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Go Big or Go Home: A Free and Perfectly Safe but Only Partially Effective Vaccine Can Make Everyone Worse Off

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  • Eduard Talamà s

    (Department of Economics, University of Pennsylvania)

  • Rakesh Vohra

    (Department of Economics, University of Pennsylvania)

Abstract

Vaccines are crucial to curb infectious-disease epidemics. Indeed, one of the highest priorities of the National Institutes of Health (NIH) on the HIV front is the development and delivery of a vaccine that is at least moderately effective. However, risk compensation could undermine the ability of partially-effective vaccines to curb epidemics: Since vaccines reduce the cost of risky interactions, vaccinated agents may optimally choose to engage in more of them and, as a result, may increase everyone’s infection probability. We show that—in contrast to the prediction of standard models—things can be worse than that: A free and perfectly safe but only partially effective vaccine can reduce everyone’s welfare. The reason is simple: By reducing the cost of risky interactions, a partially-effective vaccine can destabilize the existing interaction structure in favor of a less efï¬ cient one. Because of the strategic complementarities in risky interactions that we show a rise when agents strategically choose their partners, the most efï¬ cient stable interaction structure after the introduction of a partially-effective vaccine can be much denser and—due to the negative externalities of risky interactions—worse for everyone. The result of this paper underscorestheimportanceoftakingintoaccounttheeffectsthatdifferentinterventions have on social structure, and it suggests that the NIH might want to go big—i.e. deliver a highly-effective vaccine—or go home.

Suggested Citation

  • Eduard Talamà s & Rakesh Vohra, 2018. "Go Big or Go Home: A Free and Perfectly Safe but Only Partially Effective Vaccine Can Make Everyone Worse Off," PIER Working Paper Archive 18-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 15 Jan 2018.
  • Handle: RePEc:pen:papers:18-006
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    References listed on IDEAS

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    Cited by:

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    4. Adriani, Fabrizio & Ladley, Dan, 2021. "Social distance, speed of containment and crowding in/out in a network model of contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 597-625.
    5. Fabrizio Adriani, 2020. "Social distance, speed of containment, and crowding in/out in a network model of contagion," Discussion Papers 2020-10, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.

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