The Epidemiology Track provides you with the skills necessary to analyze public health trends, design and implement studies, and interpret the results for policy and program development. You also learn to investigate disease origins as well as prevention and intervention strategies at the individual and societal levels. Our program prepares you to take on leadership roles in clinical and population-based health research in government, health care institutions, and private industry.

You take coursework in epidemiology, biostatistics, and clinical outcomes research and you are required to take two elective classes in specialized areas of epidemiology. Electives are available in infectious disease, chronic disease, molecular, genetic, and environmental and occupational epidemiology. You complete a capstone project as your culminating experience.

Please note that while most students complete the MPH degree in two years, those in the Epidemiology Track who enroll in the spring terms should allow more than two years to complete the MPH program.

Track-specific Competencies

To make sure our students develop the skills necessary to be successful and productive in the field of public health, and especially in the area of epidemiology, we have developed a list of skills and content areas for the students in this specialty track:

  • Describe a public health problem in terms of magnitude, person, time, and place.
  • Calculate basic epidemiological measures.
  • Evaluate the strengths and limitations of epidemiological studies.
  • Interpret results of statistical analyses found in public health studies.
  • Critically synthesize the public health research and practice literature for a selected health topic.
  • Conduct an epidemiological and biostatistical data analysis.
  • Distinguish between a statistical association and a causal relationship using appropriate principles of causal inference.
  • Identify appropriate methods of study design, analysis, and data synthesis to address population-based health problems.
  • Identify circumstances under which non-randomized (observational) designs are the best approach to addressing important health-related knowledge gaps.
  • Recognize the assumptions and limitations of common statistical methods and choose appropriate approaches for analysis.
  • Use tabular and graphical methods to explain model results.