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

12 Pages Posted: 28 Apr 2020

See all articles by Theresa Kuchler

Theresa Kuchler

New York University (NYU)

Dominic Russel

Harvard University - Business School (HBS)

Johannes Stroebel

New York University (NYU) - Leonard N. Stern School of Business; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

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Date Written: 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.

Keywords: social connectedness, COVID-19, coronavirus, communicable disease

JEL Classification: C600, I100

Suggested Citation

Kuchler, Theresa and Russel, Dominic and Stroebel, Johannes, The Geographic Spread of COVID-19 Correlates with Structure of Social Networks as Measured by Facebook (2020). CESifo Working Paper No. 8241, Available at SSRN: https://ssrn.com/abstract=3587255 or http://dx.doi.org/10.2139/ssrn.3587255

Theresa Kuchler (Contact Author)

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
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Dominic Russel

Harvard University - Business School (HBS) ( email )

Boston, MA 02163
United States

Johannes Stroebel

New York University (NYU) - Leonard N. Stern School of Business ( email )

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New York, NY NY 10012
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National Bureau of Economic Research (NBER) ( email )

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Centre for Economic Policy Research (CEPR) ( email )

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United Kingdom

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