Description: This course covers applications of mathematical and computational modeling to behavior, social processes, and chronic disease. Methods include game theory, agent-based, and network modeling, and natural history models of chronic diseases. Students will learn to develop models in Python. Coursework includes computer lab exercises and a final modeling project.
Prerequisites: Enrolled in Epidemiology MS programs
Description: This capstone research project course is designed for Epidemiology MS students (30-credit or 48-credit CESM programs). Working with their mentor, students are expected to develop an original research project to address public health problems using epidemiologic methods.
Students will have the opportunity to apply what they learned in their coursework to important public health questions. Students will work with a faculty mentor to conduct a literature review, develop a research project, develop and implement an analysis plan, write up the results and discuss the implications of the findings, and present their work in the annual Epidemiology Poster Day.
Students are expected to begin their capstone project in their first term and complete it in the second term of their final year (or only, for one-year programs) of training (three credits per term, for a total of six credits). The Epidemiology Master’s committee will help students find an appropriate mentor. Details regarding the structure of capstone writing products and evaluation guidelines will be provided in the MS Student Handbook.
Learning Objectives: The learning objectives of and skills employed in this course are determined by the specific research project. The list below (which is not exhaustive) provides examples of learning objectives for this course:
1. Assess knowledge gaps in the scientific literature;
2. Develop a scientific research question designed to address a gap in the scientific literature
3. Identify appropriate data sources to address a research question;
4. Better understand the role of data in understanding public health problems;
5. Create a data collection instrument and/or collect data;
6. Analyze data (quantitative or mixed data – including both quantitative and qualitative) to test research hypotheses relevant to public health in a manner that reflects principles of epidemiology (e.g., study design, measurement, confounding, etc);
7. Generate appropriate data visualizations and/or presentations;
8. Communicate the significance, approach, and implications of epidemiological research in a written format appropriate for the target audience;
9. Complete research ethics training through the Program for the Education and Evaluation of Responsible Research and Scholarship (PEERRS). Two modules are required: Human Subjects Research Protections and Responsible Conduct of Research and Scholarship (RCRS).
