M.P.H. in Epidemiology Curriculum

An overview of American healthcare systems, as well as their administration and financing. Focuses on major stakeholders in the systems, issues driving reform efforts, and the use of community-based needs assessment.

Covers major environmental detriments to human health, including sources of exposure, etiology of environmental disease, and mortality. Students will have the opportunity to tour a local public works facility.

What behavioral and social factors contribute to health? Study socio-cultural conditions in disease etiology, the role of social conditions and policy in addressing public health problems, and individual-, community-, and technology-based solutions.

Applying public health concepts from earlier courses. Examining how they can translate into policy and intervention.

Presents fundamental statistical skills employed in clinical and public health research. Covering basic probability, common distribution, inferential statistical approaches, and more. Students learn how to interpret and present data in professional publication.

Introduces principles and practices of epidemiology, provides a population-based perspective on health and disease. Learn basic measurements of frequency and association, methods of describing, monitoring, and studying health and disease in populations.

A structured public health practice experience applying knowledge and skills learned in the classroom to a population-based public health problem.

Builds on Introduction to Epidemiology, expanding on concepts and problems of epidemilogic reasoning, and the design and analysis of epidemilogic research. Lecture topics include reliability and validity, causal inference, stratification and modeling techniques, and more.

Advanced epidemilogic methods including longitudinal data methods, regressing techniques, propensity scores, and more.

First part of a two-semester sequence. Covers descriptive statistics, probability, estimation, hypothesis testing for one and two samples, non-parametric methods and introduction of hypothesis testing with categorical data.

Second part of a two-semester sequence. Covers hypothesis testing with categorical data, multiple and logistic regression, and statistical methods used in studies and clinical trials like life table analysis and logistic analysis.

Teaches application of basic SAS programming skills to data management and analysis, exposes students to a range of computing techniques for management, organization, analysis, and presentation of health science data.

See catalog for full list of elective courses.