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

22 Pages Posted: 13 Apr 2020 Last revised: 1 Apr 2023

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: April 2020

Abstract

We use aggregated data from Facebook to show that COVID-19 was more likely to spread between regions with stronger social network connections. Areas with more social ties to two early COVID-19 “hotspots” (Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more confirmed COVID-19 cases as of the end of March. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population densities of the regions. As the pandemic progressed in the U.S., a county's social proximity to recent COVID- 19 cases predicts future outbreaks over and above physical proximity. These results suggest data from online social networks can be useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.

Suggested Citation

Kuchler, Theresa and Russel, Dominic and Stroebel, Johannes, The Geographic Spread of Covid-19 Correlates with the Structure of Social Networks as Measured by Facebook (April 2020). NBER Working Paper No. w26990, Available at SSRN: https://ssrn.com/abstract=3574454

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
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Johannes Stroebel

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

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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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