Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 118, Issue 1, Pages -Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2015455118
Keywords
nursing homes; COVID-19; complex networks; smartphone data
Categories
Funding
- Tobin Center at Yale University
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Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide, with outbreaks persisting despite visitor restrictions. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, while staff network connections and centrality within the greater network strongly predict COVID-19 cases.
Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in US nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirk-land, WA, to other skilled nursing facilities. The full extent of staff connections between nursing homes-and the role these connections serve in spreading a highly contagious respiratory infection-is currently unknown given the lack of centralized data on cross-facility employment. We perform a large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1% of smartphone users who visited a nursing home for at least 1 h also visited another facility during our 11-wk study period-even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7.1 other facilities. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Controlling for demographic and other factors, a home's staff network connections and its centrality within the greater network strongly predict COVID-19 cases.
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