Housing Precarity, Eviction, and Inequality in the Wake of COVID-19
- Funded by C3.ai DTI
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Funder
C3.ai DTIPrincipal Investigator
Prof and Prof and Assis Prof Karen Chapple, Matthew Desmond, Joshua BlumenstockResearch Location
United States of AmericaLead Research Institution
University of California-Berkeley, Princeton UniversityResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Social impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Ensuring housing security is vital to mitigating the spread of the COVID-19 virus and sustaining health, economic security, and family stability. This joint, interdisciplinary project will bring together academics and data scientists to track, analyze, and respond to pandemic-driven spikes in eviction and displacement risks. Doing so requires development of: 1) an innovative system for tracking real-time eviction filings after the outbreak; and 2) a housing precarity risk model using machine learning, to better analyze and predict areas at disproportionate risk of displacement in the wake of the COVID-19 pandemic. This project will provide major new sources of data and inform research and public policy regarding U.S. housing and inequality.