MPH Courses

3 Credits

The purpose of the course is to focus on the design, implementation, and evaluation of effective health communication initiatives tailored to diverse populations and settings. Students will examine how communication influences health knowledge, literacy, attitudes, norms, and behaviors, with an emphasis on equity, ethics, and cultural responsiveness.

2 Credits

This course will examine sources, routes, media, and health outcomes associated with biological, chemical and physical agents in the environment. It will cover how these agents affect disease, water and air quality, food safety, and land resources in community and occupational settings.

2 Credits

The Community Engagement Seminar will give students the fundamentals of applying community engagement, organization, and development principles to create successful community public health campaigns. Emphasizing nontraditional approaches and partnerships, and the need to readjust traditional strategies, it discusses organization and development methods optimal for public health practice, including public health ethics, faith-based initiatives in community health, community assessment and measurement methods, coalition building, frameworks for developing health policy, and more.

3 Credits

The public health practicum will enable the MPH student to address the MPH competencies including: (1) evidence-based approaches to public health; (2) public health and health care systems; (3) planning and management to promote health; (4) policy in public health; (5) leadership; (6) communications; (7) interprofessional and/or intersectional practice; and (8) systems thinking. In doing so, students work on projects that focus on:

• Experiential Learning: Students work on projects designed to improve public health, often engaging in research with faculty.
• Networking and Partnerships: Strong ties exist with various partnering organizations to offer opportunities in applied public health, epidemiology, and health policy.
• Competency Development: The practicum aims to build skills in areas such as program planning, assessment, and communication.
• Structure: As part of a fully accredited Council on Education for Public Health (CEPH), the experience is designed to meet rigorous professional standards.

The Public Health Practicum will take place off-campus within the DMV area. It is an Unpaid Practicum. It is for variable credit (1-3 credits). There are 60 contact hours for each credit.

3 Credits

The Capstone Project is the culminating experience required for graduation from the MPH Program. Students apply the knowledge and skills learned in class to public health problems in a chosen skillset or area of interest under the guidance of a Capstone Mentor. The projects should be chosen to help students address their academic interests and afford them an opportunity to master advanced public health competencies. The Capstone satisfied the CEPH Integrated Learning Experience requirement of the MPH degree. Please see Appendix B for more details about capstone project expectations.

3 Credits

Epidemiology overview and history; distributions of disease by time, place and person; association and causality; ecological studies; cross-sectional studies and surveys; case-control studies; analysis of case-control studies; types of bias in case-control studies; cohort studies; analysis of cohort studies; bias in cohort studies; population attributable risk; confounding factors; effect modification (interaction); analysis for confounding and interaction; multivariate analysis; sensitivity, specificity and screening; public health practice and prevention; special issues in cancer epidemiology, infectious disease epidemiology and genetic epidemiology. This course includes a discussion session.

3 Credits

This course builds on the epidemiologic concepts introduced in EPID 5001, with a strong emphasis on causal inference and common study designs. We focus on developing your conceptual understanding over quantitative estimation through a solid foundation in the basic epidemiologic and statistical calculations covered in EPID 5001 and EPID 5003.

By the end of the course, you will be able to grasp causal inference in epidemiologic research, design studies tailored to specific questions with a focus on health equity and recognize common biases, as well as strategies to address them. You will also deepen your knowledge of confounding and effect modification in epidemiologic studies.

Skills you will develop 

• Causal inference
• Study design
• Bias remediation

3 Credits

This course is designed for introductory biostatistical theory and application for students pursuing a master’s degree in fields outside of the Department of Biostatistics, Bioinformatics, and Biomathematics. Students first learn the four pillars of exploring and displaying data appropriately, exploring relationships between two variables, issues of gathering sample data, and understanding randomness and probability. On these pillars, students then can develop the platform for statistical inference including proportions and means, multiple regression, and ANOVA.

3 Credits

This course will deepen your understanding of applied biostatistical theory and its practical application in epidemiology. To take this course, you are expected to have completed EPID 5003 or possess equivalent knowledge. You will explore advanced modeling techniques, including linear models, general linear models, ANOVA and analysis of covariance (ANCOVA), logistic regression, survival analysis and strategies for sample size planning.

Skills you will develop 

• Advanced biostatistical modeling
• Applied epidemiological analysis
• Sample size planning

1 Credit – Lab

This advanced course equips you with hands-on experience in statistical software and computational techniques to confidently apply biostatistical methods in epidemiological research.

Skills you will develop 

• Statistical software proficiency
• Computational methods
• Biostatistical application

1.5 Credits

This course is a comprehensive overview of cancer’s public health impact on populations. Through a blend of engaging lectures and interactive sessions, you will explore the distribution of cancer types across the U.S. and globally, including disparities shaped by gender, race and ethnicity.

You will gain insight into data sources and cutting-edge methods for cancer surveillance, diagnosis, treatment and follow-up care, preparing you to contribute to ongoing public health efforts.

Skills you will develop 

• Cancer epidemiology
• Data analysis
• Cancer surveillance

1.5 Credits

This course introduces you to the foundational principles of infectious disease epidemiology, emphasizing emerging and re-emerging pathogens, including viruses, bacteria and eukaryotic parasites.

You will explore how these infections influence medical care and public health, with a special focus on their role in driving and deepening health disparities both locally and globally.

Skills you will develop 

• Infectious disease epidemiology
• Identifying pathogens
• Understanding health disparities 

1 Credit

This course centers on two key areas:

• Ethics and the responsible conduct of scientific research
• A broad exploration of epidemiology topics through the lens of health equity and disparities

Past sessions have featured talks on issues such as “Stigma: Global Mental Health,” “AI Tools in Research and Ethical Use,” and “Work, Retirement and Aging.”

Skills you will develop 

• Research conduct
• Ethics
• Epidemiology research

1 Credit

This course develops your understanding of what types of quantitative datasets exist in global health, how to access them and how to use them for basic statistical analysis. You’ll learn about dataset structure and how to select variables for analysis of global health questions.

3 Credits

This course provides essential skills to formulate health policy, and to understand, analyze, and evaluate health systems in low- and middle-income countries. Weekly meetings provide a forum for discussing and analyzing many important areas, including governance and performance issues for health systems and health programs.

Public Health Nutrition is the arm of public health that examines the role of nutrition in population and provides answers that lead to health promotion and disease prevention through the development of policies and environmental changes. This course merges concepts of nutrition and epidemiological research with practical application, including dietary assessment methods, food security, social determinants of health, and policies to address chronic diseases and cancer.

Meta-analysis is a statistical tool to combine findings from multiple independent studies. In recent years, it has been increasingly used in many scientific fields. It plays an important role for improving precision of research results and resolving seemingly contradictory research outcomes. This course will introduce meta-analysis methods commonly used in public health and medical research. The course is designed to help students understand the statistical techniques used to conduct quantitative meta-analyses. Students will learn to systematically synthesize evidence from multiple studies, critically assess study heterogeneity and bias, and apply appropriate statistical models for quantitative data pooling. The course covers fixed-effect and random-effects models, forest plots, meta-regression, publication bias, and the use of software tools such as R and SPSS. Emphasis is placed on practical applications and the interpretation of findings.

Students will apply social epidemiologic concepts to addiction, introduced through weekly lectures and readings, and the use of discussions and case studies. This course will prepare students to understand and appreciate the contribution of social factors to addiction etiology, course and the distribution in populations.

This course will examine threats to the U.S. homeland and how these threats are defeated in the context of “homeland security.” The course focuses on homeland security policy and planning considerations at all levels of government (federal, state, and local) and the U.S. private sector. We place emphases on understanding the concept of risk management as well as the role of science and technology in homeland security. We will begin most classes with a review of current events before covering the material for the week. Many classes will also have guest speakers who are experts in their fields.

This graduate seminar is a unique combination of presentations by experts in biomedical sciences, policy, and social science that are united by key topics in global infectious diseases. The purpose of this seminar series is to provide a venue for the discussion of interdisciplinary research and development that acknowledges how the world has become a global system for the propagation of infectious disease.

Particular attention will be paid to the role of community-­level initiatives aimed at educating graduate students to think critically at how a community can prepare for, cope with, and recover from the adverse social, health and community impacts of disasters through the interrelated domains of prevention, preparedness, response and recovery with the end goal of achieving resilience. Emphasis will also be on identifying federal, state, local, private sector and non-­governmental agency plans to enhance community resilience for health security threats and describe options for building community resilience.

This course introduces students to interdisciplinary and graduate studies in the Communication, Culture & Technology program. This class aims at helping students to develop an expertise so they can contribute to an intellectual community. At the same time the course will equip students with an academic and professional problem-solving framework. Students will explore interdisciplinarity in communications, cultural, media, and technology studies by taking the initial steps to identify the communities to which they want to matter, to determine what foundations/ assumptions/ viewpoints exist in said community, and to figure out how to contribute knowledge to the ongoing conversation. Central to these endeavors are keywords like truth, trust, facts, knowledge and power – all concepts that are hard to pin down these days and as such we will explore their scope and how they are interconnected. A core question of this course is then: how do you (or anyone else) know what you know and how can you trust this what you know?

This interactive course focuses on applying knowledge experimental design, biostatistics, and research ethics to trainee specific proposal. We will use, as examples, obesity/metabolic syndrome; age-related neurocognitive impairment; asthma. Students will work in groups to identify a researchable question and study hypothesis, and consider alternative approaches to study design, participant recruitment, and data collection. This is an online course that requires meetings in addition to lecture time. All non-CLTR students must request instructor/dept. approval. The Registration Team will be able to help with the “add/drop”. Section information text: This is an online course that requires meetings in addition to lecture time. All non-CLTR students must request instructor/dept. approval.

This course covers the basics of epidemiology and biostatistics with an emphasis on infectious disease methods (e.g., surveillance, outbreak investigation) and substance (e.g., transmission risks and dynamics) compared to standard epidemiology courses. Covers fundamentals of descriptive epidemiology, surveillance systems, and disease dynamics. Some minimal coverage of research design and analytical epidemiology.

This course will build students’ ability to identify and evaluate evidence related to infectious disease, and to learn to translate evidence into recommendations for policy. Both qualitative and quantitative evidence will be covered. The course will in particular explore how quantitative evidence can drive decision making for infectious disease problems. Students will learn how to evaluate model-based or other quantitative findings for public health policy.

This course is designed as a workshop experience which will meet over two Saturdays. It is designed to allow students to deeply explore an academic topic, problem, issue, or idea of individual interest related to global health. Students will learn and practice the design, plan the implementation of an investigation to address a research question that they will choose. Specific topics will include research methodology, employing ethical research practices, and accessing, analyzing, and synthesizing information. Students will reflect and document their processes, and collect their scholarly work in a portfolio that will contain the research question, literature review, proposed methodology and plan.

Population biology is a quantitative science dealing with changes in the size and composition of populations, and population biologists often use mathematical models to infer population dynamics. These models use information about the properties of individuals and basic assumptions about their interactions to predict population size, gene frequency, and optimal behavioral strategies of individuals, forming an important conceptual framework. Junior and Seniors only. This course shows what kinds of insight mathematical techniques can give to about biological populations of individuals, communities, and cells. My expectation is that all of you have had a good foundation in biology and some mathematics, but you won’t be expected to remember every detail. You will see a good deal of mathematics and biology in this course, and we won’t be assuming a great deal of prior knowledge. However, you will be expected to grasp new knowledge conceptually and demonstrate knowledge through in-class computer lab exercises, homework assignments and projects.

This graduate-level research methods course will train students in a wide range of qualitative and quantitative methodological and analytical approaches necessary for careers in global health and infectious disease policy, research, and practice.

This course uses the principles of economics to study the allocation of resources used to provide health and long-term care. Market inadequacies and market failures that have affected the financing, organization, and delivery of care are examined. The impact of private and public insurance programs on the organization and delivery of health care are analyzed, and the relationships between politics, policies, and health care markets are explored. Basic economics principles are taught and applied to the study of health care.

As value-based models incentive efforts to reduce costs, improve the patient experience, and advance the health of populations, widespread efforts are underway to make real-time data available for analytics – leading to more informed decision-making and resource allocation. To facilitate these efforts, organizations are employing data visualization platforms (e.g. Tableau, Power BI) for operational and population health surveillance. Through a series of big data simulation exercises, this course will allow students to create, interpret, analyze, and critique data visualization methodologies for improved organizational performance and population health advancement.

This course will explore how politics has shared our public-private mix of financing arrangements – with significant consequences for access and costs; how politics in the Congress and the courts together pose significant hurdles to reforming health financing that will assure access to affordable quality care.

This didactic course will provide an overview of the field of Biomedical Informatics from different perspectives. This course will provide an overview of biology and medicine relevant to healthcare from an informatics perspective. This course focuses on utilizing data to solve relevant health and informatic problems that the healthcare system is facing. Emphasis is given to understanding the basic building blocks, various information resources and the application areas of Biomedical Informatics. Students will learn to explore the process of developing and applying computational techniques for determining the information needs of healthcare providers and patients. This class uses lectures, flipped classroom approaches where needed as well as student led discussions. Relevant topics include Electronic Health Records, Patient Quality Assessment and Improvements, Evidence Based Medicine, Natural Language Processing, Consumer and Public Health Informatics.

This course introduces the fundamentals of the molecular genetics and molecular cytogenetics of cancer. In addition, it covers diagnostic, clinical, and population-based aspects of this rapidly advancing field.

Students will apply social epidemiologic concepts to addiction, introduced through weekly lectures and readings, and the use of discussions and case studies. This course will prepare students to understand and appreciate the contribution of social factors to addiction etiology, course and the distribution in populations.

This course will provide a multidisciplinary introduction to emerging and re-emerging infectious diseases that pose a threat to public, animal and environmental health. The course covers a variety of topics (disease emergence drivers, vector-borne diseases, vaccine preventable diseases, impacts of epidemics/pandemics on health systems, international health frameworks and governance) and will aim to be as current as possible, discussing disease events in real time.

This graduate seminar is a unique combination of presentations by experts in biomedical sciences, policy, and social science that are united by key topics in global infectious diseases. The purpose of this seminar series is to provide a venue for the discussion of interdisciplinary research and development that acknowledges how the world has become a global system for the propagation of infectious disease.

Survey Research Methods is a methods course that teaches what surveys are best used for, how to design a questionnaire, how sampling and weighting work, how to analyze survey data, how to critique a survey and its design, and the limitations of and future considerations for survey methodology. Students will draft and critique their own survey questionnaires, learn about survey methodology, and complete an analytical project using survey data and RStudio including some data visualization.

This course builds upon the introductory statistics concepts and skills developed in the first term, extending them to practical application in study and clinical trial design and interpretation. Topics include structural aspects of clinical trials, protocol design, randomization and blinding, issues of error, bias and hypothesis testing, selecting and working with trial outcome variables, issues in safety versus efficacy trials, power and sample size calculations, secondary subgroup and exploratory analysis.

This graduate-level course will train students to navigate the landscape of ethical issues which arise at each step of the data science process, with an eye towards developing policy recommendations for governments and organizations seeking expert advice on how to tackle these issues from a regulatory perspective. Students will explore and critically evaluate a range of data-related issues in contemporary society, such as responsible data collection, algorithmic bias, privacy, transparency, accountability, democratic participation in data usage and data-driven decisions, and the ethical implications of emerging technologies like artificial intelligence and machine learning (self-driving cars, ChatGPT, crowd-sourced training data, etc.).

Time series analytics focuses on trends that occur in data over time. The Time Series class will use R to perform time series analysis for a variety of applications, including financial, econometrics, policy, health, engineering, forecasting, etc. Time series data can be used to better understand temporal forces and to generate predicative models. Often, underlying or latent effects can lead to observable trends. Analytics techniques will include model fitting, statistical methods, visualization, and storytelling.

This course provides an opportunity for students to engage in learning new algorithms and data science methods in measurement that is applied across all research fields. Unlike traditional one-size-fits-all assessments, how to make an adaptive test, survey, scale, or game for individuals that are tailored by their ability, interests, behavior, health status, and learning requirements is the major theme to be explored in this course.

This course covers the basics of epidemiology and biostatistics with an emphasis on infectious disease methods (e.g., surveillance, outbreak investigation) and substance (e.g., transmission risks and dynamics) compared to standard epidemiology courses. Covers fundamentals of descriptive epidemiology, surveillance systems, and disease dynamics. Some minimal coverage of research design and analytical epidemiology.

Engaging Communities for Health introduces students to the core principles, practices, policies, and capabilities that are required to engage communities around all aspects of infectious disease surveillance, control, and response. It moves beyond short-term outbreak dynamics to provide the tools to students to engage in structural, multi-scalar, and social, cultural, economic, and political analysis.

This course introduces the complex field of global environmental health and explores many existing challenges. It also will examine the concept of planetary health and the relevance to public health of current global issues including climate change, the 2030 Agenda for Sustainable Development and its health-related Sustainable Development Goals, and the three Rio Conventions on Biodiversity, Climate Change, and Desertification. Students will also learn about effective relationships with other disciplines and sectors, including inter-sectoral approaches in public health.

A core set of research methods courses that equip students with foundational research skills, including qualitative methods, the application of frameworks and theories of change relevant for monitoring and evaluation of health programs, and broader conceptual skills in problem definition, choice of research question, primary data collection, and research ethics.

This course uses the principles of economics to study the allocation of resources used to provide health and long-term care. Market inadequacies and market failures that have affected the financing, organization, and delivery of care are examined. The impact of private and public insurance programs on the organization and delivery of health care are analyzed, and the relationships between politics, policies, and health care markets are explored. Basic economics principles are taught and applied to the study of health care.

As value-based models incentive efforts to reduce costs, improve the patient experience, and advance the health of populations, widespread efforts are underway to make real-time data available for analytics – leading to more informed decision-making and resource allocation. To facilitate these efforts, organizations are employing data visualization platforms (e.g. Tableau, Power BI) for operational and population health surveillance. Through a series of big data simulation exercises, this course will allow students to create, interpret, analyze, and critique data visualization methodologies for improved organizational performance and population health advancement.

A course designed to explore the varied ways pathogenic bacteria overcome natural host defense, to describe host responses to infection, and to discuss the network of interactions between pathogen and man at the molecular and cellular level.

This course will engage students with the design, collection, and evaluation of the methodological approaches we commonly think of as “qualitative,” emphasizing interview-based research, ethnography, and comparative research. As we learn to use qualitative methods, we will explore a range of important topics in the world today including political polarization, racial and ethnic identity, immigrant experiences, sexual harassment, extreme poverty, homelessness, employment discrimination, natural disasters, and eviction.

Cancer epidemiology, prevention and control relies on the conduct of basic science research and applied research in the behavioral, social, and population sciences to create or enhance interventions that, independently or in combination with biomedical approaches, reduce cancer risk, incidence, morbidity and mortality, and improve quality of life. The objectives of this course are to equip students with the understanding of cancer problems from cell to society and to provide them with the evidence of the need of cross-disciplinary collaboration between biomedical and behavioral sciences.

Lectures in Clinical & Translational Oncology

Clinically based course wherein students are provided directed reading on current literature encompassing brain tumor pathology, tumor biology, neuro-genetics, survivorship, and targeted therapy. Discussions with clinical faculty, eg. Oncologists, Pathologist, Radiation Medicine professionals and researchers based upon the assigned topics assist the students in better understanding the status of Brain Tumor Medicine.

This course addresses the biological basis for the observed unequal burdens of cancer across racial/ethnic populations. The impact of genetic/genomic/epigenetic variability between groups that may affect cancer susceptibility and/or response to therapy which is vital to reducing the cancer gaps will be explored. The course will also explore evidence-based mechanisms that are designed to increase our understanding of biological factors and mechanisms that play a role in cancer health disparities.