Nikhil Vellodi* and Joshua Weiss

Vaccine policies are a crucial ingredient in the eradication of pandemics. Given the scarcity of supply, and the urgent need for roll-out, the prudent prioritization of vaccine allocation is of paramount importance. Prevailing prioritization schemes revolve around two key attributes: vulnerability risk and transmission risk. Thus far, however, little attention has been devoted to the role that behavior plays in designing optimal vaccination policies, despite growing evidence of its importance.

In this article, Nikhil Vellodi and Joshua Weiss offer a simple, tractable theoretical model that addresses these issues by combining three key elements: people differ both in their rate of contact with others, as well as their vulnerability to adverse symptoms; people exert negative externalities through interaction; and people can take voluntary preventative measures, for instance self-isolation. Their main result is a full characterization of the optimal allocation of vaccines, taking as given behavioral incentives. It displays three striking features. First, it exhibits an exposure premium – people with higher contact rates require a lower effective risk to be vaccinated. This feature reflects the gain from targeting interactive individuals due to the greater negative externalities they impose on others. Second, it is non-monotone – more people with intermediate vulnerability are vaccinated than the most and least vulnerable. Intuitively, people with intermediate vulnerability are still at significant risk but fail to self-isolate. Thirdly, the policy is invariant to vulnerability for those who voluntarily self-isolate. This property reveals two distinct roles of contact rates. For those who voluntarily self-isolate, the contact rate reflects self-isolation costs, as agents with higher contact rates must bear greater costs to avoid interaction. For those who interact, the contact rate reflects the costs of personal risk and transmission to others.

The paper is primarily designed to introduce a simple framework that provides important theoretical insights regarding a sensitive and politically charged problem. Nevertheless, Vellodi and Weiss proceed to perform a suite of numerical exercises, not only to further explore key properties of the optimal policy, but also to compare it to commonly considered heuristics, such as policies that vaccinate only the most vulnerable, policies that vaccinate only the most interactive, and also policies that vaccinate according to effective risk. Several policy-relevant insights emerge. Purely vulnerability-based policies perform significantly worse than other heuristics, in particular when supply is limited. Vaccine allocation should be geographically dispersed rather than concentrated, and should favor regions that either do not or struggle to implement mandatory lockdown policies. Finally, as vulnerability and exposure become more negatively correlated – an empirically relevant case –, the welfare losses from heuristic policies relative to the optimal policy become greater.



Original title of the article: Optimal Vaccine Allocation: Incentives and Spillovers

Published in: CEPR – Covid Economics, Issue 65

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