Webinar featuring a dynamic plenary between two leading epidemiologists. The fall event features live oral presentations selected from submitted abstracts. Participants are encouraged to participate individually or organize a viewing party at their institution.

UPCOMING EVENTS

"Missing Data in Epidemiologic Research: Contemporary Approaches for Enduring Problems" March 8, 2023, 12:00pm -2:00pm EST

According to the U.S., Food and Drug Administration, Real-world evidence refers to the clinical evidence about the usage and potential benefits or risks of a medical products derived from analysis of real-world data, whereas real-world data is data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources such as electronic health records, medical claims data and data from product or disease registries. The use of real-world data is a growing area in epidemiologic research, providing an unprecedented opportunity to analyze health outcomes, disease patterns, and interventions based on real-life experiences. This session will provide a comprehensive understanding of how real-world data is collected, analyzed, and leveraged to derive valuable insights for improving population health.

PAST EVENTS

"Missing Data in Epidemiologic Research: Contemporary Approaches for Enduring Problems" March 8, 2023, 12:00pm -2:00pm EST

Handling missing data is a common challenge in epidemiology that can affect the validity of research findings. Epidemiologists are trained in various methods for addressing missing data, such as multiple imputation and inverse probability weighting. However, as statistical and epidemiological techniques continue to evolve, it is important to also consider newer and cutting-edge methods for addressing this persistent problem. During this session, we will explore new methods and current considerations for dealing with missing data. The session will provide an opportunity to understand the benefits and drawbacks of different strategies and help you decide which methods are best suited for your research.

Recording

Charlie Rioux PHD (She/Her)

Assistant professor, Department of Psychology, University of Oklahoma

BIO

Dr. Rioux is an assistant professor of developmental and quantitative psychology at the University of Oklahoma (OU). She is also an affiliated member of the Health Promotion Research Center, the Institute for Community and Society Transformation, and the Data Institute for Societal Challenges at OU. Dr. Rioux completed her Ph.D. in Psychology in 2018 at the University of Montreal. She completed a 3-year postdoctoral fellowship in quantitative methods at Texas Tech University and a 1-year postdoctoral fellowship in clinical and developmental psychology at the University of Manitoba and the University of Calgary. Her research was funded by the Canadian Institutes of Health Research, the Quebec Health Research Fund, and Research Manitoba.

Dr. Rioux’s research examines social and individual determinants of mental health from the prenatal period to adulthood. Her research in methodology aims to contribute to the accessibility of state-of-the-art research methods, including longitudinal and missing data methods.

Twitter
@Charlie_Rioux

Neil J. Perkins, PHD (He/Him)

Acting Branch Chief and Staff Scientist, Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research

BIO

Bio

Neil J. Perkins, Ph.D., became the acting chief of NICHD’s Biostatistics and Bioinformatics Branch in 2022. He joined the branch as a biostatistician staff scientist in 2020. His research interests focus on biomarker challenges including assessing and accounting for measurement error, missing data methods, and diagnostic assessment. A member of NICHD since 2008, Dr. Perkins has worked on several Division of Intramural Population Health Research studies, publishing numerous papers on etiologic and methodologic research. He is the recipient of several NIH and NICHD merit awards. Dr. Perkins earned his Ph.D. from American University.

November 9, 2022
12PM – 2PM EDT

“The Promise and Perils of Machine Learning Approaches in Epidemiologic Research”

Machine Learning (ML) is a rapidly growing subfield of artificial intelligence with an already extensive application in health and healthcare research. However, ML is not widely adapted in epidemiologic research, partly owing to its low emphasis on traditional epidemiologic thinking built on causal inference. Yet, ML has potential advantages that could tackle common issues in epidemiologic research, such as measurement error and missing data. The session will focus on the promise and perils of ML in epidemiology and advancements in the field over the past few years and how we can best adapt and harmonize ML approaches in epidemiologic research.

Recording

Jean Feng, PhD

Assistant Professor of Epidemiology and Biostatistics
University of California, San Francisco

Twitter: @Jean_J_Feng

Jack Wilkinson

Lecturer in Biostatistics, Centre for Biostatistics, University of Manchester
(he/him)

Twitter: @jd_wilko

Yiyang Mei

BIO

Yiyang Mei is a third-year law student at Emory University where she is pursuing a JD and MPH focusing on epidemiology. She’s interested in exploring environmental and structural effects on public health issues. She also served as a research fellow for the Georgia Department of Public Health, where she worked on opioid and substance-abuse issues. Yiyang received her undergraduate degree from St. John’s College in Annapolis, Maryland.

Jennifer Dunne

BIO

Jennifer Dunne is a PhD candidate at the School of Population Health at Curtin University in Australia. She holds science degrees in health promotion, information systems and public health (honours). Her PhD research is focused on the application of simulation to quantify the bias in perinatal epidemiology. Her broader interests include the application of causal methods in reproductive and perinatal epidemiology, working with big data and population data linkage.

Emma Casey

BIO

Emma Casey is a Data Analyst at the Rollins School of Public Health for the Pregnancy and Childhood Epigenetics Consortium (PACE) and a second year MSPH student focusing on Epidemiology. Her work combines the intersection of environmental health and genetic epidemiology, health disparities, and Alzheimer’s disease research. She is currently working with Dr. Anke Huels to complete her thesis research which encompasses the effects of ambient/traffic-related fine particulate matter on cerebrospinal fluid biomarkers of Alzheimer’s Disease and evaluates potential effect modification by the APOE-ε4 allele. Her research interests involve the integration of omics data in epidemiological studies for a more accurate risk assessment and improved understanding of complex diseases.

March 16, 2022
12PM – 2PM EDT

“Health disparities research in epidemiology: present and future directions “

Partly inspired by the ongoing COVID-19 pandemic and racial justice movements, the past few years have seen health disparities research come to the forefront of public health research like never before. Likewise, current epidemiologic research is ever-increasingly geared towards disparities research across various research areas. In this panel, we will discuss current trends and shortcomings of health disparities, the future of health disparities research, and how early career epidemiologists can model responsible engagement in health disparities research.

Recording

Ana Diez Roux, MD, PhD, MPH
(She/her/hers)
Dana and David Dornsife Dean and Distinguish Professor of Epidemiology
Drexel University School of Public Health

Twitter: @adiezroux

BIO

Dr. Ana Diez Roux is Distinguished University Professor of Epidemiology and Dana and David Dornsife Dean at Drexel University Dornsife School of Public Health. She earned an MD at the University of Buenos Aires and a Ph.D. and MPH at The Johns Hopkins University School of Hygiene and Public Health. Originally trained as a pediatrician, Dr. Diez Roux is an epidemiologist internationally known for her research on the social determinants of population health and the study of how neighborhood built and social environments affect health. Her work on neighborhood health effects has been highly influential in the policy debate on population health and its determinants. Her research areas include social epidemiology and health disparities, environmental health effects, urban health, psychosocial factors, cardiovascular disease epidemiology, social environment-gene interactions, and the use of multilevel methods and complex systems approach in population health. She has received the Wade Hampton Frost Award for her contributions to public health from the American Public Health Association, the Award for Outstanding Contributions to Epidemiology from the American College of Epidemiology, and the Rothman Award from the Society for Epidemiologic Research. She is an elected member of the American Epidemiological Society and the Academy of Behavioral Medicine Research. She was elected to the National Academy of Medicine of the National Academy of Sciences in 2009. Dr. Diez Roux has been an active mentor of junior faculty and trainees from groups underrepresented in health research.

Mya L. Roberson, MSPH, PhD
(She/her/hers)
Assistant Professor, Department of Health Policy, Vanderbilt University
School of Medicine

Twitter: @MyaLRoberson

BIO

Mya Roberson is an Assistant Professor in the Department of Health Policy at the Vanderbilt University School of Medicine. Her broad research interests are in applying epidemiologic methods to health policy and health services research to promote health equity using big data. She is specifically interested in equity in cancer care delivery for Black people in the US South. Dr. Roberson has experience working in cancer registries, claims data, national healthcare databases, and electronic health records, along with expertise in health disparities, health equity, and social epidemiology theory. Dr. Roberson earned her MSPH and Ph.D. degrees in the field of epidemiology from the University of North Carolina at Chapel Hill Gillings School of Global Public Health. While at UNC she was a Truman Scholar and Robert Wood Johnson Foundation Health Policy Research Scholar.

November 10, 2021
12PM – 2PM EDT

“Infodemic Inoculation – Lessons Learned and Future Directions”

As online news and social media sites flood us with content, epidemiologists must become effective scientific communicators. The current “infodemic”, brought on by the increasing availability of misleading information related to COVID-19, reflects the public health importance of vetting news for accuracy. Many health experts have already made use of online platforms to combat the viral spread of misinformation. Panelists will present their success stories in countering current and future infodemics.

Recording

Thu T. Nguyen, ScD, MSPH (she/hers/her)
Associate Professor
Department of Epidemiology and Biostatistics
Maryland School of Public Health

BIO

Thu Nguyen, ScD, MSPH is an Assistant Professor in the Department of Family and Community Medicine at University of California, San Francisco (UCSF). She is a social epidemiologist whose research focuses on the impact of modifiable social factors on minority health and health disparities. A primarily line of focus of her research is investigating the influence of racism and discrimination in creating and perpetuating health equities. Dr. Nguyen uses a variety of different data sources (including Big Data) and approaches (including quantitative and qualitative research methods) to advance our understanding of social determinants of health. Dr. Nguyen received her BA in Human Biology from Stanford University, her MSPH in Epidemiology from UNC Gillings School of Global Public Health, and her ScD in Social Epidemiology from the Harvard T.H. Chan School of Public Health.

Sandra Albrecht, PhD, MPH (she/her/hers)
Assistant Professor
Department of Epidemiology
Mailman School of Public Health at Columbia University

BIO

Dr. Albrecht is formally trained as a social epidemiologist, with additional training in the social sciences, nutrition, and in both chronic and infectious diseases. Her research focuses on the social determinants of nutrition-related diseases in immigrants and other marginalized populations with an emphasis on improving access to quality care, and to affordable, healthy food. Dr. Albrecht has also been engaged in scientific communication efforts to help individuals, communities and policy-makers make evidence-based decisions around health. To this end, she has been serving as Chief Epidemiologist for Dear Pandemic, a social media-based, multi-disciplinary COVID-19 science communication project aimed at tackling the “infodemic” of misinformation that has helped to cripple the response to the pandemic. She is also the Editor-in-Chief of the parallel Spanish language effort, Querida Pandemia.
@S_AlbrechtPerez

Live Student Presentations

Erin Campbell
“Associations among historical neighborhood disinvestment, hazardous air pollution, and current adult asthma prevalence”

BIO

Erin J. Campbell is a Research Analyst at Resources for the Future, and she is a recent graduate of the University of Rochester. She graduated in May 2021 with a BA in Economics and a BS in Environmental Health. Her work combines theory and methods from economics with public health. Erin’s research interests lie at the intersection of health and environmental justice, with a key focus on how policies, even historical, can create lasting impacts on population health.

Navdep Kaur
“Trends in Racial and Ethnic Disparities in Adult Mental Health Treatment: Results from the 2005-2019 National Survey on Drug Use and Health”

BIO

Navdep Kaur, MPH, is a second-year Ph.D. student in Epidemiology at Columbia University. She is currently receiving training in the Psychiatric Epidemiology Training (PET) Program under the guidance of Dr. Katherine M. Keyes and Dr. Sharon Schwartz. Her research focuses on social epidemiology with particular attention to racial/ethnic disparities of psychiatric disorders and mental healthcare. More broadly, she is interested in the development of epidemiologic theory to study drivers of social determinants of mental health.

Katharine McCarthy
“Assessing the potential for differential disease misclassification in survival analysis: Applying probabilistic bias analysis”

BIO

Katharine McCarthy, PhD, MPH. Dr. McCarthy is a Postdoctoral Research Fellow with the Blavatnik Women’s Health Research Institute and the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. Dr. McCarthy is a perinatal epidemiologist with expertise in the construction and analysis of complex longitudinal datasets. Her research interests include the intersection of social and structural risks in adolescence as predictors of future reproductive health and the measurement of quality maternal and newborn care. Dr. McCarthy received her PhD in Epidemiology from the CUNY Graduate School of Public Health & Health Policy and her MPH from the Mailman School of Public Health at Columbia University.