students will learn about the U.S. and global distributions of specific types of cancer, gender, racial/ethnic, and other disparities, sources of the data, and methods of cancer surveillance, diagnosis, treatment, and follow-up care. This is a core course required for all students in the M.S. in Epidemiology program.
EPID-5009 Introduction to Infectious Disease Epidemiology (1.5 credits)
This course provides an introduction to the basic principles of infectious disease epidemiology focusing on emerging and re-emerging disease agents that affect medical care and public health, e.g. viruses, bacteria and eukaryotic parasites, with special emphasis on how these infections cause or exacerbate health disparities locally and globally. This is a core course required for all students in the M.S. in Epidemiology program.
EPID-5010 & 5011 Research Ethics & Professional Development Seminar (1 credit)
This course consists of two main areas of focus: 1) ethics and the responsible conduct of scientific research and 2) exposure to a variety of topics in epidemiology – with consideration of health equity and disparities. Examples of past talks include Stigma: Global Mental Health, AI Tools in Research and Ethical Use, and Work, Retirement, and Aging.
EPID-9999 Thesis Research
Students must choose between a thesis or capstone to fulfill their graduation requirements. The thesis is a year long course. A candidate for the Master of Science in Epidemiology is required to perform a study, a design of investigation, under the direction of a faculty advisory committee. All master’s students must identify an advisor/mentor who will help form the thesis advisory committee comprising a total of 2 faculty. A written thesis is required to be presented, as a poster on the established annual research symposium day for the Epidemiology Program. The thesis committee and mentor/advisor must sign off on the Master’s Thesis Reviewers Report once thesis has been successfully completed.
EPID 5014 Capstone (3 credits) Students must choose between a thesis or capstone to fulfill their graduation requirements. Graduate students who wish to to integrate and apply practical skills learned through their epidemiological coursework. This project is based on interest, exposure and experience in their chosen concentration. Students are facilitated by faculty advisors. After the writing is finished in the spring semester, students will make an oral or poster presentation.
Selected Electives
EPID 5015 Meta-Analysis for Public Health and Medical Research (3 credits) Meta-analysis is a statistical tool to combine findings from multiple independent studies. In recent years, it has been increasingly used in many scientific fields. It plays an important role for improving precision of research results and resolving seemingly contradictory research outcomes. This course will introduce meta-analysis methods commonly used in public health and medical research. The course is designed to help students understand the statistical techniques used to conduct quantitative meta-analyses. Students will learn to systematically synthesize evidence from multiple studies, critically assess study heterogeneity and bias, and apply appropriate statistical models for quantitative data pooling. The course covers fixed-effect and random-effects models, forest plots, meta-regression, publication bias, and the use of software tools such as R and SPSS. Emphasis is placed on practical applications and the interpretation of findings.