IDEAS home Printed from https://ideas.repec.org/a/spr/dyngam/v14y2024i5d10.1007_s13235-023-00531-w.html
   My bibliography  Save this article

Stochastic Vaccination Game Among Influencers, Leader and Public

Author

Listed:
  • Vartika Singh

    (IIT Bombay)

  • Veeraruna Kavitha

    (IIT Bombay)

Abstract

Celebrities can significantly influence the public towards any desired outcome. In a bid to tackle an infectious disease, a leader (government) exploits such influence towards motivating a fraction of public to get vaccinated, sufficient enough to ensure eradication. The leader also aims to minimize the vaccinated fraction of public (that ensures eradication) and use minimal incentives to motivate the influencers; it also controls vaccine supply rates. Towards this, we consider a three-layered Stackelberg game, with the leader at the top. A set of influencers at the middle layer are involved in a stochastic vaccination game driven by incentives. The public at the bottom layer is involved in an evolutionary game with respect to vaccine responses. We prove the disease can always be eradicated once the public is sufficiently sensitive towards the vaccination choices of the influencers—with a minimal fraction of public vaccinated. This minimal fraction depends only on the disease characteristics and not on other aspects. Interestingly, there are many configurations to achieve eradication, each configuration is specified by a dynamic vaccine supply rate and a number—this number represents the count of the influencers that needs to be vaccinated to achieve the desired influence. Incentive schemes are optimal when this number equals all or just one; the former curbs free-riding among influencers, while the latter minimizes the dependency on influencers.

Suggested Citation

  • Vartika Singh & Veeraruna Kavitha, 2024. "Stochastic Vaccination Game Among Influencers, Leader and Public," Dynamic Games and Applications, Springer, vol. 14(5), pages 1268-1316, November.
    • Handle: RePEc:spr:dyngam:v:14:y:2024:i:5:d:10.1007_s13235-023-00531-w
    DOI: 10.1007/s13235-023-00531-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13235-023-00531-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13235-023-00531-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Isoni, Andrea & Poulsen, Anders & Sugden, Robert & Tsutsui, Kei, 2019. "Focal points and payoff information in tacit bargaining," Games and Economic Behavior, Elsevier, vol. 114(C), pages 193-214.
    2. Cyril Hédoin, 2016. "Community-Based Reasoning in Games: Salience, Rule-Following, and Counterfactuals," Games, MDPI, vol. 7(4), pages 1-17, November.
    3. Pope, Devin G. & Pope, Jaren C. & Sydnor, Justin R., 2015. "Focal points and bargaining in housing markets," Games and Economic Behavior, Elsevier, vol. 93(C), pages 89-107.
    4. Sundaram,Rangarajan K., 1996. "A First Course in Optimization Theory," Cambridge Books, Cambridge University Press, number 9780521497190, January.
    5. Streefland, Pieter H., 2001. "Public doubts about vaccination safety and resistance against vaccination," Health Policy, Elsevier, vol. 55(3), pages 159-172, March.
    6. Ashok P. Maitra & William D. Sudderth, 2007. "Subgame-Perfect Equilibria for Stochastic Games," Mathematics of Operations Research, INFORMS, vol. 32(3), pages 711-722, August.
    7. Gerber, Anke & Hens, Thorsten & Vogt, Bodo, 2010. "Rational investor sentiment in a repeated stochastic game with imperfect monitoring," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 669-704, December.
    8. Sundaram,Rangarajan K., 1996. "A First Course in Optimization Theory," Cambridge Books, Cambridge University Press, number 9780521497701, January.
    9. Erika Bonnevie & Sarah D Rosenberg & Caitlin Kummeth & Jaclyn Goldbarg & Ellen Wartella & Joe Smyser, 2020. "Using social media influencers to increase knowledge and positive attitudes toward the flu vaccine," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, 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. Brett, Craig & Weymark, John A., 2016. "Voting over selfishly optimal nonlinear income tax schedules with a minimum-utility constraint," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 18-31.
    2. Gonzalez, Stéphane & Rostom, Fatma Zahra, 2022. "Sharing the global outcomes of finite natural resource exploitation: A dynamic coalitional stability perspective," Mathematical Social Sciences, Elsevier, vol. 119(C), pages 1-10.
    3. Sawada, Hiroyuki & Yan, Xiu-Tian, 2004. "Application of Gröbner bases and quantifier elimination for insightful engineering design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 67(1), pages 135-148.
    4. John Duggan & Joanne Roberts, 2002. "Implementing the Efficient Allocation of Pollution," American Economic Review, American Economic Association, vol. 92(4), pages 1070-1078, September.
    5. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, December.
    6. Raffaella Giacomini & Toru Kitagawa, 2021. "Robust Bayesian Inference for Set‐Identified Models," Econometrica, Econometric Society, vol. 89(4), pages 1519-1556, July.
    7. Depetris Chauvin, Nicolas & Porto, Guido G., 2011. "Market Competition in Export Cash Crops and Farm Income," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126159, International Association of Agricultural Economists.
    8. Tina Kao & Flavio Menezes & John Quiggin, 2014. "Optimal access regulation with downstream competition," Journal of Regulatory Economics, Springer, vol. 45(1), pages 75-93, February.
    9. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised May 2023.
    10. Nirav Mehta, 2017. "Competition In Public School Districts: Charter School Entry, Student Sorting, And School Input Determination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(4), pages 1089-1116, November.
    11. Rasch, Alexander & Wambach, Achim, 2009. "Internal decision-making rules and collusion," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 703-715, November.
    12. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2009. "Pointwise Stationary Fluid Models for Stochastic Processing Networks," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 70-89, August.
    13. Zachary Feinstein, 2015. "Financial Contagion and Asset Liquidation Strategies," Papers 1506.00937, arXiv.org, revised Nov 2016.
    14. Calthrop, Edward & Proost, Stef, 2006. "Regulating on-street parking," Regional Science and Urban Economics, Elsevier, vol. 36(1), pages 29-48, January.
    15. Brett, Craig & Weymark, John A., 2017. "Voting over selfishly optimal nonlinear income tax schedules," Games and Economic Behavior, Elsevier, vol. 101(C), pages 172-188.
    16. Park, Hyungmin, 2023. "Developmental Dictatorship and Middle Class-driven Democratisation," The Warwick Economics Research Paper Series (TWERPS) 1485, University of Warwick, Department of Economics.
    17. Dan Kovenock & Brian Roberson, 2021. "Generalizations of the General Lotto and Colonel Blotto games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(3), pages 997-1032, April.
    18. Gregory Besharov, 2004. "Second‐Best Considerations in Correcting Cognitive Biases," Southern Economic Journal, John Wiley & Sons, vol. 71(1), pages 12-20, July.
    19. David Sayah & Stefan Irnich, 2019. "Optimal booking control in revenue management with two substitutable resources," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 189-222, April.
    20. Omar Besbes & Denis Sauré, 2014. "Dynamic Pricing Strategies in the Presence of Demand Shifts," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 513-528, October.

    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:spr:dyngam:v:14:y:2024:i:5:d:10.1007_s13235-023-00531-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.