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Doctors' and Nurses' Social Media Ads Reduced Holiday Travel and COVID-19 Infections: A Cluster Randomized Controlled Trial

Author

Listed:
  • Emily Breza
  • Fatima Cody Stanford
  • Marcella Alsan
  • Burak Alsan
  • Abhijit Banerjee
  • Arun G. Chandrasekhar
  • Sarah Eichmeyer
  • Traci Glushko
  • Paul Goldsmith-Pinkham
  • Kelly Holland
  • Emily Hoppe
  • Mohit Karnani
  • Sarah Liegl
  • Tristan Loisel
  • Lucy Ogbu-Nwobodo
  • Benjamin A. Olken
  • Carlos Torres
  • Pierre-Luc Vautrey
  • Erica Warner
  • Susan Wootton
  • Esther Duflo

Abstract

During the COVID-19 epidemic, many health professionals started using mass communication on social media to relay critical information and persuade individuals to adopt preventative health behaviors. Our group of clinicians and nurses developed and recorded short video messages to encourage viewers to stay home for the Thanksgiving and Christmas Holidays. We then conducted a two-stage clustered randomized controlled trial in 820 counties (covering 13 States) in the United States of a large-scale Facebook ad campaign disseminating these messages. In the first level of randomization, we randomly divided the counties into two groups: high intensity and low intensity. In the second level, we randomly assigned zip codes to either treatment or control such that 75% of zip codes in high intensity counties received the treatment, while 25% of zip codes in low intensity counties received the treatment. In each treated zip code, we sent the ad to as many Facebook subscribers as possible (11,954,109 users received at least one ad at Thanksgiving and 23,302,290 users received at least one ad at Christmas). The first primary outcome was aggregate holiday travel, measured using mobile phone location data, available at the county level: we find that average distance travelled in high-intensity counties changed by -0.993 percentage points (95% CI -1.616, -0.371, p-value 0.002) the three days before each holiday. The second primary outcome was COVID-19 infection at the zip-code level: COVID-19 infections recorded in the two-week period starting five days post-holiday declined by 3.5 percent (adjusted 95% CI [-6.2 percent, -0.7 percent], p-value 0.013) in intervention zip codes compared to control zip codes.

Suggested Citation

  • Emily Breza & Fatima Cody Stanford & Marcella Alsan & Burak Alsan & Abhijit Banerjee & Arun G. Chandrasekhar & Sarah Eichmeyer & Traci Glushko & Paul Goldsmith-Pinkham & Kelly Holland & Emily Hoppe & , 2021. "Doctors' and Nurses' Social Media Ads Reduced Holiday Travel and COVID-19 Infections: A Cluster Randomized Controlled Trial," NBER Working Papers 29021, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29021
    Note: EH LS PE POL
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    References listed on IDEAS

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    1. Vivi Alatas & Arun G. Chandrasekhar & Markus Mobius & Benjamin A. Olken & Cindy Paladines, 2019. "When Celebrities Speak: A Nationwide Twitter Experiment Promoting Vaccination In Indonesia," NBER Working Papers 25589, National Bureau of Economic Research, Inc.
    2. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
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    Cited by:

    1. Matilde Giaccherini & Joanna Kopinska & Gabriele Rovigatti, 2022. "Vax Populi: The Social Costs of Online Vaccine Skepticism," CESifo Working Paper Series 10184, CESifo.
    2. Gutierrez, Emilio & Rubli, Adrian & Tavares, Tiago, 2022. "Information and behavioral responses during a pandemic: Evidence from delays in Covid-19 death reports," Journal of Development Economics, Elsevier, vol. 154(C).
    3. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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