George Mason University
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George Mason University

Introducing the 2019-2020 Dean's Seminar Series

Join Dean Louis for the inaugural Dean's Seminar Series.

Please join Dean Germaine Louis for the inaugural College of Health and Human Services Dean’s Seminar Series, made possible through the generous contributions of an anonymous donor.

Note that the remaining Dean’s Seminar Series events will take place virtually from 12:00 p.m. to 1:00 p.m. All presentations will be archived on this page.

September 29, 2020
12pm ET - Log in details to be provided

Jon Samet, M.D., M.S.
Professor and Dean
Colorado School of Public Health
University of Colorado, Colorado State University & University of Northern Colorado

Title:  Risky Breathing and Policy:  Lessons Learned from Smoking and Air Pollution

RSVP here

This presentation addresses the translation of public health policy into action through regulatory and non-regulatory paths.  It draws on the lengthy stories of tobacco control and air quality management and how mounting scientific evidence supported regulatory and non-regulatory control measures.  Emphasis is given to the roles of public health researchers in affecting evidence-based change.

October 27, 2020
12pm ET - Log in details to be provided


Coleen Boyle, Ph.D., MSHyg
Adjunct Professor, Center for Leadership in Disability, Georgia State University, School of Public Health & Former Director, National Center on Birth Defects and Developmental Disabilities,
Centers for Disease Control and Prevention

Title: How the Zika Virus Response Improved our Public Health Approach to Protecting Mothers and Infants

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In late 2015, alarming reports from northeast Brazil suggested that many babies were being born with very small and unusually shaped heads. This was followed by a flurry of global public health and research activities to determine whether the reports were real, and if so, what was the cause. Over the ensuing months, it became increasingly clear that a new infectious cause of a birth defect had emerged in the Americas—Zika virus. This was the first time that the bite of a mosquito was found to transmit a virus that caused birth defects in the developing baby.  In responding, CDC, state, and local public health stood up a real-time surveillance system to piece together the Zika story and to protect pregnant women and their babies from the virus as it made its way across the Americas. The system developed for Zika is now being leveraged to address other serious threats to mothers and infants. The seminar will describe how the Zika outbreak unfolded, how the science and surveillance were rapidly developed to answer all the frightening unknowns, and how this response became the lynchpin for a system of readiness to address and respond to other infectious and noninfectious threats to mothers and infants. 


Past Dean's Seminar Speakers

Data Science for a Learning Healthcare System of Systems

Monday, November 11, 2019
Scott Zeger, Ph.D., M.S.
John C. Malone Professor of Biostatistics and Medicine
and former Chair Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health

This talk addresses a data science framework that is essential infrastructure for a learning healthcare system of systems.  We frame core health-system questions in statistical terms, then offer a Bayesian hierarchical modeling approach that integrates complex data with prior biomedical knowledge to empirically address the questions.  We discuss the importance of both discovery and delivery to improve health outcomes at more affordable costs.  Our approach is being implemented in the Johns Hopkins Precision Medicine program called Hopkins inHealth.  Recent progress from a few of JHM’s 30 inHealth Centers of Excellence is used to illustrate the methods and current obstacles.  The talk identifies opportunities for data scientists to directly impact healthcare decisions by translating their models into practice for use locally and in multi-institutional information networks of the future. View a recording of Dr. Zeger's seminar.

The Rapid Decline in Adolescent Mental Health in the 21st Century:  Magnitude, Causes, and Public Health Implications


Monday, January 27, 2020
Kerry Keyes, Ph.D., M.P.H.
Associate Professor
Department of Epidemiology & Co-Director, Psychiatric Epidemiology Training Program
Mailman School of Public Health
Columbia University

Recorded suicide among adolescent girls has tripled in the past decade, and suicide among adolescent boys had doubled. These increases underlie concomitant increases in hospitalized suicide attempts. Additionally, increases in three independent, national-representative survey data sources of US adolescents have documented unprecedented increases in suicidal thoughts and reported attempts, major depressive episodes, depressive symptoms, loneliness, and low self-esteem, with all increases occurring since 2012.  Across these data sources, increases are faster among girls than boys. The consistency of findings across data sources, outcomes, self-report and administrative records, indicates that these increases are likely not due to methodological artifact, requiring strong epidemiological studies that elucidate causes of the increases, reasons for gender differences, and identification of groups within gender that are at higher risk. Existing evidence has tested the hypothesis that use of digital technology underlies these increases, but to date the strongest evidence suggests a limited and nuanced role of new technologies in predicting depression and self-harm. Additional research has pointed to broader sociological trends in the experience of adolescence within a fractured political and precarious economic environment, indicating that research progress that is cross-disciplinary and engages a broad range of scholars will propel recommendations for intervention and prevention forward. View a recording of Dr. Keyes' Seminar. Read the news story summary. 

Integrated Nutrition Approach to Improving Personal, Population, and Planetary Health

Febraury 17, 2020
Frank Hu, M.D., Ph.D., M.P.H.
Fredrick J. Stare Professor of Nutrition and Epidemiology
Chair, Department of Nutrition, Director of Boston Nutrition Obesity Research Center Epidemiology & Genetic Core
Co-Director, Program in Obesity Epidemiology and Prevention
Harvard T.H. Chan School of Public Health

The global chronic disease burden and the food production system’s enormous environmental impact are two pressing threats to personal, population and planetary health. Fortunately, dietary modifications can alleviate both of these threats. Healthful plant-based dietary patterns have been associated with lower risks of coronary heart disease and type 2 diabetes. Precision nutrition can provide insight into the mechanisms behind these associations by assessing individual characteristics such as the metabolome, genome and microbiome. While precision nutrition has future potential to provide personalized diets for disease prevention, the field is still developing and thus must be balanced with public health nutrition strategies. In addition to their health benefits, plant-based diets have less environmental impact than animal-based diets. Producing animal products, especially meat, is more energy-intensive than producing plant products. Shifting global dietary patterns towards diets higher in plant-based foods and lower in meat would likely have significant personal, population and planetary health benefits. 



Monday, March 2, 2020
F. DuBois Bowman, Ph.D., M.S.
Professor and Dean
School of Public Health
University of Michigan

Title: Precision Discovery of Neuroimaging Biomarkers for Parkinson’s Disease

Parkinson's disease (PD) is a complex neurodegenerative disorder that manifests through hallmark motor symptoms, often accompanied by a range of non-motor symptoms.  There is a putative delay between the onset of the neurodegenerative process, marked by the death of dopamine-producing cells, and the onset of motor symptoms, creating an urgent need to develop biomarkers that may yield early PD detection. Neuroimaging offers a non-invasive approach to examine the utility of a vast number of functional and structural brain characteristics as biomarkers.  We present a statistical framework for analyzing neuroimaging data from multiple modalities to determine features that reliably distinguish PD patients from healthy control subjects. This pursuit involves precision discovery from ultra-high dimensional data.  Our approach builds on the statistical learning procedure elastic net, performing regularization and variable selection, while introducing additional criteria centering on parsimony and reproducibility.  We apply our methods to data from two studies of PD.  We demonstrate high accuracy, assessed via cross-validation, and identify brain regions in the basal ganglia and outer cortex that are implicated in the neurodegenerative PD process.

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