Register for the 2020 Advanced Methods Workshop
November 10, 2020 – 12pm-1pm EDT
“Semi-competing risks: Accounting for death as a competing risk in public health research when the the outcome of interest is non-terminal.”
The workshop will provide an overview of semi-competing risks data analysis. Briefly, semi-competing risks corresponds to the setting where primary interest lies in some non-terminal event, the occurrence of which is subject to a terminal event. Although not as well-known as standard competing risks, semi-competing risks arise in any study of any event that is not mortality but where the force of mortality is strong. Read more
Sebastien Haneuse, PhD
Assistant Professor of Biostatistics
Harvard T.H. Chan School of Public Health
Harvard T.H. Chan School of Public Health
Infectious Diseases and Pregnancy: old and new
November 17, 2020 – 1pm-2pm EDT
Catherine L. Haggerty, MPH, PhD
Associate Professor, Graduate School of Public Health, University of Pittsburgh
Brandie DePaoli Taylor, MPH, PhD
Associate Professor, College of Public Health, Temple University
Deshayne Fell, PhD
School of Epidemiology and Public Health
University of Ottawa Scientist
CHEO Research Institute
Ashley V. Hill, MPH, DrPH
Division of Adolescent and Young Adult Health
UPMC Children’s Hospital of Pittsburgh
Annette Regan, PhD
School of Nursing and Health Professionals
University of San Francisco
Pregnancy-induced physiological changes can make pregnant women more susceptible to severe complications due to infections compared to non-pregnant populations. Furthermore, infections disrupt the receptive immunological state at the maternal-fetal interface. For example, viral infections can prime innate immune receptors leading to an excessive influx of pro-inflammatory cytokines in response to pathogenic and non-pathogenic bacteria in the genital tract. Indeed, common bacterial and viral infections have been implicated in infertility, pregnancy loss, preterm birth and preeclampsia. However, prevention efforts have not substantially reduced infection-related complications, suggesting that renewed focus on infections during pregnancy is needed. Given the rise of sexually transmitted infections and global risk of viral infectious diseases, this webinar will prompt discussion on strategies to gain insight into the multifaceted relationship between infection and pregnancy health. Dr. Ashley Hill will first discuss the frameworks that address social risk factors for sexually transmitted infections in the perinatal period. Dr. Annette Regan will provide an overview of the 2009 influenza A/H1N1 pandemic, its implications for perinatal health, and impact on immunization programs targeting pregnant women. Lastly, Dr. Deshayne Fell will summarize key findings from descriptive and epidemiologic studies of SARS-CoV-2 infection during pregnancy, with a focus on perinatal outcomes and maternal-fetal transmission. The webinar will be moderated by Dr. Catherine Haggerty and Dr. Brandie DePaoli Taylor. Following speaker presentations the audience will be invited to discuss strategies to better incorporate infection data into epidemiologic investigations of pregnant women.
November 18, 2020 – 12pm-1pm EDT
Jonathan M Snowden
School of Public Health, Oregon Health & Science University/Portland State University
Department of Obstetrics & Gynecology, Oregon Health & Science University
Sarah Osmundson, MD MS
Vanderbilt University Medical Center
Cesarean Delivery Rates and Costs of Childbirth in a State Medicaid Program After Implementation of a Blended Payment Policy
December 1, 2020 – 12pm-1pm EDT
Stay tuned for more information!
September 10, 2020 – 12pm-1pm EDT
“Improving health communication: now, more than ever before”
Lee Badgett, PhD
Department of Economics
University of Massachusetts at Amherst
Author of The Public Professor: How to Use Your Research to Change the World
Julia Marcus, PhD MPH
Department of Population Medicine
Harvard Medical School
Asst. Managing Editor for Business
Health and Built Environment
The Philadelphia Inquirer
The evolving COVID-19 pandemic and its accompanied unique vulnerabilities for mothers and children presents an opportunity to reexamine the important issue of health communication. How should we, as epidemiologists, better communicate our science to a mosaic of audience types? As stakeholders in pediatric and perinatal health, what are the important issues to be aware of and how can we improve the feedback loop of health communication. Our panel of speakers will explore these issues and present their personal experiences in health communication.
May 12, 2020 – 12pm EDT
Online Journal Club
#SPER_ONLINE presents: “Father matters: Paternal effects on reproductive, perinatal, and pediatric outcomes”
Dr. Jens Peter Bonde, Professor
Department of Occupational and Environmental Medicine, University of Aarhus, Denmark
Dr. Sunni Mumford, Earl Stadtman Investigator, Eunice Kennedy Shriver National Institute of Child Health and Human Development, United States
Dr. Bola Grace, Research Fellow
Institute for Women’s Health, Faculty of Population Health Sciences, University College London, London, United Kingdom
Dr. Lauren Wise, Professor,
Department of Epidemiology, Boston University, United States
Please join us for a one-hour SPER webinar entitled “Father matters: Paternal influences on reproductive, perinatal, and pediatric outcomes.” The webinar will feature three expert panelists who will summarize the scientific evidence on the extent to which paternal exposures affect reproductive and offspring health outcomes. The panelists will also discuss ideas for increasing male engagement and participation in epidemiologic studies on reproductive health. Specifically, Dr. Jens Peter Bonde will present on “Paternal environmental exposure and offspring health,” Dr. Sunni Mumford will speak on “Paternal exposures and reproductive outcomes,” and Dr. Bola Grace will speak on “Male participation in reproductive health research: how can we better engage men in our studies?” The webinar will be moderated by Dr. Lauren Wise. Each speaker will present for about 12-15 minutes, and the final 15-20 minutes will be devoted to discussing challenges and controversies in the field, including recommendations for future research.
April 15, 2020 – 12pm EDT
Online Journal Club
“Estimating the obstetric co‐morbidity burden using administrative data: The impact of the pregnancy‐related assessment window”
This event is co-sponsored by the Society for Epidemiologic research.
February 25, 2020 – 12pm EDT
A Tweet is worth a thousand words: using Twitter for epidemiologic research, a joint webinar from two research groups
Part 1: Twitter-derived measures of sentiment towards minorities and birth outcomes.
Quynh Nguyen, PhD, MSPH is an Assistant Professor of Epidemiology and Biostatistics at the University of Maryland School of Public Health. Twitter handle: @quynhcnguyen
Interpersonal and structural racial bias are leading explanations for the continuing racial disparities in birth outcomes but research to confirm the role of racism has been hampered by challenges in both measuring racial bias and evaluating its impact. We use Twitter data to characterize area-level racial hostility and examine the associations with birth weight and preterm birth. In this webinar, we cover Twitter data collection and processing, sentiment analysis, and use of machine learning to classify tweets for racist content. Use of nontraditional data sources like Twitter has the potential to lead to greater tracking of area-level racial bias and to provide essential information needed to develop interventions to reduce the impact of racial bias on health.
Part 2: Discussions of Miscarriage and Preterm Birth on Twitter.
Nina Cesare is a Postdoctoral Associate at Boston University School of Public Health. Twitter handle: @nlcesare
Studies suggest that there is a trend towards expressing disenfranchised grief on social media. However, no large studies have investigated trends and discussions around miscarriages and preterm births on Twitter. Our presentation will review findings from a study analyzing disclosure of miscarriage and preterm birth on Twitter. First, we will show that there are multiple conversation topics related to miscarriages and preterm births. Second, we demonstrate that specific events usually drive surges in discussions. Lastly, in addition to grief, we illustrate that women who have experienced a miscarriage may use social media to share feelings towards insensitive comments by clinicians, friends and family; healthcare costs; legislatures affecting women’s health etc. Our findings are intended to inform both researchers utilizing digital data for healthcare experience research, as well as clinicians seeking to guide conversations about miscarriage and preterm birth and improve patient care.
December 11, 2019 – 12:00-1:00pm EDT
Dr. Jeanette A Stingone
Incorporating machine learning approaches into perinatal and pediatric epidemiology: opportunities and challenges
The use of machine learning, broadly defined as analytic techniques that fit models algorithmically by adapting to patterns in data, is growing in use across many areas within public health and epidemiology. This talk will provide attendees with broad exposure to the elements of machine learning and its practical applications within perinatal and pediatric epidemiology. The talk will include discussion of technical aspects of machine learning, as well as important ethical and scientific considerations of using data-driven methods for epidemiologic research. A number of examples from the scientific literature will be presented and a general listing of resources for additional information and training will be provided.
Jeanette A Stingone PhD MPH
Assistant Professor, Department of Epidemiology
Mailman School of Public Health, Columbia University
Dr. Jeanette Stingone is an environmental epidemiologist with a focus on perinatal and pediatric health. She received her BS in Biomedical Engineering from Boston University, an MPH from the Mount Sinai School of Medicine and a PhD in Epidemiology from the University of North Carolina, Chapel Hill. Now an Assistant Professor in the Department of Epidemiology at Columbia University’s Mailman School of Public Health, she conducts research that couples data science techniques with epidemiologic methods to address research questions in children’s environmental health. Supported by an NIEHS-funded career development award, her current research seeks to uncover the combinations of air pollutants associated with adverse child health outcomes within high dimensional public health data. Read more
It is recommended to read the overview by Bi et al and then skimming the others, as Dr. Stingone will refer to these in the talk when providing examples.
1. Overview of ML approaches: Bi Q, Goodman KE, Kaminsky J, Lessler J. What is machine learning? A Primer for the epidemiologist. AJE 2019; https://doi.org/10.1093/1je/kwz189 [epub ahead of print]
2. Examples of implementation:
a. Pan I, Nolan LB, Brown RR, Khan R et al Machine learning for social services: a study of prenatal case management in Illinois. AJPH 2017; 107:938-944.
b. Chiavegatto Filho ADP, Dos Santos HG, do Nasciemento CF, Massa K, Kawachi I Overachieving municipalities in public health: a machine learning approach. Epidemiology 2018; 29:836-840.
c. Das LT, Abramson EL, Stone AE, Kondrich JE, Kern LM, Grinspan ZM. Predicting frequent emergency department visits among children with asthma using HER data. Pediatr Pulmonol 2017; 52:880-890.