Master of Science in Computational Epidemiology and Systems Modeling

2-Year DEGREE PROGRAM | 48 CREDIT HOURS

The Master of Science (MS) program in Computational Epidemiology and Systems Modeling trains students to become highly skilled epidemiologists who apply mathematical and statistical models to understand and analyze public health problems. Students are rigorously trained on how to manage and analyze big data relevant to a wide range of data science applications. They will learn to develop and apply dynamic models to important problems in the epidemiology of both infectious and non-communicable disease to optimize intervention strategies. Using their newly acquired skills, students will leverage the wealth of big data including remote sensing imagery, the microbiome, medical and surveillance records, genomics and metagenomics.

Epidemiological models and simulation-based analyses are increasingly used to inform public health policy and practice. The curriculum aims to provide students with the knowledge, skills, and hands-on experience necessary to become epidemiologists who are proficient in mathematical modeling, computational science, and the statistical tools that connect these models to real-world data and problems. Graduates of the program will be well-prepared for careers in research, academia, data management, industry, and health informatics.

The degree is awarded by the University of Michigan’s Rackham Graduate School through the Department of Epidemiology in the University of Michigan School of Public Health.

Program Curriculum

The program is organized around four core areas: epidemiology, mathematical modeling, statistics, and computing/programming. Training consists of three elements:

Core courses that introduce and further explain key concepts in epidemiology, mathematical modeling, statistics, and computing/programming (35 credits)
A series of electives covering topics in computational epidemiology, systems modeling, public health decision-making, and applied statistics (9 credits)
Capstone project(s) to be completed by students during the final two semesters of the MS degree program (4 credits)

Courses will serve as a way for students to gain knowledge across the four disciplines and apply their acquired skills to coursework. By graduation, students will have competence in key computing languages (e.g. R, Python, or C++).

Computational Epidemiology and Systems Modeling Requirements

Courses	Credit	Term
EPID 600 Introduction to Epidemiology	3	Fall
EPID 602 Applied Epidemiologic Data Analysis	3	Winter
EPID 675, 684, or 815 EPID Advanced Methods	3	Winter
EPID 633 Introduction to Modeling in Public Health	3	Fall
EPID 634 Foundations of Infectious Disease Modeling	3	Winter
EPID 636 Cancer Risk and Epidemiology Modeling	3	Fall
EPID 639 R for Epidemiology Research	2	Fall
Biostatistic Sequence Option 1
*BIOSTAT 601 Probability And Distribution Theory	4	Fall
*BIOSTAT 650 Applied Statistics I: Linear Regression	4	Fall
*BIOSTAT 651 Applied Statistics II: Extensions for Linear Regression	3	Winter
BIOSTAT 607 Basic Computing for Data Analytics	1	Fall
BIOSTAT 615 Statistical Computing	3	Fall

* The Biostat 600-level sequence has a prerequisite of three semesters of undergraduate level calculus and one semester of undergraduate level linear algebra. Students without these prerequisites should take instead the Biostatistics sequence for MPH in Epidemiology students (First term Biostat 521, Second term Biostat 522 and Third term Biostat 523)

Elective Options are listed below (9 credits)

Epidemiology Elective Options- 1 required:

Courses	Credits	Term
EPID 601 Principles and Methods of Epidemiology	4	Fall
EPID 605 Infectious Disease Epidemiology	3	Fall
EPID 514 Social Epidemiology (3 credits)	3	Fall
EPID 621 Cancer Epidemiology (3 credits)	3	Winter

Modeling Electives:

Courses	Credits	Term
EPID 637 Systems Modeling of Behavior, Social Processes and Chronic Disease	3	Winter
CMPLXSYS 530 Computer Modeling of Complex Systems	3	Winter

Statistics Elective Options

Courses	Credit	Term
BIOSTAT 625 Computing with Big Data	3	Fall
BIOSTAT 675 Survival Time Analysis	3	Fall
STATS 531 Analysis of Time Series	3	Winter
STATS 620 Applied Probability and Stochastic Modeling	3	Winter

Health Management and Policy Elective Options - 1 required

Course	Credit	Term
HMP 553 Data Management in Health Care	3	Winter
HMP 610 Cost-Effectiveness Analysis in Health	3	Fall
HMP 654 Operations Research and Control Systems in Health Care	2-3	Fall
HMP 655 Decision Making Models in Health Care	3	Winter

Program Prerequisites

Epidemiology is a discipline strongly rooted in the life sciences and quantitative analysis. Applicants should have a strong interest in quantitative science and health. Most applicants have an undergraduate degree from social, life or applied quantitative sciences, engineering, mathematics, statistics, or public health. While this program has no specific required courses, ideally students would have taken courses in calculus, linear algebra, statistics, and/or programming.

Faculty and Research

Students in the MS in Computational Epidemiology and Systems Modeling program will have the opportunity to learn and work alongside faculty with varied interests, specializations, backgrounds, and active research projects in different areas. From using models to optimize cancer intervention designs, to surveillance modeling and pandemic response, University of Michigan School of Public Health faculty lead centers and partnerships that span the globe.

Associated Research Centers

University of Michigan and Georgetown University CAsToR Tobacco Modeling Center
Michigan Institute for Computational Discovery and Engineering (MICDE)
University of Michigan Center for the Study of Complex Systems (CSCS)
National Cancer Institute Cancer Intervention and Surveillance Modeling Network (CISNET)

Research, News, and More

Ready to Apply?

MS applicants apply to our program through the University of Michigan Rackham Graduate School.

The priority deadline for applications to the MS in Computational Epidemiology and Systems Modeling program is December 1, 2024. Applications accepted on a rolling basis after December 1, but priority for funding decisions is given to those submitted by December 1. Final Deadline for International Applicants: January 15, 2025.

We encourage applicants to submit prior to the priority deadline to ensure they are considered for scholarships. Those who submit afterward are not guaranteed consideration. Funds are available on a first come first served basis.

How to Apply

Application Requirements

As part of the application process, prospective students must provide:

Statement of Purpose: Your statement of purpose should be a concise, well-written statement about your academic and research background as well as your career goals. The length of the statement of purpose should be between 1-3 pages and submitted via ApplyWeb and Rackham.
Personal Statement: Your personal statement should be a discussion of the journey that led to your decision to pursue a graduate degree in Computational Epidemiology and Systems Modeling. It should be submitted via ApplyWeb and Rackham.
Transcripts:

- Applicants who attended or are attending a U.S. Institution:
  Upload an electronic version of your official transcript(s) for each bachelor’s, master’s, professional, or doctoral degree earned or in progress through your ApplyWeb application account.
  If you are recommended for admission, the Rackham Graduate School will require an official transcript(s). Recommended applicants will receive an email notification when the official transcript(s) are required for submission. All students are asked to include an electronic transcript during the online application.

- Applicants who attended or are attending a non-U.S. institution: Review required academic credentials from non-U.S. institutions for transcript/academic record requirements by country or region. Submitting transcript/academic records is a two-step process.
  
  Upload an electronic version of your official transcript/academic record for each institution attended through your ApplyWeb application account.
  
  At the time of application, you must also submit an official transcript/academic record for each institution attended. See Rackham’s detailed instructions on how to submit transcripts/academic records to the Rackham Graduate School.

English Language Test Scores: The TOEFL or IELTS is required for applicants whose native language is not English, unless they meet one of the exemption criteria.
Letters of Recommendation: Letters of recommendation should signed and printed on letterhead. Submitted via ApplyWeb and Rackham.
master: 3 letters are required (at least 2 academic)

Financial Support

The Epidemiology Department offers a limited number of Epidemiology Departmental Scholarships to support MS in CESM student tuition. All MS in CESM students are considered for these scholarships, and no additional application is required. In addition, the School of Public Health offers financial aid and funding opportunities to support a limited number of students through a mixture of training grants, research grants, and graduate student research assistantships. Students pursuing a Master of Science degree may also be eligible to receive financial support from the Rackham Graduate School. Learn more about funding opportunities from Rackham.