Courses Taught by Andrew Brouwer
EPID602: Epidemiologic Data Analysis
- Graduate level
- Residential
- Winter term(s) for residential students;
- 3-4 credit hour(s) for residential students;
- Instructor(s): Elizabeth Levin-Sparenberg, Andrew Brouwer, (Residential);
- Offered Every Year
- Prerequisites: Epid 600, and EPID 639, or permission of the instructor.
- Description: A practicum in epidemiologic data analysis designed to integrate and apply concepts learned in previous biostatistics and epidemiologic methods courses. Students learn practical skills to analyze and interpret epidemiologic data with continuous and dichotomous outcome variables through lectures and hands-on exercises.
- Syllabus for EPID602
| Department | Program | Degree | Competency | Specific course(s) that allow assessment | EPID | General Epidemiology | MPH | Describe population patterns of health-related risk factors and health-related outcomes in terms of person, place, and time | EPID600, EPID602 | EPID | General Epidemiology | MPH | Compare the relative strengths and weaknesses of common epidemiologic study designs (e.g., cross-sectional, cohort, case-control, randomized experiments) | EPID600, EPID602 | EPID | General Epidemiology | MPH | Interpret the impact of bias, confounding, and effect modification on causal inference in epidemiologic research | EPID600, EPID602 | EPID | Clinical Research-Epidemiology | MS | Analyze research data and interpret these results from a population health or clinical-translational perspective | EPID602, BIOSTAT522 |
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EPID703: Applied Infectious Disease Modeling
- Graduate level
- Residential
- Summer term(s) for residential students;
- 1 credit hour(s) for residential students;
- Instructor(s): Andrew Brouwer (Residential);
- Prerequisites: None
- Advisory Prerequisites: Experience with modeling or good quantitative background, including statistics and differential equations; familiarity with R software.
- Description: Infectious disease modeling is increasingly being used to inform policy, practice, and research. This course will provide an introduction to the epidemiological and mathematical concepts underlying infectious disease modeling as well as the application of these concepts through hands-on model implementation.