CSDE Affiliate Gregory Bratman (College of the Environment) released an article with co-authors in Science Advances, titled “Nature and human well-being: The olfactory pathway“. The world is undergoing massive atmospheric and ecological change, driving unprecedented challenges to human well-being. Olfaction is a key sensory system through which these impacts occur. The sense of smell influences quality of and satisfaction with life, emotion, emotion regulation, cognitive function, social interactions, dietary choices, stress, and depressive symptoms. Exposures via the olfactory pathway can also lead to (anti-)inflammatory outcomes. Authors integrate perspectives from a range of health, social, and natural systems to provide an overview of this unique sensory system and its role in the pathway between natural environments and human well-being. This fascinating research was supported by a Population Planning Research Grant (PPRG) from CSDE. This research was also featured in an article by UW News, where Bratman discusses the project’s significance.
Opportunity for Funding from the Northwest Climate Adaptation Science Center: FY25 Project Solicitation, USGS-Directed Funding
JSDE Seminar to Host Matt Lowe
Call for Papers: Scholarly Migration and Mobility Symposium
CSDE Seminar – Measuring the Hidden Burden of Violence: Use of Explicit and Proxy Diagnoses Codes for Violence Identification and its Association with Economic Hardship
CSDE welcomes you to a seminar with Jeanie Santaularia (Epidemiology, UW) on Friday, May 24th from 12:30-1:30 in 360 PAR and on Zoom (register here). Dr. Santaularia (she/her/ella) is an interdisciplinary population health researcher. Before coming to UW she was a Postdoctoral Scholar in Population Science with the Carolina Population Center at the University of North Carolina at Chapel Hill. She completed her doctoral training in Epidemiology from the University of Minnesota and Master of Public Health in Epidemiology from the University of Illinois at Chicago. Prior to beginning her doctoral studies, Dr. Santaularia worked in various capacities with local and state governments in epidemiological surveillance and practice.
Her primary areas of research include violence prevention, social epidemiology, health equity, social determinants of health, and analytical methods to obtain causal estimates in social epidemiology when traditional randomized control trials are either not feasible or unethical. Dr. Santaularia’s current body of research examines how: (1) social and institutional determinants influence violence; and (2) violence gets under the skin or is ‘embodied’ to impact health. She aims to expand this research to better understand the cumulative influence of violence over the life course as well as the roles of society, community, psychosocial and family protective factors in offsetting negative outcomes due to violence. Ultimately, she will build on this research to develop and test scalable interventions in underserved populations informed by understanding the role of larger social structures, familial and cultural contexts.
Pelletier to Present in UW’s Three Minute Thesis (3MT) Competition on May 23 (Thursday @3pm)!
CSDE Trainee Lizzy Pelletier (Evans School of Public Policy & Governance) will be presenting at this year’s UW Three Minute Thesis (3MT) Competition! Lizzy’s talk is titled ‘Does Paid Leave Help All Parents?’. UW 3MT is a professional development competition that celebrates the exciting capstone and research experiences of master’s and doctoral students at the University of Washington. The competition supports graduate students’ capacity to effectively explain their research or capstone project in three minutes, in a language appropriate to a public audience. The event will occur on Thursday, May 23, 2024 from 3:00-4:00 in the auditorium of Alder Hall. Doors open at 2:30 pm. RSVP here and cheer Lizzy on!
Flores, Casey, and Colleagues Highlight the Disproportionate Impacts of Severe Weather-driven Power Outages
CSDE Affiliate Joan Casey and colleagues released an article in Plos Climate, titled “Powerless in the storm: Severe weather-driven power outages in New York State, 2017–2020“. This article was lead-authored by Nina Flores, a Phd candidate in Columbia University’s Mailman School of Public Health. Flores and Casey also discussed their findings in a co-authored piece in The Conversation. The vulnerability of the power grid to severe weather events is a critical issue as climate change is expected to increase extreme events, which can damage components of the power grid and/or lessen electrical power supply, resulting in power outages. However, largely due to an absence of granular spatiotemporal outage data, we lack a robust understanding of how severe weather-driven outages, their community impacts, and their durations distribute across space and socioeconomic vulnerability. Here, authors pair hourly power outage data in electrical power operating localities (n = 1865) throughout NYS with urbanicity, CDC Social Vulnerability Index, and hourly weather (temperature, precipitation, wind speed, lightning strike, snowfall) data. Authors used these data to characterize the impact of extreme weather events on power outages from 2017–2020, while considering neighborhood vulnerability factors.
Upcoming Disaster Resilience Lunch Event on Hazards, Human Behavior, and Health
Berridge and Co-authors Offer a Research Agenda on AI and Aging
CSDE Affiliate Clara Berridge (Social Work) released a new article with co-authors in The Gerontologist, titled “Addressing the Black Box of AI – A Model and Research Agenda on the Co-Constitution of Aging and Artificial Intelligence“. Algorithmic technologies and large data infrastructures, often referred to as AI, have received increasing attention from gerontological research in the last decade. While there is much literature that dissects and explores the development, application, and evaluation of AI relevant for gerontology, this article makes a novel contribution by critically engaging with the theorizing in this growing field of research.
CSDE Computational Demography Working Group (CDWG) Hosts Aja Sutton on Incorporating spatial structure into multilevel regression and poststratification for subnational demographic and small area estimation (5/22/2024)
On Wednesday, May 22nd from 9:00 AM – 10:00 AM, CDWG will host Dr. Aja Sutton to introduce her research. Dr. Aja Sutton is a Postdoctoral Scholar in the Social Sciences Division at the Stanford Doerr School of Sustainability, Stanford University. She received her PhD from the Department of Geography at the University of Washington (UW). From 2020-2022 she was TADA-BSSR NIH T32 Fellow in Data Science and Demography Training at UW’s Center for Studies in Demography and Ecology, from which she also holds a Certificate in Demographic Methods. She received an MA in History from Western University, and an MSc in Palaeopathology from Durham University. Her work is focused on population health, computational social science, and epidemiology. The event will take place in 223 Raitt and on Zoom (register here).
Title: Incorporating spatial structure into multilevel regression and poststratification for subnational demographic and small area estimation
Abstract: Demography is a discipline dependent on the accurate enumeration of population-level processes, especially the count of individuals. When near-perfect census enumeration or representative survey data are unavailable for a particular outcome of interest, it is often difficult to establish the count of that outcome in a population. Instead, we may be able to make indirect estimates through small area estimation (SAE) methods; these use additional contextual information to produce statistically robust estimates of under- or unobserved subpopulations or geographic units. Multilevel regression and poststratification (MRP) is a model-based statistical method that uses national/high-level administrative survey or census data to adjust for non-representativeness in subnational surveys, and to provide small area estimation in areas where subnational survey data are sparse or nonexistent. MRP is computationally inexpensive and generally able to produce quick, consistent, and accurate estimates, and prevailing approaches borrow strength from other administrative areal data through partial (global) pooling. While this approach is effective, it does not account for any potential existing neighborhood spatial structure in the data. Including spatial specifications in MRP is a powerful way to better handle existing spatial relationships and generate more accurate area-level estimates. Join us as we learn more about MRP, Bayesian methods for exploring and handling spatial structure in data, while considering how to improve indirect estimates of 2021 COVID-19 vaccination in California using MRP with spatial structure.