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Program Launch and Lecture: Injury-Related Health Equity Across the Lifespan

Join us in launching the Injury-related Health Equity Across the Lifespan (I-Heal) Program at the University of Washington Harborview Injury Prevention and Research Center in Spring 2017!

Public Lecture with Adil Haider

Dr. Haider, an active trauma and critical care surgeon, is credited with uncovering racial disparities after traumatic injury and establishing the field of trauma disparities research. He will be speaking about “cultural dexterity” in health care and provide a roadmap for research and practice in this area.

The lecture is supported by the Population Health Initiative, Harborview Injury Prevention & Research Center, School of Social Work, and the Institute of Translational Health Sciences.

Book Event: CSDE Affiliate Gunnar Almgren – Health Care as a Right of Citizenship

Faculty, staff, and students are invited to attend a presentation and discussion of the arguments for health care as a right of democratic citizenship, as advanced in CSDE Affiliate Gunnar Almgren’s newly released book—Health Care as a Right of Citizenship: The Continuing Evolution of Reform.

The event will feature Almgren offering a brief overview of the evolution of American exceptionalism in health care, explaining the current political and social context that motivated the book, and unpacking the book’s main arguments. A discussion, facilitated by UW Professor of Philosophy Bill Talbott, with and among the audience will follow.  The event is free and open to the entire three-campus UW community.

CSSS Seminar: A Network Model for Dynamic Textual Communications with Application to Government Email Corpora

Abstract: In this paper, we introduce the interaction-partitioned topic model (IPTM)—a probabilistic model of who communicates with whom about what, and when. Broadly speaking, the IPTM partitions time-stamped textual communications, such as emails, according to both the network dynamics that they reflect and their content. To define the IPTM, we integrate a dynamic version of the exponential random graph model—a generative model for ties that tend toward structural features such as triangles—and latent Dirichlet allocation—a generative model for topic-based content. The IPTM assigns each topic to an “interaction pattern”—a generative process for ties that is governed by a set of dynamic network features. Each communication is then modeled as a
mixture of topics and their corresponding interaction patterns. We use the IPTM to analyze emails sent between department managers in two county governments in North Carolina; one of these email corpora covers the Outer Banks during the time period surrounding Hurricane Sandy. Via this application, we demonstrate that the IPTM is effective at predicting and explaining continuous-time textual communications.

Next Population Science Insights: PAA Practice Session

The 2017 Population Association of America meeting is just around the corner, and CSDE’s speakers are primed to practice their presentations in front of an audience.

Presentation Topics

  • Christine Leibbrand – “Great Migration’s Great Return? An Examination of Second-Generation Return Migration to the South”
  • Lee Fiorio – “Sprawl and Neighborhood Change: Patterns of ‘White Flight’ Amid Growing Neighborhood-Level Racial Diversity, 1990 to 2010”
  • Jessica Godwin – “Probabilistic Population Projections for Countries with Generalized HIV/AIDS Epidemics”

More information is available below. Come by this Friday to learn about their work on demography’s cutting edge!

*Please plan to allow around 15 additional minutes after presentations for audience questions and feedback.


Christine Leibbrand – “Great Migration’s Great Return? An Examination of Second-Generation Return Migration to the South”

Presented alongside Catherine Massey, J. Trent Alexander, and Stewart Tolnay

Abstract: Using novel panel data spanning 1940-2000, we examine the children of the Great Migration who returned to the South. We observe two types of return migrants: (1) southern-born, “lifetime” return migrants who were born in the South, resided outside of the South in 1940, and returned to the South by 2000, and (2) northern-born, “generational” return migrants whose parents were born in the South but who, themselves, were born in the North, resided in the North in 1940, and had returned to the South by 2000. These data also allow us to observe return migrants and their parents over a longer period of time than any previous data source, permitting us to definitively identify both southern- and northern-born return migrants. Using these data, we find that generational migrants comprise a large majority of return migrants to the South and that these migrants are positively selected on their own and their parents’ socioeconomic characteristics, relative to second-generation Great Migration migrants who remain in the North. Conversely, southern-born return migrants are negatively selected. For both groups of return migrants, returning to one’s or one’s parents’ birth state is common, though it is particularly likely among southern-born return migrants.

Christine is a graduate student with the Department of Sociology. Her research focuses on internal migration within the United States, its associations with individual and familial socioeconomic outcomes, and the extent to which race and gender play into these relationships. She is also involved with several independent and collaborative research projects looking at second generation Great Migration migrants, segregation and neighborhood attainment, and the influence of paternal incarceration on maternal neighborhood outcomes. Christine has presented her work at conferences including the American Sociological Association’s (ASA) annual conference, the Population Association of America (PAA) annual conference, and the Pacific Sociological Association (PSA) annual conference.

Lee Fiorio – “Sprawl and Neighborhood Change: Patterns of ‘White Flight’ Amid Growing Neighborhood-Level Racial Diversity, 1990 to 2010”

Abstract: Over the last half century, the literatures on racial segregation and sprawl have largely been kept separate. This paper aims to rectify this deficit by conducting an analysis of the sprawl of populations in four race/ethnicity categories (white, black, Asian and Latino) in 52 large US metropolitan areas, 1990 to 2010. Findings indicate that white flight remains a dominate feature of the residential landscape despite increasing neighborhood diversity in inner ring suburbs. These results provide a framework for assessing the future trajectories of neighborhood change, urban spatial development and segregation as the relative share of the white population continues to fall into the next decade and beyond.

Lee is a third year graduate student in the department of geography and CSDE fellow. His work focuses on neighborhood change and migration in the US context with an emphasis on methodology and data visualization.

Jessica Godwin – “Probabilistic Population Projections for Countries with Generalized HIV/AIDS Epidemics”

Presented alongside David J. Sharrow, Yanjun He, Samuel J. Clark and Adrian E. Raftery

Abstract: The UN issued official probabilistic population projections for all countries to 2100 for the first time in July 2015. This was done by simulating future levels of total fertility and life expectancy from Bayesian hierarchical models, and combining the results using a standard cohort-component projection method. The 40 countries with generalized HIV/AIDS epidemics were treated differently from others, in that the projections used the multistate Spectrum/EPP model, a complex 15-compartment model that was designed for short-term projections of quantities relevant to policy for the epidemic. Here we propose a simpler approach. Changes in life expectancy are projected probabilistically using a simple time series regression model on current life expectancy, HIV prevalence and ART coverage. These are then converted to age- and sex-specific mortality rates using a new family of model life tables designed for countries with HIV/AIDS epidemics that reproduces the characteristic hump in middle adult mortality. These are then input to the standard cohort-component method, as for other countries. The method performed well in an out-of-sample cross-validation experiment. It gives similar population projections to Spectrum/EPP in the short run, while being simpler and avoiding multistate modeling.

Jessica is a PhD student in the Department of Statistics and a CSDE BD2K Fellow. She currently works with advisor Jon Wakefield on Bayesian space-time methods for estimating and projecting under-five mortality in countries without vital registration. Previously, she worked with Adrian Raftery on Bayesian projections of life expectancy in the presence of a generalized HIV/AIDS epidemic. She received her B.S. in actuarial science and M.S. in statistics from Auburn University.

R Programming for Sample Size Calculations

This workshop is an introduction to programming (e.g., writing functions and using loops) in the open source statistical language R using the context of simple sample size and power calculations. It requires previous experience with R and RStudio.

Global Burden of Disease Study – 20th Anniversary Symposium

The Global Burden of Disease study is the world’s largest systematic, scientific effort to quantify the magnitude of health loss from all major diseases, injuries, and risk factors by age, sex, and population. With 2,303 collaborators in 130 countries and territories, the study examines 332 diseases and injuries and 84 risk factors. The GBD has helped transform health care policy in numerous countries, and has greatly influenced research, policy, and education.

Speakers and participants will explore various topics, including:

  • The history and evolution of the Global Burden of Disease enterprise
  • The epidemiological transition and progress toward improving health
  • Emerging challenges in health metrics sciences
  • The key risk factors that are driving health loss
  • The power and impact of subnational estimates
  • The future of the GBD

The event is co-hosted by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington and The Lancet. This event is primarily organized into a series of plenary and panel sessions, with the exception of one full day of training on September 25.

Since health metrics sciences is a multidisciplinary field, conference participants will represent a variety of academic and professional perspectives. Invitees include researchers, academic leaders, students, policymakers, non-governmental organizations, foundations, and national and multinational health organizations.

I hope you will be able to join us. To learn more about this event and to register, please visit our event website.

Fragile Families Challenge

The Fragile Families Challenge is a mass collaboration that will combine predictive modeling, causal inference, and in-depth interviews to yield insights that can improve the lives of disadvantaged children in the United States.  By working together we can discover things that none of us can discover individually.

The Fragile Families Challenge is based on the Fragile Families and Child Wellbeing Study, which has followed thousands of American families for more than 15 years.  During this time, the Fragile Families study collected information about the children, their parents, their schools, and their larger environments.

These data have been used in hundreds of scientific papers and dozens of dissertations, and insight from these studies are routinely shared with policy makers around the world through the Future of Children, which is jointly published by Princeton University and Brookings Institution. Your challenge is to use this data in a new way.  Given all the background data from birth to year 9 and some training data from year 15, how well can you infer six key outcomes in the year 15 test data?

The Fragile Families Challenge is our attempt to create a new way of doing social research, one that is much more open to the talents and efforts of everyone. We expect that by combining ideas from social science and data science, we can—together—help address important scientific and social problems. And, we expect that through a mass collaboration we will accomplish things that none of us could accomplish individually.

The Fragile Families Challenge will involve two steps. In the first step, described above, participants will build statistical and machine learning models of several important outcomes in the lives of the children. Participants will then submit their code, their model outputs, and a narrative explanation of their modeling strategy. Then, we will use the unreleased test set to evaluate each model. This first step is an example of the common task method, which David Donoho (2015) has called the “secret sauce” of machine learning. At the end of the first step, we will optimally combine all the individual models into a community model. A variety of results about ensemble methods in machine learning suggest that this community model will perform better than the best individual model.

In the second step, we will use the individual models and the community model to conduct substantive and methodological research.

Network Modeling for Epidemics

Network Modeling for Epidemics (NME) is a 5-day short course at the University of Washington that provides an introduction to stochastic network models for infectious disease transmission dynamics, with a focus on empirically based modeling of HIV transmission.  It is a ”hands-on” course, using the EpiModel software package in R (www.epimodel.org). EpiModel provides a unified framework for statistically based modeling of dynamic networks from empirical data, and simulation of epidemic dynamics on these networks. It has a flexible open-source platform for learning and building several types of epidemic models: deterministic compartmental, stochastic individual-based, and stochastic network models. Resources include simple models that run in a browser window, built-in generic models that provide basic control over population contact patterns, pathogen properties and demographics, and templates for user-programmed modules that allow EpiModel to be extended to the full range of pathogens, hosts, and disease dynamics for advanced research.

This course will touch on the deterministic and individual-based models, but its primary focus is on the theory, methods and application of network models. The course uses mornings for lectures, and afternoons for labs with students working in small groups.  On the final day, students have the option of developing an EpiModel prototype for their own research projects, with input from the instructors, which includes the lead EpiModel software developer, Dr. Samuel Jenness.

Returning students: We encourage previous attendees with active modeling projects to apply to return for a refresher course.  The EpiModel package has been significantly enhanced over the last few years. Returning students with active projects will have the opportunity to work with course instructors to address key challenges in the design of their network model code.

Dates and location:

The course will be taught from Monday, August 14 to Friday, August 18 on the University of Washington campus in Seattle.

Application dates and decision dates:

  • May 1: Fellowship application deadline. Decisions will be made by May 15.
  • June 1:  General application deadline.  Applications will continue to be accepted on a rolling basis until this date. Decisions will be made by June 15.

Costs:

Course fee is $500. Travel and accommodation costs are the responsibility of the participant, although discounted hotel rates will be available. We offer a limited number of fellowships for pre-doctoral students or for attendees from low income countries; these cover waiver of the registration fee only (travel and accommodation are still the responsibility of the fellowship recipient).

Application:

Apply online at https://catalyst.uw.edu/webq/survey/morrism/329397

Course website and more information:  http://statnet.github.io/nme

Graduate Student Conference Travel Awards

The UW’s Population Health Initiative is offering Graduate Student Conference Travel Awards of up to $1,500 to further students’ academic, research, or professional goals as they strive to become the next generation of leaders in population health. The application period for this round of funding opens on April 10, 2017 and closes on Friday, April 28, 2017.

These awards are open to graduate students on all three campuses who:

  1. Are currently enrolled in a graduate degree program.
  2. Have been accepted to present a population health-related paper, poster, or exhibit, or to serve as an invited speaker, at a conference, symposium, or other professional and academic meeting. Students in the arts may request funding for invited performances or installations.

In order to apply, an applicant must be nominated by a faculty member. Once nominated, applicants will receive an email with a link to their portion of the application.

To learn more, please visit the link below.