Seminar

Nursing Home Staff Networks & COVID-19

September 7, 2021
 at 
3:00 pm
EST
See how SafeGraph data powered research from UCLA & Yale about shared staff networks of skilled-nursing facilities and the spread of COVID-19.

Skilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.

Learn more about this research from UCLA and Yale using SafeGraph data by watching the on-demand seminar, presented by UCLA's Elisa Long.

See how SafeGraph data powered research from UCLA & Yale about shared staff networks of skilled-nursing facilities and the spread of COVID-19.

Skilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.

Learn more about this research from UCLA and Yale using SafeGraph data by watching the on-demand seminar, presented by UCLA's Elisa Long.

Speakers
See how SafeGraph data powered research from UCLA & Yale about shared staff networks of skilled-nursing facilities and the spread of COVID-19.

Skilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.

Learn more about this research from UCLA and Yale using SafeGraph data by watching the on-demand seminar, presented by UCLA's Elisa Long.

Speakers
Seminar

Nursing Home Staff Networks & COVID-19

September 7, 2021
 at 
3:00 pm
EST

Seminar

See how SafeGraph data powered research from UCLA & Yale about shared staff networks of skilled-nursing facilities and the spread of COVID-19.

Skilled nursing homes (SNFs) accounted for a disproportionate share of COVID-19 fatalities worldwide, with outbreaks persisting despite the March 2020 nationwide ban on visitors. Using device-level geolocation data for 50 million smartphones, we analyze SNF connections via shared staff and observe 500,000 individuals entering at least one SNF, with 5.1% entering two or more facilities. Nursing homes share connections with 7.1 other facilities, on average. Network measures of connectivity, including node degree, strength and Eigenvector centrality, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size.

Learn more about this research from UCLA and Yale using SafeGraph data by watching the on-demand seminar, presented by UCLA's Elisa Long.

Speakers

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