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The Geographic Spread of COVID-19 Correlates with Structure of Social Networks as Measured by Facebook

Authors :
Kuchler, Theresa
Russel, Dominic
Stroebel, Johannes
Publication Year :
2020
Publisher :
Munich: Center for Economic Studies and ifo Institute (CESifo), 2020.

Abstract

We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population density of the regions. These results suggest that data from online social networks may prove useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od......1687..b6a86642ea9851084ec024eedc56d52a