The course descriptions below are correct to the best of our knowledge as of April 2016. Instructors reserve the right to update and/or otherwise alter course descriptions as necessary after publication. The listing of a course description here does not guarantee a course’s being offered in a particular semester. The Course Rotation Guide lists the expected semester a course will be taught. Please refer to the published schedule of classes for confirmation a class is actually being taught and for specific course meeting dates and times. In addition to the courses listed in the Bulletin and courses approved after April 1, SPH degree candidates may register for a directed (independent) study with a full-time SPH faculty member. For more information, speak with your faculty advisor or a staff member in the SPH Registrar’s office.
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SPH BS 831: Genomics Data Mining and Statistics
In this course, students will be presented with the methods for the analysis of gene expression data measured through microarrays. The course will start with a review of the basic biology of gene expression and an overview of microarray technology. The course will then describe the statistical techniques used to compare gene expression across different conditions and it will progress to describe the analysis of more complex experiments designed to identify genes with similar functions and to build models for molecular classification. The statistical techniques described in this course will include general methods for comparing population means, clustering, classification, simple graphical models and Bayesian networks. Methods for computational and biological validation will be discussed.
SPH BS 845: Applied Statistical Modeling and Programming in R
Graduate Prerequisites: The MPH biostatistics core core and SPH BS723 or consent of instructor
This course covers applications of modern statistical methods using R, a free and open source statistical computing package with powerful yet intuitive graphic tools. R is under more active development for new methods than other packages. We will first review data manipulation and programming in R, then cover theory and applications in R for topics such as linear and smooth regressions, survival analysis, mixed effects model, tree based methods, multivariate analysis, boot strapping and permutation.
SPH BS 849: Bayesian Modeling for Biomedical Research & Public Health
The purpose of this course is to present Bayesian modeling techniques in a variety of data analysis applications, including both hypothesis and data driven modeling. The course will start with an overview of Bayesian principles through simple statistical models that will be used to introduce the concept of marginal and conditional independence, graphical modeling and stochastic computations. The course will proceed with the description of advanced Bayesian methods for estimation of odds and risk in observational studies, multiple regression modeling, loglinear and logistic regression, hierarchical models, and latent class modeling including hidden Markov models and application to model-based clustering. Applications from genetics, genomics, and observational studies will be included. These topics will be taught using real examples, class discussion and critical reading. Students will be asked to analyze real data sets in their homework and final paper.
SPH BS 851: Applied Statistics in Clinical Trials I
Graduate Prerequisites: The MPH epidemiology and biostatistics core course requirements and SPH BS723 or consent of instructor, firstname.lastname@example.org
This is an intermediate statistics course, focused on statistical issues applicable to analyzing efficacy data for clinical trials. Topics include design and analysis considerations for clinical trials, such as randomization and sample size determination, and the application of statistical methods such as analysis of variance, logistic regression and survival analysis to superiority and non-inferiority clinical trials. This course includes lectures and computer instructions. Upon completion of the course, the student will be able to have a working knowledge of how to collect and manage clinical trial data; will be to analyze continuous, dichotomous, and time-to-event clinical trial data; and will be able to contribute to the statistical portions of a clinical trial study design. The student will also gain the overall knowledge required to interpret clinical trial statistical results.
SPH BS 852: Statistical Methods in Epidemiology
Graduate Prerequisites: The biostatistics and epidemiology core course requirements and BS723. Cannot be taken concurrently with BS805.
This course covers study design and intermediate-level data analysis techniques for handling confounding in epidemiologic studies. Confounding is carefully defined and distinguished from interaction. Course content covers stratification and multivariable techniques for controlling confounding in both matched and independent sample study designs, including analysis of covariance, logistic regression, and proportional hazards models. Model fit and prediction are discussed. Students are required to apply these methods with the aid of computerized statistical packages. BS805 and BS852 cannot be taken in the same semester without approval from both faculty. Students should speak to faculty of both courses before registering.
SPH BS 853: Generalized Linear Models with Applications
Graduate Prerequisites: The biostatistics and epidemiology MPH core course requirements and BS805 or consent of instructor
This course introduces statistical models for the analysis of quantitative and qualitative data, of the types usually encountered in health science research. The statistical models discussed include: Logistic regression for binary and binomial data, Nominal and Ordinal Multinomial logistic regression for multinomial data, Poisson regression for count data, and Gamma regression for data with constant coefficient of variation. All of these models are covered as special cases of the Generalized Linear Statistical Model, which provides an overarching statistical framework for these models. We will also introduce Generalized Estimating Equations (GEE) as an extension to the generalized models to the case of repeated measures data. The course emphasizes practical applications, making extensive use of SAS for data analysis.
SPH BS 854: Bayesian Methods in Clinical Trials
Graduate Prerequisites: SPH BS851 or BS861 or consent of instructor
Bayesian statistical methods use prior information or beliefs, along with the current data, to guide the search for parameter estimates. In the Bayesian paradigm probabilities are subjective beliefs. Prior information/ beliefs are input as a distribution, and the data then helps refine that distribution. The choice of prior distributions, posterior updating, as well as dedicated computing techniques are introduced through simple examples. Bayesian methods for design, monitoring analysis for randomized clinical trials are taught in this class. These methods are contrasted with traditional (frequentist) methods. The emphasis will be on concepts. Examples are case studies from the instructors' work and from medical literature. R will be the main computing tool used.
SPH BS 855: Bayesian Modeling for Biomedical Research & Public Health
Graduate Prerequisites: BS805 or MA684 and MA581/MA582 or equivalent or consent
The purpose of this course is to present Bayesian modeling techniques in a variety of data analysis applications, including both hypothesis and data driven modeling. The course will start with an overview of Bayesian principles through simple statistical models that will be used to introduce the concept of marginal and conditional independence, graphical modeling and stochastic computations. The course will proceed with the description of advanced Bayesian methods for estimation of odds and risk in observational studies, multiple regression modeling, loglinear and logistic regression, latent class modeling including hidden Markov models and application to model-based clustering, graphical models and Bayesian networks. Applications from genetics, genomics, and observational studies will be included. These topics will be taught using real examples, class discussion and critical reading. Students will be asked to analyze real data sets in their homework and final project.
SPH BS 856: Adaptive Designs for Clinical Trials
Graduate Prerequisites: SPH BS851
An adaptive design is a clinical trial design that allows modification to aspects of the trial after its initiation without undermining the validity and integrity of the trial. Adaptive designs have become very popular in the pharmaceutical industry because they can increase the probability of success, considerably reduce the cost and time of the overall drug development process. With a recent rapid development in this area, there is a high demand for statisticians proficient in designing and conducting adaptive clinical trials. Students will learn different (both frequentist and Bayesian) adaptive designs and gain hands-on experiences on adaptive randomization, adaptive dose-finding, group sequential, and sample-size reestimation designs.
SPH BS 857: Analysis of Correlated Data
Graduate Prerequisites: SPH BS805 or BS852
The purpose of this advanced seminar is to present some of the modern methods for analyzing tricorrelated observations. Such data may arise in longitudinal studies where repeated observations are collected on study subjects or in studies in which there is a natural clustering of observations, such as a multi-center study of observations clustered within families. Students start with a review of methods for repeated measures analysis of variance and proceed to more complicated study designs. The course presents both likelihood-based methods and quasi-likelihood methods. Marginal, random effects and transition models are discussed. Students apply these methods in homework assignments and a project.
SPH BS 858: Statistical Genetics I
Graduate Prerequisites: SPH BS723, BS730 or equivalent as determined by instructor.
This course covers a variety of statistical applications to human genetic data, including collection and data management of genetic and family history information, and statistical techniques used to identify genes contributing to disease and quantitative traits in humans. Specific topics include basic population genetics, linkage analysis and genetic association analyses with related and unrelated individuals.
SPH BS 859: Applied Genetic Analysis
Graduate Prerequisites: SPH BS858 or EP763.
Statistical tools such as linkage and association analysis are used to unravel the genetic component of complex disease. Investigators interested in the genetic analysis of complex traits need a basic understanding of the strengths and weaknesses of these methodologies. This course will provide the student with practical, applied experience in performing linkage and association analyses, including genome-wide analyses. Special emphasis is placed on understanding assumptions and issues related to statistical methodologies for genetic analysis to identify genes influencing complex traits. Students will use specialized genetics software for homework assignments.
SPH BS 860: Statistical Genetics II
Graduate Prerequisites: SPH BS858 or consent of instructor (email@example.com).
This course covers current topics in statistical genetics, with emphasis on how statistical techniques can be used with various types of genetics data for mapping genes responsible/contributing to complex human diseases. Topics such as genetics map functions, gene mapping in experimental organisms, advanced linkage analysis methods, statistical approaches for the analysis of genome-wide high density SNP scans in unrelated and family samples will be discussed.
SPH BS 861: Applied Statistics in Clinical Trials II
Graduate Prerequisites: BS851 or consent of instructor (firstname.lastname@example.org).
This course covers a variety of biostatistical topics in clinical trials, including presentation of statistical results to regulatory agencies for product approval, analysis of safety data, intent-to-treat analyses and handling of missing data, interim analyses and adaptive designs, and analyses of multiple endpoints. Upon completion of the course, students will be able to make and defend decisions for many study designs and for issues faced when analyzing efficacy and safety data from clinical trials. Students will also be able to present, in a written format following standard guidelines accepted by the clinical trials' community, results of such efficacy and safety analyses to the medical reviewers and statistical reviewers of regulatory agencies.
SPH EH 705: Toxicology for Public Health
This is a two credit course designed to introduce the basic concepts of toxicology to students from multiple fields and disciplines. The objectives of the first part of the course are to detail the routes of exposure to xenobiotics (chemicals and drugs) and to trace the biochemical and biological pathways through which xenobiotics are absorbed, metabolized, distributed, excreted and biomonitored. In the second section of the course, we examine the effects of molecular/cellular changes on the function of representative organ systems including the respiratory, endocrine/reproductive, immune, liver, kidney and nervous systems. Students are also introduced to regulatory toxicology and food toxicology. At the completion of the course students are expected to have an extensive toxicology vocabulary. Students will also have a working knowledge of: 1) general toxicological principles, 2) inter-species and inter-individual differences in responses to toxicants, 3) the effects of several key toxicants on the normal function of several organ systems, and 4) the basic approach to regulatory toxicology. The overall objective of this course is to provide the student with an introduction to the language and principles of toxicology such that these principles may be applied to public health situations and communicated to the general public.
SPH EH 707: PHYSIOLOGY FOR PUBLIC HEALTH
This course provides a foundation in the basic mechanisms required for human health. It is designed for students who have little or no background in the biological sciences. Students will learn the fundamentals of human physiology, from the molecular/cellular level to the level of the various organs and organ systems. The integration of organ system functions to maintain homeostasis, or health, is explored in depth. After completing this course, students will be able to participate knowledgeably in both technical and non-technical discussions of public health issues. Moreover, upon entering the workforce as practitioners, they will be able to effectively communicate with and educate the public about actually how public health activities and interventions serve to promote healthy lives.
SPH EH 710: Physiological Mechanisms of Health and Disease
This course provides students with a detailed working knowledge of the normal mechanisms of human body function. It is most appropriate for MS and PhD students, though it is available to all students. Physiological mechanisms are studied from the molecular level to the level of organ systems, and emphasis is placed on understanding how body processes are regulated and integrated so as to achieve homeostasis characteristic of a normal, healthy individual. Students will become acquainted with both the gross and histological anatomy of major organs. For each system covered, a case study of a disease of significant public health interest is used to reinforce basic physiological principles, and to acquaint students with physiological measurements commonly used in clinical settings. This course is recommended for all students who need a substantive understanding of human physiology for subsequent coursework. This course will be of special value to students whom expect their careers to involve close interaction with health care providers.
SPH EH 725: Analytical Methods in Environmental Health
Graduate Prerequisites: Required for all EH concentrators who have not completed EH765. EH717may be taken concurrently with or prior to EH725.
Students in this course learn the skills, methods and critical thinking framework necessary for upper level environmental health courses and for success as public health professionals. Environmental Health is a field of public health in which environmental hazards and health risks to populations are identified, assessed and managed through a data-driven process. This course extends the depth of concepts taught in EH717 and should be taken concurrently for students entering in the fall semester. We take the opportunity to partner with communities to design and conduct a data collection and analysis effort that is suitable for rigorous analyses with the many tools commonly used in environmental health.
SPH EH 730: Methods in Environmental Health Sciences
This course is one of three foundational courses for the Environmental Hazard Assessment (EHA) Certificate. Environmental health is a field of public health in which environmental hazards and health risks to populations are identified, assessed and managed through a data-driven process. This course extends the depth of concepts taught in the Core curriculum and extends the breadth to teach the scientific and policy aspects of relevant environmental health situations. We take the opportunity to partner with communities to design and conduct a data collection and analysis effort that is suitable for rigorous analyses with the many tools commonly used in environmental health. The methods relevant to the field are taught in the context of the relevant environmental health issues of today. Students are well prepared for upper level (Level 3) environmental health courses and for success as public health professionals.
SPH EH 735: The Environmental Determinants of Infectious Diseases
Graduate Prerequisites: SPH PH709 or EH710 or one year of college biology within last 5 yearswith a B or better
The environment is a key determinant of infectious disease burden in a population. This course presents an overview of how existing and, in particular, changing global environmental factors can affect the transmission cycle of infectious pathogens in both developing and industrialized countries. It examines issues of water, sanitation and hygiene in resource-limited settings that contribute enormously to childhood death due to infectious diarrheal diseases, and to morbidity and mortality due to neglected tropical diseases (NTDs). It also explores how environmental alterations and natural disasters can result in ecological changes that impact on the maintenance and spread of infectious diseases in a community. Sustainable environmental intervention strategies to reduce the burden of infectious diseases will be considered for each of the major diseases covered in class. This course is appropriate for MPH students and undergraduates, especially those interested in biology, global health, and the environment.