Digital Twin Neighborhoods for Research on Place-Based Health Inequalities in Mid-Life

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Digital Twin Neighborhoods for Research on Place-Based Health Inequalities in Mid-Life Increasingly, it is recognized that high-value therapies, screening tools and preventive services have created or increased inequalities experienced by persons from racial and ethnic minority backgrounds, those of low socioeconomic position (SEP) and other vulnerable groups. This project aims to chart a new course for understanding place-based population health strategies. A growing literature on health and place has demonstrated the outsize influence of social and neighborhood indicators versus traditional clinical measures in driving individual health outcomes. Thus, our overall objective is to empower community members and organizations, local health systems and population health and political leaders to use evidence from place- based research to inform, prioritize, evaluate and implement health-promoting strategies that close health disparities. The cornerstone innovation of our work is the development of Digital Twin Neighborhoods which will dramatically expand access to data and algorithms for understanding placed-based health and social inequalities. Digital Twin Neighborhoods (DTNs) are digital replicas of real communities, including biological, social and geographic data and algorithms in a cloud computing environment. In this project, we will i) establish community- and privacy-focused procedures for constructing Digital Twin Neighborhoods which incorporate EHR data; ii) evaluate the efficacy of a DTN approach to understanding mechanisms of place- based health inequities in mid-life across multiple health conditions and geographies; and iii) examine the generalizability and scalability of the DTN approach for studying place-based mid-life health inequalities. The developed open science DTN platform will make the combination of modeling capabilities and privacy preserving features available to multi-sector initiatives that are aimed at evaluating local health inequalities and informing strategic population health policy decisions. Thus, the results of this work will i) provide a framework for mechanistic understanding of clinical, social and environmental forces producing disparities in life expectancy, multi-morbidity, and the onset and management of chronic disease and ii) catalyze researchers and community and health care institutions both locally and nationally to improve equity and meet the needs of the communities they serve.