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

Author

Listed:
  • Theresa Kuchler
  • Dominic Russel
  • Johannes Stroebel

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.

Suggested Citation

  • Theresa Kuchler & Dominic Russel & Johannes Stroebel, 2020. "The Geographic Spread of Covid-19 Correlates with Structure of Social Networks as Measured by Facebook," CESifo Working Paper Series 8241, CESifo.
    • Handle: RePEc:ces:ceswps:_8241
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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:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General

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