Post-baccalaureate trainees, Infectious Diseases fellows, physicians, and public-health staff increasingly need quantitative modeling skills but often do not want a full degree. This certificate packages a small set of IDEEEP courses into a standalone credential that can be taken part-time or bolted onto an existing fellowship specialty certificate. It gives quantitative training a professional on-ramp without requiring enrollment in the full concentration.
Draft proposal. This is an early proposal for a graduate certificate. Course numbers, credit hours, admission requirements, and the mapping onto the Infectious Diseases fellowship specialty-certificate structure are placeholders and will be confirmed with the Department of Biology and the fellowship program before the certificate is offered.
Overview
The certificate assembles three modules drawn from the quantitative courses in the IDEEEP concentration: outbreak analytics, statistical modeling of disease dynamics, and spatial epidemiology. Each module maps to an underlying proposed course and to the concept pages on this site, so learners work from the same material used in the degree track. The credential is stackable. A learner can take it on its own or append it to a Wake Forest Infectious Diseases fellowship specialty certificate.
Who it is for
- Post-baccalaureate trainees preparing for graduate study or research roles
- Infectious Diseases fellows who want modeling skills beyond clinical training
- Physicians and public-health staff who analyze surveillance and outbreak data
- Working professionals who need a credential rather than a full degree
No prior modeling coursework is assumed beyond introductory statistics and comfort with a scripting language such as R or Python.
Structure and credits
The certificate targets 9 to 12 credits assembled from three modules. Delivery is modular and part-time compatible. Modules can be taken in sequence over multiple terms, and the certificate can be completed alongside a fellowship or a full-time job.
| Module | Focus | Approx. credits |
|---|---|---|
| Outbreak analytics | Reproduction numbers, epidemic curves, forecasting | 3–4 |
| Statistical modeling | Bayesian workflow, hierarchical models, Stan | 3–4 |
| Spatial epidemiology | Disease mapping, CAR/BYM models, Gaussian processes | 3–4 |
Exact credit hours per module will be set with the Department of Biology.
Learning outcomes
On completing the certificate, learners will be able to:
- Estimate and interpret the time-varying reproduction number and read epidemic curves
- Build and forecast from models of transmission using a reproducible workflow
- Fit hierarchical and Bayesian models to infectious disease data with Stan
- Map disease risk across space using areal and continuous spatial models
- Communicate quantitative results with appropriate uncertainty to clinical and public-health audiences
Curriculum and modules
Each module draws on a proposed underlying course and the concept pages listed below. The proposed courses (Outbreak Analytics and Modeling, Statistical Modeling of Infectious Disease Dynamics, and Spatial Epidemiology and Disease Mapping) are being developed in parallel and are referred to here in plain text.
| Module | Underlying course (proposed) | Site resources |
|---|---|---|
| Outbreak analytics | Outbreak Analytics and Modeling | Reproduction number Rt, SEIR models, Stochastic epidemics, Branching processes |
| Statistical modeling | Statistical Modeling of Infectious Disease Dynamics | Bayesian inference, MCMC, Hierarchical models, Model calibration |
| Spatial epidemiology | Spatial Epidemiology and Disease Mapping | Areal models and CAR, Gaussian processes, Spatial point processes |
Relationship to existing Wake Forest certificates
Wake Forest’s Infectious Diseases fellowship already offers specialty
certificates in antimicrobial stewardship, global health, patient safety, and
translational sciences.
This modeling-and-analytics certificate slots into that structure as a
quantitative option.
A fellow can take it as a standalone credential or append it to an existing
specialty certificate.
The exact mapping onto the fellowship’s credit and certificate rules is
@placeholder and will be confirmed with the fellowship program.
Site resources
The certificate is powered by the same concept pages used in the degree-track courses. See the Programs page for how these courses fit the wider concentration, and the Field Epidemiology and Tropical Medicine course for an applied companion experience. Core quantitative pages include Reproduction number Rt, Bayesian inference, Hierarchical models, Areal models and CAR, and Gaussian processes.
Admission and how to enroll
- Admission requirements:
@placeholder - Application process and deadlines:
@placeholder - Tuition and fees:
@placeholder - Contact for enrollment questions:
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Prospective learners should contact the program to discuss fit and sequencing.
Artificial intelligence and academic integrity
Large language models such as ChatGPT, Claude, and Gemini are now part of academic and professional work, and learners are encouraged to use them to support their learning. If you use these tools, cite them and describe how you used them. They supplement your work; they do not replace your own understanding, and using them without attribution is plagiarism and will be treated as such.
Proposal change notice
This certificate proposal and the details herein are subject to change.