EPI 530, 545, and 550 and/or instructor permission.

This course covers epidemiologic concepts in further depth than previous methods courses and provides an overview of advanced topics in the analysis of epidemiologic data. The course reviews basic concepts behind cohort studies, and introduces students to fundamental survival analysis concepts, including risk and survival, hazards, competing risks, cause-specific and sub-distribution risk, risk difference, and risk ratio estimators. Generalized linear models for conditionally and marginally adjusted risk differences and ratios, as well as methods for correct variance estimation. Concepts of time-dependent confoundinng, and methods that can be used to analyze complex longitudinal data (IP weighting, marginal standardization). This is a required course for students in the MSPH and PhD Epidemiology program.

The focus of this course is on the epidemiology of obesity, its determinants, and consequences, and population-based methods for investigating obesity. The course will entail a survey of obesity research, including: (1) the biology and physiology of adiposity; (2) behavioral, environmental, social, and genetic determinants of obesity; and (3) the health consequences of obesity. Methodologic concepts in the practice of research, including those related to measurement, modeling and interpretation, will be emphasized in this course.

Prerequisites: Prior coursework in introductory GIS (e.g. INFO530) and multivariable regression. Spatial EPI includes both the characterization of the geographic distribution of disease, and the investigation of the role of spatially structured processes/exposures as determinants of disease in populations. Upon completion, students will be able to evaluate epidemiologic research using common spatial analytic approaches; match appropriate methods to specific epidemiologic needs or questions; prepare effective visualizations of spatial data; conduct statistical cluster or autocorrelation analysis; estimate model-based disease risk maps; and conduct basic exploratory spatial regression.

This course will acquaint students with the comprehensive nature of public health preparedness and response efforts for disasters whether natural or man-made. Students will get introduced to practical considerations of public health preparedness from the local, state, and national levels. Discussions of specific preparedness elements necessary for responses to natural disasters and man-made events will be covered, often in consultation with guest speakers and experts in various aspects of public health preparedness and practice. Ethical and legal issues related to preparedness and bioterrorism are also discussed. Students can expect interactive discussions, assigned readings, in-class exercises, and a project and/or paper.

Prerequisites: EPI 530 or EPI 504, BIOS 500 and knowledge of SAS. This course introduces students to data sources and methods commonly used by epidemiologists in state or provincial health departments. Data sources include websites, census, vital statistics, surveys (PRAMS). Methods include record linkage, questionnaire design, mapping, trend analysis, perinatal periods of risk, cluster investigation, small number analysis and secondary data analysis.

Provides an introduction to the entire spectrum of vaccines and immunization: from basic bench research through testing, licensure, and use; program design, implementation and evaluation; and social, economic, and political factors affecting the use of vaccines. Primary emphasis will be on the international setting but examples will also be taken from developed countries. Cross-listed with GH 566.

Prerequisites: EPI 530 or instructor permission. This course introduces the student to the epidemiology of aging populations. Aging and health are characteristics of both individuals and populations. Students will be introduced to the distribution of and trends in chronic disease morbidity, functional disability, and mortality, with a focus on methods for epidemiologic research in aging populations.

Pre-requisites: EPI 530, EPI 534 and EPI 540 or 545 or instructor permission.

Observational epidemiologic studies yield estimates of effect that differ from the true effect because of random error and systematic error. Epidemiologists design studies and analyses to minimize both sources of error. When presenting results, epidemiologists use statistics to quantify the impact of random error on estimates of effect, but often only qualitatively describe residual systematic error (uncontrolled bias). Bias analysis provides one method of quantifying residual systematic error. Students in this course will learn how to use simple, multidimensional, and probabilistic bias analyses, as well as direct bias modeling (regression calibration and missing data methods) to account for systematic error in their estimates of effect. Students should expect to gain new skills, as the emphasis of the course will be on the implementation and conduct of bias analysis, rather than statistical theory.

Prerequisites: EPI 530, EPI 540, EPI 534, and experience using R. The course will provide an overview of the history, concepts and analytical methods that specifically apply to the study of infectious diseases. Topics covered include measures of frequency, burden and natural history; immune-epidemiology; vaccine epidemiology; methods for emerging infectious diseases; fundamentals of modeling and the application of classic epi methods to infectious diseases. This is a required course for the Infectious Disease Epidemiology certificate program.

This course will present the conceptual theory, mathematical framework, and computational tools to conduct mechanistic modeling of infectious diseases.