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

Theresa Kuchler, Dominic Russel and Johannes Stroebel

No 8241, CESifo Working Paper Series from CESifo

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.

Keywords: social connectedness; Covid-19; coronavirus; communicable disease (search for similar items in EconPapers)
JEL-codes: C60 I10 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-for, nep-gen, nep-net, nep-pay and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (84)

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Working Paper: The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks as Measured by Facebook (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_8241

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