One-Week Courses | Two-Week Courses| | One Day Workshops MORNING 8:30 a.m.. – noon
Principles of Epidemiology
Lechaim Naggan
(340.601.11) M T W Th F S (Saturday June 21)
This is an introductory course in epidemiologic methodology covering study design for investigation of both infectious and chronic diseases. Evaluation of screening programs and health services research will also be discussed. The laboratory problems, based on real data, will include an outbreak investigation, natural history of infectious diseases, validity of clinical tests, survival analysis, and clinical trial and etiologic studies. While there are no formal prerequisites for this course, good quantitative skills and some biologic background are strongly recommended. (5 academic credits)
June 16 - June 27 MORNING 8:30 a.m.. – noon
Observational Epidemiology
Brad Astor
(340.608.11) M T W Th F
Expands upon material presented in Principles of Epidemiology (340.601) and provides opportunity to learn more about epidemiologic concepts as applied to cohort and case-control studies. Emphasizes interpretation and the ability to critically evaluate observational study designs and methods of data analysis. Intermediate concepts include measures of association, bias, confounding, and interaction/effect modification, and are illustrated in the context of analytic observational study designs.
(4 academic credits) AFTERNOON Statistical Reasoning in Public Health I and II
Natalie Blades and Michelle Shardell
M T W Th F
(140.611.11) June 16 – June 25 1:30 p.m. – 5:00 p.m.
(140.612.11) June 25 – July 3 1:30 p.m. – 5:30 p.m.
This introductory sequence is intended to provide students with a broad overview of biostatistical methods and concepts used in the public health sciences. The emphasis is on interpretation and concepts rather than calculations or mathematical details. Statistical formulas will be kept to a minimum. An objective is to provide students with an ability to read the scientific literature in order to critically evaluate study designs and methods of data analysis. Basic concepts of statistical inference including hypothesis testing, p-values, and confidence intervals will be introduced. Specific topics will include comparisons of means and proportions, the normal distribution, regression and correlation, confounding, and concepts of study design including randomization, sample size, and power considerations. Additional topics will include logistic regression and an overview of some methods in survival analysis. Examples of the use and abuse of statistical methods will be drawn from the current biomedical literature. (3 academic credits for each course)
June 16 – June 20
MORNING 8:30 a.m. - noon
Pharmacoepidemiology
Sheila Weiss
(340.617.11) M T W Th F
Pharmacoepidemiology involves application of epidemiologic methods to study uses and effects of drugs and biologics in human populations. This includes studies of disease natural history necessary to understand drug effects. Pharmacoepidemiology also encompasses development of valid and feasible outcome measures and development of study designs and analytic methods for assessing drug effects. Drug development and approval process, clinical trials, pharmacovigilance, signal detection, and therapeutic risk management, approaches to anticipating and reducing common sources of bias in cohort and case control studies of drug effects will be discussed. Class discussions will center around published studies that illustrate important concepts as well as discussions of hypothetical research questions and how to approach them. (2 academic credits) Biostatistics Analysis Of Epidemiologic DataI: Logistic Regression
Steve Selvin
(140.676.11) M T W Th F
A "workshop" approach is used to teach advanced statistical techniques for epidemiologic data. The course will start with a discussion of model-free methods, illustrated by the 2 by k table, and combining a series of 2 by 2 tables using weighted averages. Estimation and likelihood methods will be reviewed. Linear logistic analysis methods used to explore categorical data will be discussed, as well as the biostatistical concepts of additivity, independence, confounding, and interaction in the context of logistic models. (2 academic credits) Family Based Genetic Epidemiology
Terri Beaty and Kung-Yee Liang
(340.661.11) M T W Th F
This course will present methods commonly used in genetic epidemiology, including statistical methods for measuring familial aggregation, in addition to formal segregation and linkage analysis using family data. The principles and applications of a variety of statistical methods will be presented in detail, and the students will be given the opportunity to implement these methods using both real and simulated data sets as part of the computer lab. Basic understanding of epidemiologic and biostatistical principles is required for this course. Students unfamiliar with genetics should take the "Molecular Biology for Genetic Epidemiology" course. Enrollment limited. (2 academic credits) Introduction to Diabetes And Obesity Epidemiology
Tiffany Gary
(340.644.11) M T W Th F
Describes the epidemiology and prevention of diabetes, obesity, and associated complications. Discusses methodological issues associated with evaluating these in epidemiologic studies. The course is designed to cover the global epidemics of diabetes and obesity, environmental and genetic risk factors, as well as interventions to improve diabetes outcomes and weight management. (2 academic credits) Infectious Disease Epidemiology
Kenrad Nelson
(340.668. 11) M T W Th F S
This course will provide an introduction to epidemiologic methods used in infectious disease investigations. The importance of surveillance systems in detecting modern epidemics and in the development of effective disease prevention and control strategies will also be presented. An emphasis will be placed on understanding the relationships between the host, the parasite and the environment as they relate to disease causation. The course will explore contemporary epidemiologic methods applicable to old diseases that remain real or potential problems, newly emerging infectious diseases, tropical diseases, and hospital infections. Selected diseases will be discussed to clarify the role of epidemiology in understanding the pathogenesis of infectious processes in individuals and communities. Specific disease examples to be covered include sexually transmitted diseases, tuberculosis, malaria and diarrheal diseases, enteric infections, Legionnaires’ disease, toxic shock syndrome, acquired immunodeficiency syndrome, and others. This course was previously offered in the Summer Institute as 340.627.11. Prerequisite: Knowledge of basic epidemiology. (3 academic credits)
AFTERNOON Nutritional Epidemiology
Laura Caulfield
(340.650.11) M T W Th F 1:30 p.m. – 5:00 p.m.
The course will provide an introduction to the methodological issues involved in the design, conduct, analysis and interpretation of studies investigating the relationship between nutritional status, diet and disease. Emphasis will be placed on issues such as intraindividual variation, measurement of error, misclassification, correlated variables, population homogeneity, and the use of group versus individual data. The selection and use of dietary and nutritional status assessment methods appropriate for different study designs will be covered, and some experience in their use and interpretation will be provided. The impact of methodological issues, and of the type of study design, on interpretation and conclusions from research in nutrition epidemiology will be emphasized. Prerequisites: None. (2 academic credits) Data Analysis Workshop I and II
John McGready
M T W Th F 1:30 p.m. – 5:00 p.m.
(140.613.11) June 16 – June 20
(140.614.11) June 23 – June 27
This sequence of workshops is intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills. The emphasis is on concepts and illustration of concepts applying a variety of analytic techniques to four to six public health datasets in a computer laboratory setting using STATA statistical software. In the first workshop (140.613), students learn basic methods of data organization/management and simple methods for data exploration, data editing, and graphical and tabular displays. Additional topics include comparison of means and proportions, simple linear regression and correlation. In the second workshop (140.614) students will master more advanced multivariate methods of data analysis including multiple linear regression, and multiple logistic regression. Enrollment limited; students must bring a laptop computer with Stata 9 installed. (2 academic credits for each course) Quantifying Epidemiological Relationships Using Spatial Analysis
Saad Bin Omer and William Pan
(340.650.11) M T W Th F 1:30 p.m. – 5:00 p.m.
Introduces students to analytical tools for spatial epidemiology to understand and interpret spatial relationships among data. Students are trained to look beyond descriptive maps in order to quantify observed spatial patterns in health-related events. Students also learn concepts and skills to apply tools used to conduct spatial epidemiological studies. Prequisites: Introductory courses in biostatistics and GIS. Enrollment limited: students must bring a laptop computer. (2 academic credits) Epidemiology in Evidence-Based Policy
Michel A. Ibrahim and Leon Gordis
(340.636.11) M T W Th F 1:30 p.m. – 5:00 p.m.
This course will focus on the use of scientific evidence in making clinical decisions and health and regulatory policies. The course will be organized to address several questions: What is good science and what is junk science? What are the roles of epidemiologists, government, and industry? When should established expert opinions be questioned? What should you do when the evidence is equivocal and/or controversial? And, how does science fare in the legislative, regulatory, and judicial settings? The results of systematic reviews and meta-analysis will be discussed for several case examples such as mammography, prostate cancer screening, virtual colonoscopy, breast implants, the flu vaccine shortage, tobacco use, radon exposure, and air pollution. Class time will include lectures, problem-focused case studies, and hands-on exercises, with breakout sessions and video presentations throughout the course. (2 academic credits) Ethics Issues in Human Subjects Research in Developing Countries
Nancy Kass and Andrea Ruff
(340.667.11) M T W Th F 1:30 p.m. – 5:00 p.m.
This course will introduce those enrolled to ethical principles and formal codes of ethics, to key ethical issues that arise in international research. Ultimately, the course will be case-based to enable course participants to work through ethical challenges posed by research conducted in developing countries. Each daily session will be divided between a formal lecture and a case discussion. Case studies will be discussed in small groups and will be based on actual research projects in developing countries, including both clinical and epidemiological/observational research. The course is geared towards U.S. and international faculty, researchers, and students who conduct or fund research in developing country settings and to those who sit on IRBs/research ethics boards. Student evaluation is based on case study exercises and class participation. (2 academic credits)
Advanced Methods in Global Tobacco Control
Frances Stillman and Heather Wipfli
(340.678.11) M T W Th F 1:30 p.m. – 5:00 p.m.
Global tobacco control methods are presented in depth. Focus is on designing, implementing, and evaluating tobacco control interventions based on the need of a specific region or country. The courses highlights the use of multi-level solutions linking policy, communication, prevention, education, regulation, advocacy, and community organizing to address the interdisciplinary problem of tobacco use. Aspects of tobacco use and tobacco control are examined through lectures, case studies, presentations, and discussion. (2 academic credits) Survival Analysis
Mei-Cheng Wang
(140.606.11) M T W Th F 1:30 p.m. – 5:00 p.m.
The basic concepts of survival analysis are discussed, including hazard functions, survival functions, types of censoring, Kaplan-Meier estimates, logrank tests, and the generalized Wilcoxin tests. Parametric inference includes the exponential and Weibull distribution. We will also discuss the proportional hazard models and extensions to time-dependent covariates. Clinical and epidemiological examples will be used to illustrate the various statistical procedures. Hands-on experience with computer software will be provided. Enrollment limited. (2 academic credits)
EVENING 5:00 p.m. - 7:20 p.m. Epidemiology of HIV/AIDS
Homayoon Farzadegan
(340.649.11) M T W Th F (and two noon-time seminars)
This course will deal with the epidemiology of infection with human immunodeficiency virus (HIV) and AIDS. Current knowledge of the natural history, biology, virology, epidemiology and clinical aspects of AIDS as well as treatment and vaccine clinical trials against HIV will be reviewed. Descriptive, analytic and experimental epidemiologic studies will be critically reviewed to provide a synthesis of our current understanding of the pathogenesis of this infectious disease. No prerequisites. However, an understanding of basic science concepts and biology will be assumed. Basic epidemiological principles and other quantitative skills will prove useful in understanding the distribution of the disease and in interpreting research findings. (2 academic credits)
June 23 – June 27
MORNING 8:30 a.m. - noon History of Epidemiologic Methods and Concepts
Alfredo Morabia
(340.857.11) M T W Th F
Focus is on the historical perspective of the evolution of epidemiologic ideas (e.g., study designs) and concepts (e.g, measures of outcome occurrence and effect, confounding, bias, interaction and causal inference), that constitute today's epidemiology. For each topic, reviews and discusses the historical contexts and some landmark studies that led to specific innovationsin terms of group comparisons, population thinking and framing of hypotheses. Some of the discussions are supported by exercises. Concluding discussions are on the historical conditions for the emergence of epidemiology as a scientific discipline, the phases it went through and its potential future developments.
Biostatistics Analysis Of Epidemiologic Data II: Poisson And Conditional Logistic Regression Analysis
Steve Selvin
(140.677.11) M T W Th F
Presents count data as occurring in epidemiologic research. Presents Poisson regression methods for counted responses. Describes Poisson models for application to morbidity and mortality outcomes. Discusses matched pairs data and analysis. Presents conditional logistic models for matched data. Presents randomization tests and bootstrap estimation techniques. (2 academic credits)
Genetic Epidemiology in Populations
M. Daniele Fallin
(340. 670.11) M T W Th F
This course will cover designs and methods for genetic epidemiology studies of unrelated individuals. Several population genetics concepts relevant to understanding genetic epidemiology designs and statistical tools will be introduced including concepts of quantitative and qualitative traits, genetic risk models, migration and admixture, inbreeding and allele/haplotype frequency estimation. Methods for the evaluation of single and multiple genetic loci in the context of direct and indirect (linkage disequilbrium) associations with human disease will then be addressed. Methods for gene-gene and gene-environment interaction assessment will also be presented. The lecture material will be supplemented with examples using real and simulated data and currently available software. Prerequisites: Basic knowledge of epidemiology and biostatistics. Enrollment limited; students are required to bring a laptop computer to the class (2 academic credits) Clinical Trials: Issues and Controversies
Lawrence J. Appel
(340.635.11) M T W Th F
A myriad of complex issues surround the design, analysis and interpretation of clinical trials. This course will cover certain of these common issues and controversies. Topics will include selection of the study population (including issues related to enrollment of minorities and women); choice of "control" and "active" treatments including use of placebos; issues pertaining to informed consent; use of intermediate (or pre-clinical) outcomes; trials in developing countries and premature termination of trials. Examples of published, on-going and planned studies will be used. A visit to a clinical trials research unit will be arranged. Prerequisites: Basic epidemiology. (2 academic credits) AFTERNOON Molecular Biology for Genetic Epidemiology
Floyd Bryant
(340.665.11) M T W Th F 1:30 p.m. – 3:00 p.m.
The manipulation and analysis of DNA samples has become fundamental to research including molecular and genetic epidemiology. This course will provide basic knowledge of commonly used recombinant DNA techniques involved in genetic epidemiology and genomics including gene and cDNA isolation, PCR, RFLP analysis, mutational analysis, detection of polymorphisms, SNP analysis, mini and microsatellite detection, and genetic screening. (1 academic credit) Perspectives on Management of Epidemiologic Studies
Joel Hill
(340.634.11) M T W Th F 3:30 p.m. – 5:00 p.m
This is an introductory course dealing with the practical issues of management relating to multi-center cohort studies. Discussion topics include staffing, how much and who, space, how much and where; recruitment and retention of a prospective, longitudinal cohort, quality control procedures and standardization of interviews. Additionally, there are discussions about collaboration within and between field centers as well as conflict management and team building. Presentation of assigned readings and lectures will be the basis for group discussion. The class will also tackle a problem related to a specific issue in their home environment. There are no prerequisites although some field experience would be helpful. This course is complementary with “Conducting Epidemiological Research.” (1 academic credit) Public Health Dimensions of Global Tuberculosis Control
Jonathan Golub, Jaap Broekmans, Richard Chaisson, Jacques Grosset
(340.859.11) M T W Th F 1:30 p.m. – 5:00 p.m.
Reviews the public health dimensions of global tuberculosis control. It examines the global disease burden and its economic impact with a special reference to the high-burden countries. Describes the history and current status of the global response, including a critical examination of the DOTS Strategy, the new Stop TB Strategy and the role of newly established global institutions (e.g. Stop TB Partnership, Global Fund to Fight AIDS, Tuberculosis and Malaria). Examines the challenges of TB-HIV, MDR- and XDR-TB, and Public Private Mix -DOTS. Research into new tools and interventions will be highlighted. Illustrates the public health dimensions of national program implementation using concrete examples from the experience in high-burden countries. (2 academic credits) Topics In Advanced Nutritional Epidemiology
Youfa Wang
(340.672.11) M T W Th F 1:30 p.m. – 5:00 p.m.
This course is designed for students who have taken an introductory course “Nutritional Epidemiology” and/or those who want to learn further methodological aspects of nutritional epidemiologic research and gain hands-on data analysis experience. It teaches students the methods and techniques to study dietary patterns, dietary quality, child growth, relationship between nutrition and health outcomes, energy adjustment, and agreement between assessments? (e.g., analysis approaches used in dietary assessment validation studies). Sample key analysis approaches include factor analysis, growth curve models, regression analysis, and mixed models. Student will also learn how to address nutrition- and health-related questions using existing national and international nutrition-related survey data sets. Students will be able to gain an understanding of the main issues to be covered, as well as hands on experience in data analysis and result interpretation through working on real data sets in lab sessions and assignments. Students can choose to use STATA or SAS at their preference. It is desirable if the students have prior experience with one of these software packages. Students are required to bring a laptop computer to the class. (2 academic credits)
Tobacco Control Leadership
Ann-Michele Gundlach
(340.679.11) M T W Th F 1:30 p.m. – 5:00 p.m.
The underlying premise of this course is that the exercise of principled leadership creates conditions which enable organizations and their members to be effective and adaptive in order to achieve those goals. Through lectures and discussion students will develop an understanding of the role of the tobacco control leader, and the essential knowledge and skills this role requires. The course is designed to provide a framework for understanding the process of working effectively with and leading others. Students will be able t explain the nature of organizational leadership; describe the requirements of effective public health and tobacco control leadership; apply principles and theories of leadership to current tobacco control issues and challenges; develop a personal philosophy and approach to the practice of leadership. (2 academic credits)GPS and Spatial Data Collection for Epidemiologic Studies
WIlliam Pan and Pablo Yori
223.862.11
Provides the knowledge, skills and hands-on experience necessary to use GPS technology to collect and process spatial attribute data for immediate use for spatial applications in epidemiology, statistics, demography, and econometrics. Students will learn how t explain how GPS technologies are used; use spatial location standards, methods, and USGS map accuracy standards; use GPS hardware and software to plan a GPS field survey, collect geographic data in the field, and conduct real-time and post-processing differential GPS (DGPS); Integrate DGPS data in a GIS database. Enrollment limited; students must bring a laptop computer to the class. (2 academic credits)EVENING 5:00 p.m. - 7:20 p.m.
Advanced Issues on HIV/AIDS
Homayoon Farzadegan
(340.659.11) M T W Th F (and two noon-time seminars)
Discusses the following topics at an advanced level: (1) Basic science and pathogenesis of HIV/AIDS, (2) Dynamics of the HIV epidemic in five continents, (3) Clinical management of HIV/AIDS in developed and developing countries, (4) Prevention and control modalities against HIV/AIDS, and (5) Future growth of the HIV/AIDS epidemic with special reference to global economic impact of HIV vaccine and eradication issues of HIV/AIDS. Prerequisite: Completion of 340.649.11. Students who have successfully completed 340.844 should not enroll in this course (2 academic credits)
June 30 – July 3 ALL DAY 8:30 a.m. - 4:00 p.m. Design of Clinical Experiments Introduces the application of traditional experimental design theory to biomedical control experiments, including event time studies. Stresses methods of bias and variability, particularly randomization, blocking, factorial designs, stratification, and adequate sample size. Emphasizes clinical trials and other types of medical experiments likely to be encountered by biometric researchers. Discusses elements of analysis when they relate to the design principles. (3 academic credits) MORNING 8:30 a.m. - 12:30 p.m. Biostatistics Analysis Of Epidemiologic Data III: Semi Parametric Methods
Steve Selvin
(140.678.11) M T W Th
Describes semiparametric statistical techniques as applied to epidemiologic data. Describes smoothing techniques (local linear methods, kernel methods and splines). Introduces the Weibull hazard model and uses it to describe the mortality patterns among untreated AIDS patients. (This model illustrates the principles of a parametric approach to the study of survival data.) Discusses and applies to the same AIDS data more general and widely used semiparametric proportional hazards model approaches. (2 academic credits)
Applications of the Case-Control Method
Moyses Szklo
(340.605.11) M T W Th
Following a review of the basic strengths and problems of the case-control method, the course will examine the application of this most popular method of investigation. Its use will be discussed in evaluation of risk factors, interventions, and as a surveillance tool. The course format will be based on lectures and lab work. Prerequisites: Completion of basic courses in epidemiology and biostatistics. (2 academic credits) Epidemiologic Applications of GIS
Carlos Castillo-Salgado and Enrique Loyola-Elizondo
(340.701.11) M T W Th
This introductory course will present the methods and uses of epidemiology towards the development and application of Geographic Information Systems (GIS) in public health. Emphasis is made on the potential of GIS as an epidemiological analysis tool for describing the magnitude of priority health problems, identifying health determinants and supporting health decision-making. Specific topics will include epidemiological risk assessment and GIS, thematic mapping of unmet health needs, malaria risk assessment and GIS application for identifying public health problems. The course includes hands-on experience and laboratory exercises using different public domain and ESRI software. A required GIS textbook will be available for purchase at Orientation. Should not be taken by students who completed 223.842 in the Winter Institute 2001 or 340.881.11 in the Epidemiology and Biostatistics Summer Institute. Prerequisites: Basic knowledge of epidemiology and biostatistics. (2 academic credits)
Social Epidemiology
Thomas Glass
(340.628.11) M T W Th
This one-week course will provide students with a systematic and selective overview of conceptual approaches and research findings related to the impact of social context on the health of populations. Each session will highlight a different area of research on the frontier of this emerging field. Among the social processes to be examined are social inequalities (including social class differences as well as the effects of income inequality per se), social capital and social cohesion, social networks and support, neighborhood characteristics, and racism and discrimination. Emphasis will be placed on extending the causal chain thought to be associated with patterns of acute and chronic disease to include “upstream” factors related to social context. The course will include discussion of methods related to the study of social factors across multiple levels, however, this is not intended to be a methods course. The course will be taught as a seminar with limited lecture material and extensive discussions and in-class presentation by fellow participants. Some analytic writing will be required. Some previous exposure to social science methods and theory is advised but not required. (2 academic credits)
Gene Expression Data Analysis
Carlo Colantuoni
(140.687.11) M T W Th
The goal of this course is to introduce statistical concepts and tools necessary to analyze gene expression array data. Topics will include basic data analysis, including background on gene expression measurement technology, basic microarray informatics, array normalization and bias adjustment, methods for computing gene expression indicators in oligonucleotide arrays. Methods for identifying genes that are differentially expressed across experiments will also be covered. Survey methods for genome-wide analysis of expression patterns, including clustering, principal components, and binary classification algorithms such as discriminant analysis, recursive partitioning and support vector machines will be discussed. Basic understanding of biostatistical principles, including regression, is required for this course. (2 academic credits)
AFTERNOON
Multilevel Models
Elizabeth Johnson
(140.607.11) M T W Th 1:30 p.m. – 3:30 p.m.
This course will give an overview of "multilevel statistical models" and their application in public health and biomedical research. Multilevel models are regression models in which the predictor and outcome variables can occur at multiple levels of aggegration: for example, at the personal, family, neighborhood, community and regional levels. They are used to ask questions about the influence of factors at different levels and about their interactions. Multilevel models also account for clustering of outcomes and measurement error in the predictor variables. In this course, we will focus on the main ideas and on examples of multi-level models from public health research. Students will learn to formulate their substantive questions in terms of a multilevel model and to interpret the results of basic analyses. Previous experience with regression analysis is required. (1 academic credit) Conducting Epidemiological Research
Lisa Jacobson
(340.614.11) M T W Th 1:30 p.m. – 3:30 p.m
This course covers some of the applications of epidemiologic principles in the conduct of observational studies as taught in advanced epidemiologic methods, with specific focus on case-control studies and cohort studies. Topics that will be covered include the infrastructure needed for single-site and multi-site studies, selection bias and analytical intent in the determination of populations and methods for recruitment, development of a manual of operations and forms for data collection and administration, data management tools, implementation and review of quality assurance, specimen repository tracking, and useful statistics for evaluating the progress of the study. This applications course is complementary with "Perspectives on Management of Epidemiologic Studies." Prerequisite: intermediate level courses in both epidemiology and biostatistics. (1 academic credit) Introduction to the SAS Statistical Package
Lucy Meoni
(140.605.11) M T W Th 1:30 p.m. – 5:30 p.m.
Through this course, the student will become an adept user of the SAS statistical package, mastering the skills needed for effective data management, data manipulation, and data analysis. The student will learn how to document work, and make the work replicable. Graphical techniques for displaying data will be discussed. While this course will use the SAS statistical package exclusively, much of the technical knowledge and some of the computing techniques will be applicable to any statistical package. No prerequisites. (2 academic credits)
Methods and Applications of Cohort Studies
Alvaro Munoz and Christopher Cox
(340.706.11) M T W Th 1:30 p.m. – 5:30 p.m.
Topics covered in the course include: definition and basic characteristics of cohort studies; recruitment and follow-up procedures; assessment of exposure and outcome; descriptive analysis of cohort data; methods to estimate and compare incidence rates, including Poisson regression; methods for the analysis of disease-free and survival times; estimation and testing of relative hazards (Cox regression) and of relative times; methods to nest case-control and case-cohort designs in cohort studies; procedures to combine prevalent and incident subcohorts; and the role of cohort studies in evaluating interventions and in guiding public policy. Methods will be illustrated using cohort studies in which faculty have been directly involved. Prerequisite: Intermediate-level courses in both epidemiology and biostatistics and some familiarity with data analysis software packages. Students who have successfully completed 340.603 Cohort Studies: Design,Analysis and Applications or 340.864 SS/R: Methods and Applications of Cohort Studies should not enroll in this course (2 academic credits)
Epidemiologic Methods for Planning and Evaluating Health Services
Carlos Castillo-Salgado
(340.638.11) M T W Th 1:30 p.m. – 5:30 p.m.
The use of epidemiologic methods in the planning and evaluation of health services is the primary focus of this course. Various epidemiologic techniques and designs will be reviewed as they relate to assessments of health care needs, priority setting, risk assessment, regional health planning, validity assessment, access to care and program evaluation. The format of the course will be a combination of lectures, laboratories and class discussions. The lectures will present topics such as the application of epidemiologic methods in health priority setting, health care needs, validity and reliability of public health tools, evaluation of health interventions and the epidemiologic approach to decision-making. The laboratory sessions and discussions will consider issues in health services research within the practice environments of primary and public health services. Prerequisite: Completions of basic courses in epidemiology and biostatistics. (2 academic credits)
Advanced Data Analysis Workshop
Patrick Tarwater
(140.620.11) M T W Th 1:30 p.m. – 5:30 p.m.
Covers methods for the organization, management, exploration, and statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models. Students apply these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Topics covered include generalized linear models, product-limit (Kaplan-Meier) estimation, Cox proportional hazards model. Enrollment limited; students must have a laptop computer with STATA 9 installed. (2 academic credits)
One-Week Courses| Two-Week Courses| Three-Week Courses Monday, June 16 Genetic Epidemiology and Genome Wide Association Studies
Terri Beaty and Kung-Yee Liang
340.858.11 8:30 a.m. – 5:00 p.m.
This one-day workshop presents recent data from genome wide association studies (GWAS) of complex diseases, emphasizing their successes as well as technical, analytical, and epidemiological problems in their interpretation. Presents both case-control or family-based study designs, and speakers cover issues of genotyping, study design and statistical strategies, as well as strategies to maximize valid inferences in the presence of gene-environment interactions. (I academic credit)
Saturday, June 21 Critical Reading of the Epidemiologic Literature
Moyses Szklo
340.658.11 8:30 a.m. – 5:00 p.m.
In this one-day workshop, students will develop skills in critical reading of epidemiological reports. A case-study, problem-based learning approach will be used. Students will read several articles in advance of the course and prepare critiques. During the course, a blend of lectures and discussions will be used. (I academic credit)
Saturday, June 28 Methods for Clinical and Translational Research
Jonathan Samet and Scott Zeger
340.848.11 8:30 a.m. – 5:00 p.m.
This course provides an overview of the methods of translational research. Emphasizes developing skills in the interpretation and application of findings of translational research. Topics include study design, biomarkers, statistical analyses, validation strategies, and evidence synthesis methods. (I academic credit)
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