Epidemiology MS
Major: Epidemiology
Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: None
Classification of Instructional Programs (CIP) code: 26.1309
Standard Occupational Classification (SOC) code: 19-1041
About the Program
The Master of Science in Epidemiology trains students in epidemiologic principles and methods to solve complex public health and clinical issues. Students will graduate from this degree program prepared to contribute to epidemiologic research, from academic or hospital settings to pharmaceutical or biotechnology. Students will have the opportunity to specialize in specific areas of research including infectious disease, urban health, and environmental health risk. This program is for students interested in a terminal degree in applied epidemiologic research, as well as those who may wish to pursue doctoral training in epidemiology.
Additional Information
For more information about this program, please contact:
DSPH Academic Advising Team
Office of Education
dsphadvising@drexel.edu
Additional information can be found on the Dornsife School of Public Health website, including admissions criteria and how to apply.
Degree Requirements
| Required Courses | ||
| Core Courses | ||
| BST 571 | Introduction to Biostatistics | 3.0 |
| EPI 570 | Introduction to Epidemiology | 3.0 |
| PBHL 501 | Introduction to Public Health * | 0.0 |
| Epidemiology | ||
| EPI 560 | Intermediate Epidemiology | 3.0 |
| EPI 561 | Pathophysiologic Basis of Epidemiologic Research | 3.0 |
| Biostatistics | ||
| BST 553 | Longitudinal Data Analysis | 3.0 |
| BST 555 | Introduction to Statistical Computing | 3.0 |
| BST 560 | Intermediate Biostatistics I | 3.0 |
| Master's Project | ||
| EPI 699 | Master of Science Epidemiology Project | 3.0 |
| EPI 749 | Research and Practice in Epidemiology | 3.0 |
| Electives ** | 18.0 | |
| Total Credits | 45.0 | |
- *
Foundational Public Health Learning Objectives: PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.
- **
Students choose from any BST, CHP, EOH, EPI, HMP, or PBHL course from the 500-999 level. Students can take additional 500-level or above electives across the university as long as they meet prerequisite and restriction requirements. Students can contact their faculty mentor to discuss elective options.
Students may be able to use elective credits to further focus their academic work by completing a graduate minor or by coupling a DSPH graduate certificate. Students must have enough applicable elective credits to complete the certificate program without going beyond the required credits for the program. Students can contact their academic advisor for more information.
Sample Plan of Study
| First Year | |||||||
|---|---|---|---|---|---|---|---|
| Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
| BST 555 | 3.0 | BST 571 | 3.0 | BST 560 | 3.0 | VACATION | |
| EPI 561 | 3.0 | Electives | 6.0 | EPI 560 | 3.0 | ||
| EPI 570 | 3.0 | Electives | 3.0 | ||||
| PBHL 501* | 0.0 | ||||||
| 9 | 9 | 9 | 0 | ||||
| Second Year | |||||||
| Fall | Credits | Winter | Credits | ||||
| EPI 749 | 3.0 | BST 553 | 3.0 | ||||
| Electives | 6.0 | EPI 699 | 3.0 | ||||
| Electives | 3.0 | ||||||
| 9 | 9 | ||||||
| Total Credits 45 | |||||||
- *
PBHL 501 is only required for students who do not have a degree from a CEPH accredited school.
Program Level Outcomes
Major Competencies
- Address a research question by identifying appropriate study designs based on knowledge of biological basis of disease and calculating appropriate measures of disease frequency and risk
- Review and critically evaluate the validity of the design, analysis, and interpretation of findings from published research studies
- Create and manage datasets appropriate for epidemiologic analyses from sources such as surveillance, large-scale data (i.e, Big Data, such as electronic health records, administrative claims data), or other health-related research
- Conduct univariable and multivariable regression and other semi- and non-parametric analytic techniques to analyze an epidemiologic data set using a standard statistical software package
- Create effective peer-review quality written and visual summaries of analysis results