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Graduate Curriculum

Epidemiology Courses taught as part of the Quantitative Biomedical Sciences PhD program: 

Foundations of Epidemiology I (QBS 130/Biol 072)
Instructor: Dr. Diane Gilbert-Diamond
This is the first of a two course sequence of graduate level epidemiology (Foundations of Epidemiology I and II). The two courses are designed to teach the underlying theory of epidemiologic study designs and analysis and prepare students for conduct of epidemiology research. Design of investigations seeking to understand the cause of human disease, disease progression, treatment and screening methods include clinical trials, cohort studies, case-cohort, case-case, nested case-control and case-control designs. Concepts of incidence rates, attributable rate and relative rate, induction and latent periods of disease occurrence, confounding, effect modification, misclassification, and causal inference will be covered in depth.

Foundations of Epidemiology II (QBS 131/Biol 73)
Instructor: Dr. Megan Romano
This graduate-level course is the second in a two-part sequence. The two courses are designed to teach the underlying theory of epidemiologic study designs and analysis and prepare students for conduct of epidemiologic research. Building off of concepts covered in Foundations of Epidemiology I, students develop an in-depth understanding of advanced concepts related to confounding, interpreting biomedical primary literature, and epidemiological study design. Concepts related to outbreak investigation, evaluation of screening tests, and assessment of the effects of policies on health are also covered.

Applied Epidemiological Methods I (QBS 136)
Instructor: Dr. Anne Hoen
Computer laboratory-based course designed to provide hands-on experience performing epidemiological data analyses relevant to the theoretical/conceptual material presented in Foundations of Epidemiology I. Students will complete laboratory exercises using epidemiological study data sets that guide them through descriptive data analyses, hypothesis testing within the context of a range of epidemiological study designs, causal inference methods, addressing confounding and effect modification, and power and sample size calculations. Analyses will be performed in the open-access programming language R. Course will meet once per week for 90 minutes. Note that this is a half-credit course designed to be taken at the same time as Foundations of Epidemiology I.
Prerequisite: Taken in conjunction with QBS 130. Basic proficiency in R.

Clinical Epidemiology (QBS 133)
Instructor: Dr. Michael Passarelli
This course focuses on the study of medical interventions and the outcomes of disease, expanding on selected concepts covered in Foundations of Epidemiology I & II. Lectures will emphasize study design, statistical methods, collection and interpretation of data, and will be supplemented with readings from the medical literature. Topics include assessment of the performance of diagnostic and screening tests, design of studies for evaluating the efficacy of screening programs for early detection of chronic disease, as well as randomized clinical trials and nonrandomized studies of disease prognosis, therapeutic efficacy, and therapeutic safety. Also covered will be the construction and validation of clinical risk prediction models and statistical approaches for assessing the performance of risk prediction models including discrimination, calibration, and reclassification. Additional topics include pharmacoepidemiology, pharmacogenomics, quality of life measurement, and synthesis of quantitative data for medical decision making such as meta-analysis and cost-effectiveness analysis.
Prerequisite: QBS 130 & 131

Epidemiology Seminar (QBS 270)
Instructor: Janet Peacock, PhD
Graduate-level journal club focused on interpreting scientific literature specific to epidemiological and biomedical research studies. Students will learn about the key aspects of a scientific study, how to critically evaluate epidemiological and biomedical research studies and how to effectively communicate study findings to others. Prerequisites: None.
2:30p - 4p Monday

Epidemiology Seminar (QBS 271)
Instructor: Jennifer Emond, PhD
Students will critically review a mini-set (2-3 studies) of epidemiological studies in one field of their choice. The goal of the review is to present a "mini" report of the current state of the science for a particular research area and to outline a future study. The outline of that future study should be a clear extension of the limitations of the studies reviewed or the implications of the studies reviewed. Prerequisites: None
Spring Term

Quantitative Biomedical Sciences Journal Club (QBS 270)

All first year QBS PhD students are required to enroll in the Quantitative Biomedical Sciences Journal Club except in the Summer quarter; however it is encouraged that QBS PhD students attend this journal club in subsequent years. An essential element of scientific training is in the critical analysis and communication of experimental research in an oral format.

  • Fall: Epidemiology - Dr. Janet Peacock

This course emphasizes critical evaluation of epidemiological studies and the development of effective presentation skills. Students will gain exposure to a breadth of epidemiological methodologies while examining classical and current epidemiological studies within public health and biomedical research. Class will meet weekly. Each week, all students will read one peer-reviewed, published study and an additional article or other paper for supplemental reading.  One student will present on the published study, and we will all discuss the study as well as the relevance of the additional reading. Discussion will include an assessment of study components as related to study design, statistical analyses, inference and interpretation, bias, generalizability,  and implications. Students will be asked to specifically discuss components of the study (e.g., to restate what one figure or table presents).

First-year doctoral students are required to present twice during the quarter.

  • Winter: Biostatistics - Dr. Jiang Gui

This course discusses new findings and applications in biostatistics and data science. The goal of the course is to develop critical thinking in biostatistical methodology. Starting the second week of the term, students will present two related paper with an emphasis on biostatical methods and the rest of the class will submit a short written summary (1-2 pages) that covers the paper motivation, approach, results, strengths and weaknesses. During class, a student will give a 35-minute presentation on their papers followed by 10 minutes of class discussion. In addition to reading and summarizing their selected paper for the week, all students are expected review the two presented papers prior to class in order to participate in the discussion.

  • Spring: Bioinformatics - Dr. Nicholas Jacobson & Dr. Alfredo Tirado-Ramos

The critical analysis and communication of experimental research in both written and oral formats is an essential element of scientific training. Students in the spring QBS journal club will select nine recent digital medicine and biomedical informatics papers from a set of approved journals. Starting the second week of the term, students will read one of the selected papers per week and submit a short written summary (1-2 pages) that covers the paper motivation, approach, results, strengths and weaknesses. During class, two students will each give a 45-minute presentation (40 min. of presentation with 5 min. for questions) on their papers (students will present twice during the term). In addition to reading and summarizing their selected paper for the week, all students are expected to review the two presented papers prior to class. Time permitting, additional topics for group discussion related to publishing your own research will include journal selection, impact factors, the peer review process, and authorship criteria.

For an overview of the Quantitative Biomedical Sciences program, please see our Course Catalog.