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

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Listed:
  • Theresa Kuchler
  • Dominic Russel
  • Johannes Stroebel

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

  • Theresa Kuchler & Dominic Russel & Johannes Stroebel, 2020. "The Geographic Spread of COVID-19 Correlates with the Structure of Social Networks as Measured by Facebook," NBER Working Papers 26990, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26990
    Note: CF EFG EH ITI PE POL
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    References listed on IDEAS

    as
    1. Bailey, Michael & Gupta, Abhinav & Hillenbrand, Sebastian & Kuchler, Theresa & Richmond, Robert & Stroebel, Johannes, 2021. "International trade and social connectedness," Journal of International Economics, Elsevier, vol. 129(C).
    2. Theresa Kuchler & Yan Li & Lin Peng & Johannes Stroebel & Dexin Zhou, 2022. "Social Proximity to Capital: Implications for Investors and Firms," The Review of Financial Studies, Society for Financial Studies, vol. 35(6), pages 2743-2789.
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    JEL classification:

    • I0 - Health, Education, and Welfare - - General
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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