IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/30414.html
   My bibliography  Save this paper

Passing the Message: Peer Outreach about COVID-19 Precautions in Zambia

Author

Listed:
  • Alfredo Burlando
  • Pradeep Chintagunta
  • Jessica Goldberg
  • Melissa Graboyes
  • Peter Hangoma
  • Dean Karlan
  • Mario Macis
  • Silvia Prina

Abstract

During public health emergencies, spreading accurate information and increasing adherence to recommended behaviors is vital for communal welfare. However, uncertainty, mistrust, and misinformation can slow the adoption of best practices. Preexisting social networks can amplify and endorse information from authorities, and technology makes peer-to-peer messaging scalable and fast. Using text messages and small cash incentives, we test a peer-based information campaign to encourage adherence to recommended COVID-19-related health behaviors in Zambia. Individuals respond favorably to the suggestion to pass messages to peers; however, financial incentives neither increase the dissemination of messages nor cause changes in health behaviors.

Suggested Citation

  • Alfredo Burlando & Pradeep Chintagunta & Jessica Goldberg & Melissa Graboyes & Peter Hangoma & Dean Karlan & Mario Macis & Silvia Prina, 2022. "Passing the Message: Peer Outreach about COVID-19 Precautions in Zambia," NBER Working Papers 30414, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:30414
    Note: DEV
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w30414.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lori Beaman & Jeremy Magruder, 2012. "Who Gets the Job Referral? Evidence from a Social Networks Experiment," American Economic Review, American Economic Association, vol. 102(7), pages 3574-3593, December.
    2. Abhijit Banerjee & Arun G Chandrasekhar & Esther Duflo & Matthew O Jackson, 2019. "Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(6), pages 2453-2490.
    3. Emily Oster & Rebecca Thornton, 2012. "Determinants Of Technology Adoption: Peer Effects In Menstrual Cup Take-Up," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1263-1293, December.
    4. Alan T. Sorensen, 2006. "Social learning and health plan choice," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 929-945, December.
    5. Pope, Devin G., 2009. "Reacting to rankings: Evidence from "America's Best Hospitals"," Journal of Health Economics, Elsevier, vol. 28(6), pages 1154-1165, December.
    6. Zacharias Maniadis & Fabio Tufano & John A. List, 2017. "To Replicate or Not To Replicate? Exploring Reproducibility in Economics through the Lens of a Model and a Pilot Study," Economic Journal, Royal Economic Society, vol. 127(605), pages 209-235, October.
    7. Zacharias Maniadis & Fabio Tufano & John A. List, 2017. "To Replicate or Not To Replicate? Exploring Reproducibility in Economics through the Lens of a Model and a Pilot Study," Economic Journal, Royal Economic Society, vol. 127(605), pages 209-235, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jessica Goldberg & Mario Macis & Pradeep Chintagunta, 2023. "Incentivized Peer Referrals for Tuberculosis Screening: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 15(1), pages 259-291, January.
    2. Goldberg, Jessica & Macis, Mario & Chintagunta, Pradeep, 2018. "Leveraging Patients' Social Networks to Overcome Tuberculosis Underdetection: A Field Experiment in India," IZA Discussion Papers 11942, Institute of Labor Economics (IZA).
    3. Bonan, Jacopo & Battiston, Pietro & Bleck, Jaimie & LeMay-Boucher, Philippe & Pareglio, Stefano & Sarr, Bassirou & Tavoni, Massimo, 2021. "Social interaction and technology adoption: Experimental evidence from improved cookstoves in Mali," World Development, Elsevier, vol. 144(C).
    4. S Anukriti & Catalina Herrera‐Almanza & Praveen K. Pathak & Mahesh Karra, 2020. "Curse of the Mummy‐ji: The Influence of Mothers‐in‐Law on Women in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(5), pages 1328-1351, October.
    5. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.
    6. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    7. Fafchamps, Marcel & Islam, Asad & Malek, Mohammad Abdul & Pakrashi, Debayan, 2020. "Can referral improve targeting? Evidence from an agricultural training experiment," Journal of Development Economics, Elsevier, vol. 144(C).
    8. Engström, Per & Forsell, Eskil, 2018. "Demand effects of consumers’ stated and revealed preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 43-61.
    9. Cátia Batista & Marcel Fafchamps & Pedro C Vicente, 2022. "Keep It Simple: A Field Experiment on Information Sharing among Strangers [Changing Saving and Investment Behavior: The Impact of Financial Literacy Training and Reminders on Micro-Businesses]," The World Bank Economic Review, World Bank, vol. 36(4), pages 857-888.
    10. Francesco Drago & Friederike Mengel & Christian Traxler, 2020. "Compliance Behavior in Networks: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 96-133, April.
    11. Li, Lunzheng & Maniadis, Zacharias & Sedikides, Constantine, 2021. "Anchoring in Economics: A Meta-Analysis of Studies on Willingness-To-Pay and Willingness-To-Accept," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    12. Weili Ding, 2020. "Laboratory experiments can pre-design to address power and selection issues," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 6(2), pages 125-138, December.
    13. Pushkar Maitra & Sandip Mitra & Dilip Mookherjee & Sujata Visaria, 2020. "Decentralized Targeting of Agricultural Credit Programs: Private versus Political Intermediaries," HKUST IEMS Working Paper Series 2020-70, HKUST Institute for Emerging Market Studies, revised Jan 2020.
    14. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    15. Marcel Fafchamps & Simon Quinn, 2018. "Networks and Manufacturing Firms in Africa: Results from a Randomized Field Experiment," The World Bank Economic Review, World Bank, vol. 32(3), pages 656-675.
    16. Barrera,Oscar & Macours,Karen & Premand,Patrick & Vakis,Renos, 2020. "Texting Parents about Early Child Development : Behavioral Changes and Unintended Social Effects," Policy Research Working Paper Series 9492, The World Bank.
    17. Luigi Butera & Philip Grossman & Daniel Houser & John List & Marie-Claire Villeval, 2020. "A New Mechanism to Alleviate the Crises of Confidence in Science - With an Application to the Public Goods Game," Artefactual Field Experiments 00684, The Field Experiments Website.
    18. Amedeo Piolatto, 2015. "Online booking and information: competition and welfare consequences of review aggregators," Working Papers 2015/11, Institut d'Economia de Barcelona (IEB).
    19. John List, 2021. "2021 Summary Data of Artefactual Field Experiments Published on Fieldexperiments.com," Artefactual Field Experiments 00749, The Field Experiments Website.
    20. Javdani, Moshen & Chang, Ha-Joon, 2019. "Who Said or What Said? Estimating Ideological Bias in Views Among Economists," MPRA Paper 91958, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • H0 - Public Economics - - General
    • I0 - Health, Education, and Welfare - - General
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:30414. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.