This course teaches the classical epidemiologic toolkit applied to infectious disease: how to design a study, measure disease and association, reason about bias and confounding, run surveillance, and investigate an outbreak. It gives IDEEEP students the core methods spine of epidemiology, taught with the reproducible-computing habits already used across the site.
The course syllabus is shown below.
Draft syllabus. This is a scaffold for the concentration. Course number, credit hours, dates, and specific assignments are placeholders and will be finalized before the course is offered.
Course title and instructors
Title: Applied Infectious Disease Epidemiology
Course Number: BIO 3xx (proposed; confirm with the Department of Biology)
Semester: TBD
Credit Hours: 3
Meeting Time: TBD
Course Director: Michael E. DeWitt, MS
Email: medewitt@wakehealth.edu or dewime23@wfu.edu
Course description
Infectious disease epidemiology rests on a core set of methods: choosing a study design, measuring disease frequency and association, separating real effects from bias and confounding, and turning surveillance data into action. This course develops that toolkit and applies it to infectious-disease questions. Students measure disease using incidence and prevalence, compute risk and rate ratios and attributable fractions, reason about study validity, and work through the outbreak investigation from case definition to attack rates. The course also covers screening and diagnostic test performance and introduces transmission and control. Analysis is done with reproducible-computing habits, connecting to the delay-distribution and diagnostic material the site already publishes.
Learning outcomes
Upon successful completion of this course, students will be able to:
- Choose an appropriate study design (cohort, case-control, cross-sectional, ecological, intervention) for an infectious-disease question and state its threats to validity
- Compute and interpret measures of frequency, association, and impact (incidence, prevalence, risk/rate ratios, attributable fraction)
- Reason about bias, confounding, and stratification, and apply them to real surveillance data
- Run a line-list outbreak investigation: case definition, epidemic curve, hypothesis generation, and attack rates
- Read and estimate epidemiologic delay distributions (incubation, latent, serial, generation) accounting for censoring and truncation
- Interpret screening and diagnostic test performance and its effect on surveillance
Textbook and other resources
There is no single required textbook. Recommended references include:
- Gordis L. Epidemiology. Elsevier.
- CDC, Principles of Epidemiology in Public Health Practice
- Selected primary literature on study design and outbreak investigation
Additional readings will be assigned throughout the course.
Site resources
This course draws on IDEEEP content pages as assigned readings and lab material:
- Epidemiological intervals
- Delay distributions and censoring
- Diagnostic testing
- Causal inference
- Logistic regression
- Generalized linear models
- Diagnostics and surveillance
- Research Tools and Methods
- Mathematical Biology
New concept pages on study designs, measures of association and impact, the outbreak investigation workflow, and surveillance systems are planned and will be linked here as they are published.
Course structure and schedule
This course meets over 15 weeks and combines lecture with applied exercises on real surveillance data. The schedule below is a draft outline of topics.
| Week | Topic |
|---|---|
| 1 | Introduction: what infectious disease epidemiology measures |
| 2 | Measuring disease: incidence, prevalence, and rates |
| 3 | Study designs I: cohort and case-control |
| 4 | Study designs II: cross-sectional, ecological, and intervention |
| 5 | Measures of association and impact |
| 6 | Error, bias, and confounding |
| 7 | Stratification and effect modification |
| 8 | Surveillance systems and case definitions |
| 9 | The outbreak investigation workflow |
| 10 | Epidemic curves, attack rates, and hypothesis generation |
| 11 | Delay distributions: incubation, latent, serial, generation |
| 12 | Censoring and truncation in interval estimation |
| 13 | Screening and diagnostic test performance |
| 14 | Introduction to transmission and control |
| 15 | Project presentations and wrap-up |
Note: Specific dates will be provided at the beginning of the semester. Topics may be adjusted based on class progress and student interests.
Grades and assignments
| Activity | Weight |
|---|---|
| Participation and discussion | 20% |
| Assignments and applied exercises | 30% |
| Exam(s) | 20% |
| Final project | 30% |
Final project: Students will carry out an epidemiologic analysis of an infectious-disease dataset of their choosing, stating the study design and its threats to validity, computing measures of association and impact, and reporting results with appropriate uncertainty.
Course policies
Attendance: Regular attendance is expected, particularly for discussion sessions. Please alert the instructor if you are unable to attend for any reason.
Late/Makeup work: Assignments are due on the dates provided. We recognize that extenuating circumstances arise, and assignments may be submitted up to 2 days late without penalty. If you need an extension, contact the instructor as soon as possible and before the due date.
Artificial intelligence: Artificial intelligence tools and large language models such as ChatGPT, Claude, and Gemini are now part of the academic and professional landscape and we encourage you to find ways to use them to enhance your learning. However, if you use these tools, you must cite your sources and provide a detailed description of the tools you used to complete the assignment. In no way can these tools take the place of your own work and understanding of the material. They should be used to supplement your learning, not replace it. You are ultimately responsible for your work including content and the use of valid citations and references. Using these tools without proper attribution is plagiarism and will be treated as such.
Department/School/University policies
Academic Integrity: Wake Forest University is committed to a culture of academic integrity. As a part of this community, you share the responsibility for creating a place of honesty, intellectual curiosity, and individual accountability. As you committed to with your honor pledge signature, you agree “not to deceive any member of the community; not to steal, cheat, or plagiarize on academic work; and not to engage in any other form of academic misconduct.” If you have questions about documenting your work, working with external sources, or working with peers on assigned work, consult with me as soon as possible. Instances of academic dishonesty will be referred to the Honor and Ethics Council.
Accessibility: Wake Forest University provides reasonable accommodations to students with disabilities. If you are in need of an accommodation, please contact me privately as early in the term as possible. Retroactive accommodations will not be provided. Students requiring accommodations must also consult the Center for Learning, Access, and Student Success (118 Reynolda Hall, 336-758-5929, class.wfu.edu).
Accommodations for Religious or Spiritual Practices: Wake Forest University benefits from the multitude of faiths and spiritual identities held by members of our learning community. Should you need accommodations this semester, email me as soon as possible to ensure we have time to develop equitable alternatives.
Class recordings: In case any class recordings are provided, they are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form.
Syllabus change notice
This syllabus and the dates herein are subject to change.