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Quantifying Neighborhood-Level Social Determinants of Health and Risk Landscapes
Associations between social and neighborhood characteristics and health outcomes are well known but remain poorly understood owing to complex, multidimensional factors that vary across geographic space. Growing interest in quantifying social determinants of health (SDOH) at a small-area resolution must account for such complexity. In a recent cross-sectional study, a Kolak-led team developed multidimensional SDOH indices and a regional typology of the continental U.S. at a small-area level using dimension reduction and clustering machine learning techniques, spatializing results at each stage. The modeling of SDOH as multivariate, geographic phenomena may better capture the complexity and spatial heterogeneity underlying SDOH and associated disparities in health outcomes. Extensions of this work may also characterize and define risk landscapes in complex environments, from the opioid epidemic to COVID-19 pandemic. For example, the US Covid Atlas Project integrates regional contextual factors within a dynamic hotspot surveillance application. During a time of increased attention to SDOH, a spatially explicit approach may provide actionable information for key stakeholders with respect to the focus of interventions -- and better understand what constitutes, drives, and sustains resilient communities.

Oct 28, 2020 11:00 AM in Eastern Time (US and Canada)

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Dr. Marynia Kolak
Assistant Director of Health Informatics & Senior Lecturer in GIScience @Center for Spatial Data Science, University of Chicago
Marynia Kolak, MS, MFA, PhD, is a health geographer and data scientist using open science tools and an exploratory data analytic approach to investigate issues of equity across space and time. Her research centers on how “place” impacts health outcomes in different ways, for different people, from opioid risk environments to chronic disease clusters. She focuses on quantifying and distilling the structural determinants of health across different environments, tying socio-ecological models of public health with geocomputational methods and quasi-experimental policy evaluation techniques. Marynia is the Assistant Director of Health Informatics and Senior Lecturer in GIScience at the Center for Spatial Data Science, University of Chicago. She received her Ph.D in Geography at Arizona State University, M.F.A in Writing from Roosevelt University, M.S. in GIS from John Hopkins University, and B.S. in Geology from the University of Illinois at Urbana-Champaign.