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48th Graduate Summer Session in Epidemiology

Personal Computers:
A laptop computer is essential and required for enrolled students (iPads, netbooks or other similar devices are also suitable). We recognize computers to be an extension of the learning tools needed to successfully participate in our courses. Coursepacks for most courses will be available digitally, in addition to other course requirements and final course evaluations.

1 Week Courses

EPID 703 Infectious Disease Epidemiology Principals and Applications
(1 credit hour) Mark L. Wilson
This course will introduce students to the special design, measurement, analysis and intervention issues associated with the epidemiology of infectious disease. We will address contemporary infectious diseases of public health importance in the developed and underdeveloped world. The overall goal is to help student to comprehend, analyze and synthesize processes underlying the transmission of pathogenic microbes, and approaches to disease prevention. Prerequisites: This course assumes that students have completed or are concurrently taking a basic course in epidemiologic methods.

EPID 704 Cancer Epidemiology and Prevention
(1 credit hour) Susan Gapstur
The purpose of this course is to introduce basic concepts and issues relevant to cancer epidemiology and prevention. Specifically, this course will provide a brief history of cancer and cancer epidemiology, as well as a review of the molecular and cellular basis of carcinogenesis. Issues in rea search design and interpretation of cancer statistics including trends over time and across geographic ares will be described. During the course, there will be formal lectures and discussions covering the current state of knowledge on the descriptive epidemiology, etiology and risk factors for major cancer sites. In addition, known and controversial strategies for cancer prevention and early detection also will be discussed. The course is appropriate for students who have an introductory knowledge of epidemiology and biostatistics. Previous study of cancer biology is helpful but not required. Prerequisites: Introductory level courses in epidemiology and biostatistics.


EPID 705 Epidemiology and Health Policy
(1 credit hour) Hal Morgenstern
This course deals with selected applications of epidemiologic methods and findings to health-services research, population health planning and evaluation, risk assessment and health policy. The major objective is to provide a framework for integrating causal inference with decision making, thereby bridging the gap between science and practice. Emphasis is given to important conceptual and methodologic issues that confront public-health and clinical researchers, policy analysts, health planners, attorneys, and decision makers. Prerequisites: Introductory level courses in epidemiology and biostatistics.

EPID 710 Intermediate Epidemiologic Methods
(1 credit hour) Hal Morgenstern
This course expands on the concepts, principles and methods covered in Epid 709 and focuses on the investigation of disease etiology and other causal relations in public health and medicine.  Class topics include types of research strategies (experiments, quasi experiments, observational studies), concepts of causation (counterfactuals, sufficient-cause model, effect measures), principles of analysis in observational studies (frequency, association, impact measures; confidence intervals, p values), error in effect estimation (precision; selection bias, misclassification bias, confounding), and methods for dealing with covariates (stratified analysis, matching and matched analysis; effect modification).  Prerequisites:  Basic courses in epidemiology (e.g., Epid 709) and linear regression (e.g., Epid 743, which can be taken concurrently).

EPID 716 Clinical Epidemiology and Evidence-Based Decision Making
(1 credit hour) Mitchell A.H. Levine
 With the increasing demand for an evidence-based approach in the delivery of health care services and the economic pressures for a more rational and efficient use of limited health care resources, practitioners and administrators in the health care field need to develop clinical measurement and evaluative skills in order to conduct their work optimally. Clinical Epidemiology and Evidence-Based Decision Making identifies and teaches these skills. The course will cover the basic concepts of clinical epidemiology in the context of appraising the recent medical literature pertaining to issues of causation, diagnosis, management, and economic evaluation. The format will include problem-based learning. Course materials will be provided in advance of the sessions, and should be reviewed before the course begins in order to obtain the maximum benefit from enrollment in the course. All health professionals (clinicians and administrators) who rely on the medical literature to guide their activities are invited to attend the course. No prerequisite.

EPID 717 Design and Conduct of Clinical Trials 
(1 credit hour) Stephen J. Farish
 The theoretical and practical challenges to be considered in designing and conducting a randomized clinical trial will be presented. Topics to be discussed include the specification of a primary objective, adherence to accepted ethical guidelines, the role of randomization and the means of its implementation, the choice of design strategy and design strengthening features, considerations involved in sample size determination and patient recruitment and standards for reporting clinical trials. Detailed analytic issues will be considered in the complementary one-week course that follows. Prerequisite: Introductory level course in epidemiology.

EPID 718 Analysis of Clinical Trials
(1 credit hour) Stephen J. Farish
 Methods of analysis appropriate to various designs, such as cross-over designs, nested designs, factorial designs, and designs with repeated measures will be presented. The use of GLM techniques for analysis will also be illustrated. Topics will include estimation of survival functions, survival comparison between groups of subjects, identification of important covariates, adjustment for covariates, testing for interaction, and understanding the difference between confounding and interaction. Specific tools to be discussed include the Kaplan-Meier estimators, the log-rank (Mantel-Haenszel) statistics, and the Cox proportional hazards model. Instruction will focus on empirical use of methodologies rather than formal algebraic knowledge. Practical applications of manual and software-based analysis will illustrate specific procedures and interpretation of results. Students receive a disk with the data and analysis programs for all examples in the course. Students are advised to bring a scientific calculator. Prerequisite: Introductory level course in biostatistics.

EPID 719 Quantitative Methods in Genetic Epidemiology
(1 credit hour) Not offered in 2013


EPID 722 Pharmacoepidemiology and Risk Management
(1 credit hour) Judith K. Jones
This course will cover the application of epidemiologic methods to study the use and effects of pharmaceuticals, biologics and other medical products.  In particular, it will cover methods of detecting adverse and beneficial drug effects, including spontaneous reporting systems, ad hoc epidemiologic studies, and the growing use of automated databases.  Emphasis will be placed on the need to quantify the frequency of drug effects and risk factors for these drug effects, rather than simply documenting causation.  We will also address the renewed interest in adverse events as a major public health problem and how it will impact the health care system through the more recent implementation of pharmaceutical risk management plans or Risk Evaluation and Mitigation Strategies, or REMS,and the implementation of the Sentinel System by FDA.  Other topics to be covered include measuring the frequency of drug use, the quality of prescribing, and new developments in pharmacoepidemiology methods.  Teaching methods will include lectures and workshops, as well as  development of a study protocol.  Prerequisite:  Introductory level course in epidemiology.

EPID 723 Environmental and Occupational Epidemiology
(1 credit hour) Not offered in 2013

EPID 742 Introduction to Logistic and Poisson Models
(1 credit hour) Alan E. Hubbard
The vast majority of epidemiologic data involve either binary or count data. Logistic (binary data) and Poisson (count data) regression analyses are two important analytic approaches that frequently provide valuable insights into collected data. Both techniques will be presented in a practical and an applied fashion. The discussed material begins with the simplest case with the goal of understanding the fundamental properties of each model. Once these properties are established, more advanced topics such as collinearity, variable selection, non-linear explanatory variables and goodness-of-fit will be described and applied to several multivariable epidemiologic data sets. These two analytic approaches not only provide simple and effective ways to explore complex relationships but illustrate the general process of using a linear model to draw conclusions from the analysis of epidemiologic data. Prerequisites: Introductory level courses in epidemiology and biostatistics.

EPID 743 Applied Linear Regression
(1 credit hour) Brenda Gillespie
 This course discusses the applications of linear regression models to medical research and public health data. We will focus on the two major goals of linear models: (1) explanation, the estimation of associations using linear regression models, and (2) prediction, the use of linear regression models to predict subject outcomes, as with diagnostic tests. Specific topics include graphical exploratory data analysis, assumptions behind simple and multivariate linear models, the use of categorical explanatory variables, identifying when transformations of explanatory and/or outcome variables are needed, assessing the presence of predictor/outcome associations through hypothesis testing, identifying when confounding and effect modification are present, assessing model fit, and model selection techniques. Prerequisite: Targeted audience members include researchers and health professionals with some basic knowledge of statistics and epidemiology who desire some in-depth exposure to the concepts and principles of linear regression models. This course will include a computer lab where students will gain experience with regression analysis using statistical software.

EPID 747 Successful Scientific Writing
(1 credit hour) Paul Z. Siegel
This course takes an active, participatory approach to help public health and health care professionals learn how to communicate the findings of their research and investigations more effectively and expedite publication of their manuscripts. Working in small groups, students spend much of their class time critiquing actual published and unpublished manuscripts, including their own, and solving a wide range of exercises that exemplify the real-world challenges that authors face. Free-form in-class discussions make it possible for class members to learn from one another's experiences. Major components of the course include the following: basic sections of a scientific article: the purpose, elements and organization of each section; principles of style for writing in public health and epidemiology; systematic approaches to the process of writing and publishing an article in a peer-review journal; and effective strategies for dealing with requests of journal editors and reviewers. No prerequisite.

EPID 757 Introduction to Meta-analysis
(1 credit hour) Joel Gagnier
Systematic reviews and meta-analysis are useful for evidence-based clinical and public health practice. The widespread and growing application of systematic review methods for the synthesis of evidence on important or pressing research and clinical questions underscore the need for health-care professionals to understand and critique this research design. This course will provide a detailed description of the systematic review process, discuss the strengths and limitations of the method, and provide step-by-step guidance on how to actually perform a systematic review and meta-analysis. Specific topics to be covered include: formulation of the review question, searching the literature, quality of the assessment of studies, data extraction, meta-analytic methods, assessment of heterogeneity and report writing. The course will also cover statistical issues such as selection of statistical models for meta-analysis, practical examples of fixed and random effects models, best evidence synthesis (qualitative systematic reviews) as well as examples of methods to evaluate heterogeneity and publication bias. STATA statistical software will be used to perform meta-analysis during the computer lab, along with tutorials on to effectively use tools such as PubMed for conducting reviews. Prerequisites: Basic course in epidemiology and biostatistics.

EPID 759 Introduction to SAS
(1 credit hour) Kathleen B. Welch
This course will present SAS at an introductory level for public health professionals. The overall objective of the course is to enable students to develop the ability to use SAS for basic statistical analyses, and to prepare for more advanced uses of SAS. Students in the course will learn how to navigate SAS in the Windows environment, create and submit command files, print output, do simple troubleshooting, create and manipulate SAS data sets, recode and transform variables, and do simple statistical analyses using SAS. Data management tasks, such as merging data sets to add variables, and adding cases to a data set will also be covered, as will information on how to import/export data between SAS and other programs, such as Excel, SPSS, and Epi Info. SAS/INSIGHT will be introduced for examining the distributions of variables and checking statistical assumption, and using interactive graphics. The class will be taught as a lab, with lectures and demonstrations. Prerequisites: Introductory level courses in epidemiology and biostatistics; experience in the use of Windows-based microcomputers.

EPID 761 Methods in Social Epidemiology
(1 credit hour) Carlos Mendes de Leon
Social epidemiologists seek to understand the role of social conditions and psychosocial processes in the development of poor health outcomes across the lifespan. This course will provide an introduction to some of the core theories, concepts, methods and findings in recent social epidemiologic research. Using a combination of lectures, in-class exercises, and discussions, we will develop a basic understanding of how key social factors shape the distribution of health and disease in the general population, with a focus on race/ethnicity, social status, features of the neighborhood social environment, and individual-level psychsocial characteristics. In addition , we will review recent work on biological processes that are thought to mediate or interact with social factors in producing health differences between individuals and populations. Prerequisites: Introductory level course in epidemiology.

EPID 766 Analysis of Longitudinal Data from Epidemiologic Studies
(1 credit hour) Daowen Zhang
 It has been popular in epidemiology to conduct longitudinal studies where study participants are followed over time and repeated measurements of interest are obtained. Compared to traditional cross-sectional or case-control studies, longitudinal studies can be more efficient to detect difference of interest, offer more evidence for possible causal inference, etc. However, longitudinal data are likely to be correlated, which presents substantial challenge in analyzing such data. This course will address 1) epidemiologic methods for the design and interpretation of longitudinal studies involving repeated measures and 2) statistical methods appropriate for longitudinal data including generalized estimating equations (GEEs), linear mixed models and generalized linear mixed models. A series of studies will be used to illustrate the major design issues and statistical approaches. Relevant procedures in statistical package SAS will be introduced and appropriate interpretation of results will be emphasized. Prerequisite: Student are expected to have one or two graduate biostatistics courses on (simple and multiple) linear regression models, categorical data analysis such as logistic regression models and experience of conducting data analysis using statistical software SAS.

EPID 768 Global Health Issues, Crises and Solutions (Myron E. Wegman memorial course in International Health)
(1 credit hour) Jose R. Teruel
This course will review the historical development of innovative ideas in public health and international health and will emphasize the importance to understand the transition from humanitarian assistance to international cooperation.  We define GLOBAL HEALTH as a “new dynamic approach of international health based on the analysis of the diversity and trends in the health and living conditions of people and nations, the influence of the political and socioeconomic forces, and the use of this knowledge for the solution of the identified problems”.  Global Health is concerned not only with pandemics but also with the challenges represented by poverty, environmental degradation, disasters and emergencies and the impact of violence and conflicts. We will review the basic concepts and the present knowledge and approaches to these issues and some of the most influential strategies like: Health Determinants, the Millennium Development Goals, Health as a Bridge for Peace and the new concept of Human Security.  No prerequisite.

EPID 777 Geographic Information Systems for Epidemiology
(1 credit hour) Shannon J. Brines
 Geographic Information Systems (GIS) are used for displaying and analyzing spatial data. Data from a variety of sources may be compared utilizing overlay analysis and spatial statistics. Modern tools permit novice GIS users to perform spatial analysis without extensive training. This course will introduce students to ArcGIS, the world's leading GIS analysis package. Examples of epidemiological applications will give students the opportunity to see and use this powerful tool. Some of the topics to be covered are data import/export, layering, data table management, classification, labeling, spatial and attribute queries, and buffer analysis. No prerequisite.

EPID 783 Methods in Community-Based Participatory Research for Health
(1 credit hour) Barbara A. Israel
(co-taught by other faculty and community partners involved in the Detroit Community-Academic Urban Research Center (www.sph.umich.edu/urc) and its affiliated CBPR projects)
There is increasing recognition and support for more comprehensive and participatory approaches to research and interventions in order to address the complex set of determinants associated with public health problems that affect populations generally, as well as those factors associated with racial and ethnic disparities in health more specifically. Community-based participatory research (CBPR) is one such partnership approach that equitably involves all partners in all aspects of the research and intervention process, aimed at both increasing knowledge and understanding and linking the knowledge gained with interventions and policy change to enhance the health and quality of life of community members. This course will provide an introduction to some of the core principles, concepts and methods involved in using a CBPR approach. Organized along the phases of CBPR, this course will focus on describing and understanding partnership formation, maintenance and evaluation; the use of quantitative and qualitative methods (e.g., survey, focus group interview, observational checklist) for the purposes of community assessment, examining basic research questions, and developing and evaluating interventions; and feedback, interpretation, dissemination and application of research results. The course will examine the rationale for, benefits of and challenges associated with using a community-academic partnership approach to research and interventions. Class format includes lectures, discussions, case studies, and small group exercises. No prerequisite.

EPID 784 Survival Analysis Applied to Epidemiologic and Medical Data
(1 credit hour) Douglas E. Schaubel
The primary objective of this course is to provide participants with the background required to understand commonly used survival analysis methods, and to apply such methods using standard statistical software.  The course material relies heavily on examples and intuitive explanations of concepts.  The mathematical level is completely accessible with knowledge of high school algebra, one semester of calculus, and a one-year course in basic statistical methods. Examples will be chosen from various epidemiologic and medical applications.  The topics will include: an introduction to survival analysis; right censoring and left truncation; life tables, non-parametric estimators (e.g., Kaplan-Meier, Nelson-Aalen); two- and k-sample tests (e.g., log rank, Wilcoxon); parametric methods for analyzing survival data (e.g., exponential model); semi parametric methods (e.g., Cox proportional hazards model).  The statistical techniques will be illustrated using various medical and epidemiological studies. Students will carry out some applied (pencil-and-paper) problems to illustrate the main ideas of survival analysis and to solidify the concepts. There will also be a number of data analysis exercises that will utilize statistical software.  Prerequisite: Introductory level course in statistics (including an introduction to regression methods).

EPID 785 Public Health Surveillance
(1 credit hour) Eden V. Wells
 Public health surveillance is an integral ingredient of any efficient and effective disease control and prevention program. Public health professionals must have information concerning the parameters of a disease’s occurrence in order to be able to develop and maintain a program to reduce the occurrence of that disease. This course will provide a strong background in all aspects of public health surveillance. Discussions will cover its history, purposes and uses, and the elements involved in a public health surveillance program, surveillance data sources, data analysis, preparation of reports, program evaluation, and ethical and legal issues. Discussions will include surveillance of infectious and non-infectious diseases. Newer concepts of public health surveillance will also be discussed such as syndromic surveillance. Surveillance at local, state, and federal levels as well as as practiced in other countries will also be discussed. Several case exercises will be worked on in the classroom. Prerequisite: Basic knowledge of epidemiology and descriptive statistics.

EPID 787 An Introduction to Multilevel Analysis in Public Health
(1 credit hour) Jay S. Kaufman
Multilevel analysis is an essential analytic tool in epidemiology and public health that allows the simultaneous investigation of the effects of factors defined at multiple levels on individual-level outcomes. This short course will review the rationale for multilevel analysis in public health research, build the theory and practice of these models from the fundamentals of the statistical approach and demonstrate a variety of different forms that the models can take. Fitting and interpreting models will demonstrate using strata 12 statistical software. Special emphasis will be placed on the strengths and limitations of mu lit level analysis in investigating social and group-level determinants of health. Prerequisites: Knowledge of basic epidemiology and linear and logistic regression.


EPID 790 Effective Oral Communications
(1 credit hour) Scott McNabb
This course is designed to convey the principles and practice of dynamic and persuasive techniques for oral communication of scientific information.  Its goal is to develop competency in effective oral communication of scientific research using various ways and to diverse audiences.  Course topics include: 1) communications as an interactive process; 2) persuasive vis-à-vis informative presentations; 3) distinguishing data, information, and messages; 4) analyzing a target audience; 5) condensing complex messages into sound-bite size; 6) effective approaches for the use of visual aids including PowerPoint ™, tables, graphs, charts, and photographs; 7) image matters; and 8) strategies for dealing with the media. No prerequisite.

EPID 791 Intermediate SAS for Epidemiologists
(1 credit hour) Kathleen B. Welch
This workshop will discuss SAS commands for data management, including rearranging data from "Wide" to "Long" format for use in longitudinal analysis; the inclusion of lags in a data set; removing duplicate cases; and aggregating cases across groups. Merging data containing individual values with tables containing summary statistics (e.g. merging patient data with zip-code or census-tract data) will be discussed. These topics will involve the use of arrays and do-loops in SAS. We will touch very briefly on SAS macros. This class will be taught as a lab, with lectures, demonstrations and problem sets. Prerequisite: Familiarity with SAS at the level of Epidemiology 759: Introduction to SAS.

EPID 792 Advanced Methods for Systematic Reviews and Meta-analysis.
(1 credit hour)Joel Gagnier
Systematic reviews and meta-analysis are useful for evidence-based clinical and public health practice. The widespread and growing application of systematic review methods for the synthesis of evidence on important or pressing research and clinical questions underscore the need for health-care professionals to understand and critique this research design. This course will provide a detailed description of advanced methods for performing systematic reviews and meta-analysis including: effect sizes in meta-analysis (means, binary data, correlations), fixed-effect models (e.g., Petro, Mantel-Haenszel, inverse-variance, maximum likelihood), random effects models (e.g. inverse variance, maximum likelihood), assessing between study heterogeneity (Q test, Isq, plotting and graphical tools), mixed effects modeling , exploring between study heterogeneity (fixed effects and random effects regression analyses and subgroup analyses), methods of indirect comparisons, assessing publication bias( funnel plots, contour-enhanced funnel plots), and handling missing data. The course will also cover best evidence syntheses including a detail description of the GRADE approach. STATA statistical software will be used to perform meta-analysis during computer labs. Prerequisites: Introductory course in epidemiology, biostatistics and an introductory course in systematic reviews and meta-analysis (e.g. EPID 757)

EPID 793 Complex Systems Modeling for Public Health Research.
(1credit hour) Ross Hammond
This course will provide an introduction to three major complex systems science modeling techniques with wide applicability to public health. We will cover an introductory overview to each technique, examples of applications, brief discussions of best practices, and some initial hands-on lab experience. At the completion of the course the student will be able to explain current and potential future roles of complex systems science in public health and describe each of the three approaches and their respective advantages/disadvantages. Students will be well positioned to further explore incorporation of systems science methods into their own research or participation in interdisciplinary teams using the modeling techniques. Prerequisite: Introductory level course in epidemiology.

EPID 794 Epidemiologic Methods for Population and Clinical Research
( 1 credit hour) Eduardo Villamor
This course is offered in Spanish
This course offers an overview of current concepts and methods used in epidemiologic research of health problems in population and clinical settings. Participants in this course will become familiar with basic aspects of casual inference, common observational and intervention epidemiologic study designs, measure of event occurrence and association, effect modification, impact of confounding and common biases on the interpretation of epidemiological data, and research synthesis in epidemiologic research. No prerequisites.