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The Department sponsors a biweekly seminar series during the academic year on topics of epidemiologic interest. Speakers include Michigan State University faculty, Michigan Department of Community Health public health professionals or invited guests from around the nation or, occasionally, overseas.

The seminar is open to all members of the MSU and public health community, and unless otherwise noted, takes place at 3:30 p.m. in C102 East Fee Hall (Patenge Room) or E4 Fee Hall (Fee Hall basement)  Most seminars are recorded and available for viewing by accessing the speaker name below.

E-4 Fee Hall is located in the center of the basement level of Fee Hall, next to the Take 5 Snack Shop & Medical Bookstore.

The Patenge Room, C102, is located in the C wing of East Fee Hall.


Karl Alcover
Polydrug Cannabis Use and Cannabis Dependence: A ‘Latent Class with Distal Outcome’ Approach

Omayma Alshaarawy
Cannabis use and changes in body weight studied prospectively: New estimates for the United States

Samantha Bauer
Male-Female Differences in Heroin Incidence

Madhur Chandra
Assessing differential risks of cocaine dependence problems based on cocaine onset lag-times

Villisha Gregoire
Does Cannabis Onset Now Trigger Onset of Drinking Alcohol? An Epidemiologic Case-Crossover Approach

Alyssa Vanderziel
Does a major depression precursor state influence adolescent onset heroin use? Epidemiologic case-control evidence


Rita Strakovsky, PhD | View Seminar
Assistant Professor,
Department of Food Science and Human Nutrition
Michigan State University

"Gestational estrogen status, maternal adiposity, and exposure to endocrine disrupting chemicals"

Maintaining appropriate levels of estrogens is critical for both pregnancy outcomes and fetal development. Today’s presentation focuses on two potential disruptors of gestational estrogen status: 1) maternal obesity and 2) exposure to endocrine disrupting chemicals. Maternal obesity or adiposity are known risk factors in pregnancy, and in the non-pregnant state, estrogens differ in obese vs. normal-weight women. However, little is known about this relationship in pregnancy. While studies in animals and humans have investigated the impact of endocrine disruptors (including bisphenol A (BPA) and phthalates) on several sex steroid hormone-mediated outcomes, it is less clear whether these associations can also be observed in pregnant women. These outcomes are being investigated in the Illinois Kids Development Study (I-KIDS), an ongoing prospective cohort study being conducted as part of the Children’s Environmental Health Center and ECHO Center at the University of Illinois.


Kimberly McKee, PhD, MPH | View Seminar
Research Investigator,
Obstetrics and Gynecology,
Medical School
University of Michigan

"The Vaginal Microbiome in Pregnancy and Beyond:
What do we know and where are we going? "

Recent advances in culture-independent techniques have made the study of human microbiota feasible for population-based research. I will provide an overview of analysis methods , including 16S rRNA gene sequencing, and some basic metrics used to operationalize microbiota data followed by what is known about the vaginal microbiome, including associations with clinical factors and outcomes such as preterm birth, and some examples from our own work.


Hwan Chung, PhD | View Seminar
Professor, Department of Statistics
Korea University

"Latent class models for multiple discrete latent variables"

This presentation introduces various latent class models such as latent class profile analysis (LCPA) and joint latent class analysis (JLCA), which will provide a set of principles for systematic identification of the subsets of sequential or joint patterns of the two or more discrete latent variables. We are motivated to develop a generalized latent class type model in order to deal with various research questions on behavioral studies. LCPA is proposed to identify latent clusters or paths of latent classes using sets of repeatedly measured manifest items. JLCA, another type of latent class model, can identify the joint behavioral patterns of multiple latent variables. In this work, we provide applications of these models: in an investigation of stage sequential patterns of drinking behaviors among early onset drinkers (LCPA), and in an investigation of the association of violent behavior and the simultaneous use of multiple drug compounds, including alcohol, tobacco, and cannabis as the most frequently occurring examples (JLCA).


Maureen Durkin, PhD, DrPH | View Seminar
Chair, Population Health Sciences and Pediatrics
Waisman Center Investigator
University of Wisconsin   


"Socioeconomic status and the prevalence of neurodevelopmental disabilities: causal directions and public health implications."

Socioeconomic status (SES) is both an important risk factor and a determinant of health outcomes and quality of life for individuals with neurodevelopmental disabilities. This talk will consider epidemiologic evidence of the relationships between SES and selected disabilities, including cerebral palsy, autism spectrum disorder, and intellectual disability. Public health implications of disparities in the prevalence and long-term impacts of SES on functioning in persons with disabilities will also be discussed.

2.  RAIND Seminar Feb 23, 2018 12-1:30 PM
Erickson kiva (620 Farm Lane, Erickson Hall, Rm 103).

"Trends in the epidemiology of autism spectrum disorder in the United States."

Since the first epidemiologic study of autism in the U.S. was published in 1970, data from multiple sources have shown steady increases in the prevalence of autism. This talk will describe and discuss trends over time, risk factors, and public health implications of the rising prevalence of autism spectrum disorder.


Jiayu Zhou, PhD | View Seminar
Assistant Professor, Computer Science and Engineering
Michigan State University

"Multi-task Learning and its Applications to Biomedical Informatics"

The recent decade has witnessed a surging demand in data analysis, where we built machine learning models for various data analysis tasks. The multi-task learning is a machine learning paradigm that bridges related learning tasks and transfers knowledge among the tasks. Multi-task learning is currently widely used in computational medicine such as predictive modeling from electronic medical records, modeling disease progression and drug effect prediction. In the seminar, we first introduce the basics of multi-task learning. We then show how multi-task learning can benefit the study of the progression of Alzheimer’s disease. We also introduce a distributed framework for multi-task learning that allows privacy-preserving computation over distributed patient cohorts. The seminar is concluded by a discussion of future directions of multi-task learning.

MARCH 22ND | E109 3:30 P.M. (Jointly sponsored by The Department of Economics)

Anne Case, PhD
Professor of Economics and Public Affairs, Emeritus
Princeton University

"Changing Patterns in US Morbidity and Mortality"

We build on and extend the findings in Case and Deaton (2015, 2017) on increases in mortality and morbidity among white non-Hispanic Americans in midlife since the turn of the century. Increases in all-cause mortality have continued through 2016, with additional increases in drug overdoses, suicides, and alcohol-related liver mortality, particularly among those without a bachelor’s degree. The decline in mortality from heart disease slowed and most recently stopped for whites with less education. This, combined with the three other causes, is responsible for the increase in all-cause mortality. Mortality rates in comparable rich countries have continued their pre-millennial fall at the rates that used to characterize the US. In contrast to the US, mortality rates in Europe are falling for those with low levels of educational attainment, and have fallen further over this period than mortality rates for those with higher levels of education. We find that contemporaneous economic circumstances, such as unemployment and slowly growing or stagnant incomes for those with less education, cannot explain the mortality changes we observe. We propose a preliminary but plausible story in which cumulative disadvantage from one birth cohort to the next, in the labor market, in marriage and childbearing, and in morbidity and mortality, is triggered by progressively worsening labor market opportunities at the time of entry for whites with low levels of education. This account suggests that those in midlife now are likely to do much worse in old age than those currently older than 65. This is in contrast to an account in which resources affect health contemporaneously, so that those in midlife now can expect to do better in old age as they receive Social Security and Medicare. None of this implies that there are no policy levers to be pulled; preventing the over-prescription of opioids is an obvious target that would clearly be helpful.

This talk is presented in conjunction with the Dunaway lecture seminar, presented by Angus Deaton.

Professor Sir Angus Deaton
Dwight D Eisenhower Professor of Economics and International Affairs
Emeritus, Princeton University
Recipient of the 2015 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel

"Why is global (and American) poverty so hard to measure and to eradicate?"

Thursday, March 22, 2018 at 6:00 p.m.
103 (the Kiva) Erickson Hall, MSU

The elimination of global poverty by 2030 is one of the Sustainable Development Goals, and has been accepted as a goal by the World Bank and by the United States. Yet the measurement of global poverty poses many difficulties, especially now that the SDGs include poverty in rich countries as well as poor countries. The lecture will give a non-technical discussion of some of these issues, including the vexed issue of whether there are people living in the US who are as poor as the poorest in Africa or in India. It also discusses the puzzle of why global poverty exists at all, given that cost of bringing every person in the world up to the global poverty line amounts to less than the cost of a cup of coffee for everyone in the rich world. It argues that “finding out what works” in poverty relief is unlikely to help, and that the problems of global poverty are to do with politics and power, or at least the lack of it.


David Kent, MD, CM, MS | View Seminar

Professor of Medicine, Neurology and Clinical and Translational Science
Tufts Medical Center

"Special Topics in Predictive Analytics and Comparative Effectiveness in Medicine"

Dr. Kent builds on the concepts of heterogeneity of treatment effect by examining special issues that arise when developing models to predict treatment benefit. Dr. Kent will discuss the conceptual underpinnings of the development of the Risk of Paradoxical Embolism (RoPE) Score, which models the attributable fraction of paradoxical embolism in patients with cryptogenic stroke and patent foramen ovale (PFO). He will also discuss special problems that arise when we incorporate personalized estimates of treatment effect into cost effectiveness analysis based on a recent analysis of the National Lung Cancer Screening Trial (NLST).

Miss a seminar or would like to revisit one you attended?  Most seminars are available to view online.    SEMINAR ARCHIVES