This course will provide an introduction to public health practices and cover management basics as applied to the public health field. The topics covered in the course will be examined through the lenses of prevention, social justice and the role of governmental public health. In Part I of the course, we will study basic public health concepts, core public health functions and practices, public health infrastructure at the local, state and federal levels, and the major areas of public health services and interventions. In Part II, we will cover management principles and functions such as planning, organizing, controlling and leading. We will apply these concepts to the administration of public health organizations.

The goal of the Capstone project is to provide students the opportunity to demonstrate knowledge and skills acquired in the academic coursework and through practicum experience. The objective is to enable the student to work on a project which translates both general and discipline specific information into public health practice. Students should complete the core, program specific courses. We recommend to split credits over last two semesters and register 1 credit each semester.

This course introduces students to statistical computing. The emphasis is on manipulating data sets and basic statistical procedures such as t-tests, chi-square tests, and correlations. The course currently focuses on the use of SAS and STATA software packages., data importation from various sources, cleaning, validation, subsetting, merging, and transforming datasets); Construct clear and concise documentation of newly created datasets; Use SAS data-step programming, macros, and built-in procedures for statistical analysis and visualization (i.e., PROC MEANS, FREQ, SGPLOT, and UNIVARIATE); Demonstrate the ability to use descriptive techniques to summarize public health data (i.e., t-tests, chi-square tests, and basic regression models); Describe the results of basic statistical analyses.

This course is a survey course designed to expose MPH and other interested inter-professional students, e.g., nursing and dietetic students, to the multiple domains of the worldwide obesity epidemic. The course will explore determinants, outcomes and public health policy associated with obesity from the perspective of energy balance, i.e., that ultimately all determinants and outcomes of obesity.

This course covers public health topics related to non-communicable diseases (NCDs). The course explores topics such as: burden of NCDs in populations; the conceptual frameworks for studying chronic disease causation and control; the epidemiology of cardiometabolic diseases as well as the epidemiologic transition in relation to risk factors for the major chronic diseases (e.g. nutrition, obesity, physical exercise, alcohol and tobacco use) as well as upstream factors impacting on diseases such as food policy and the built environment; integrated healthcare services and public health interventions; and, the study designs used to assess associations between exposures and NCDs.

This course introduces students to the scope of health services research by addressing issues central to understanding and applying modern research to public health and health policy. Formulate questions and develop studies using primary data collection approach that are timely and relevant to contemporary organization, financing, and delivery of U.S. public health.

This course explores how the law can be utilized to promote, or impede, proposed public health interventions at the local, state, federal level. Students review key theories of public health law that examine the role of the legislature, executive agencies, and the courts in crafting, executing, reviewing public health policy. This course is geared towards MPH students in Public Health Policy and Management track, and no prior training in law or legal analysis is assumed.

Course will cover linear and logistic regression and ANOVA. Students will utilize STATA software for hypothesis testing.

This course will examine selected topics in health economics with major implications for healthcare delivery, healthcare financing and clinical and public health research. Essential economic theories and methods for exploring each topic will be discussed along a review of existing empirical research.

This course will provide an introduction to the issues and methods of health policy analysis. Health policy analysis requires several distinct sets of skills: technical understanding of analytical tools, understanding the policy and managerial context within and outside of your organization, and the ability to produce and communicate practical advice. This is a track-specific requirement for MPH Graduates in the Health Policy track.

This course covers a broad overview of statistical models and estimation methods for outcome variables (normal and non-normal) that are clustered or measured repeatedly in time or space. The focus is on applications and computer software methods for correlated regression models, including ANOVA based methods, hierarchical linear models, etc.

This course provides an introduction overview of the health consequences associated with climate change and the local, federal, and global response to mitigate these negative health outcomes. During the course students will be expected incorporate course content and develop a realistic response public health plan to climate change for a locality of their choosing. This course is offered both online and in-person.

This course will provide an overview of the NIH extramural funding process, with additional information on funding opportunities outside NIH. Students will learn the key components of successful grants and factors that may lead to grants not being reviewed favorably. The focus will be on grant writing skills.

This course targets the application of sophisticated statistical methodologies to enhance the efficacy and precision of public health interventions. At the heart of this course is a rigorous examination of strategies for reducing bias in observational studies through advanced techniques such as imputation for missing data and propensity scores. The curriculum is expanded to include psychometric analysis, providing essential tools for the evaluation of measurement instruments, and ecological analysis, which aids in the interpretation of population-level health outcomes. A significant addition to this course is the analysis of screening and diagnostic tests, focusing on studying measures of accuracy and agreement critical for evaluating the performance of these tests in public health. The course also explores the complexities of survey design, offering insights into managing and analyzing data from multifaceted study designs to ensure the reliability and validity of intervention assessments.

This course delves into the analysis and interpretation of data from Electronic Health Records (EHRs), a cornerstone of clinical, epidemiologic, and translational research. Emphasizing a hands-on approach, it covers EHR system fundamentals, data extraction and cleaning, privacy standards, case identification, study design, and advanced statistical analysis. Students will learn to navigate EHR data structures, medical vocabularies, and relational databases, applying these skills to design research studies and create patient cohorts. The goal is to equip students with the ability to harness EHR data for innovative healthcare solutions., ICD, CPT, NDC, SNOMED, and LOINC codes) for accurate case identification; Develop skills in constructing patient cohorts and extracting relevant data; Identify controls and apply propensity score matching in observational research; Design robust matched case-control and retrospective cohort studies using EHR data; Recognize privacy and security standards, including HIPAA regulations; Apply advanced statistical methods to analyze EHR data and assess research findings critically.

This course is designed to navigate the intersection of public health data, visual communication, and ethical representation, focusing on creating impactful visuals that cater to diverse audiences including patients, healthcare providers, policymakers, and the broader community. It emphasizes the ethical considerations in data visualization, tackling potential biases, and ensuring visuals are both informative and accessible. Through practical applications, students will learn to craft infographics, community health maps, dashboards, and effective manuscript tables, all while understanding the unique needs of different user groups. The course will explore advanced visualization techniques like heatmaps, interaction visuals, and temporal data displays, equipping students with the skills to present complex health data.