Optimal Policies for Vaccine Campaign: The Case of COVID-19

Abstract

We model the Coronavirus disease 2019 (COVID-19) vaccine uptake by assuming (based on the most updated surveys) that the target population has mixed beliefs and is composed of three (rational, skeptic, negationist) types. We calibrate the model with the most reliable historical or forecasted likelihoods of COVID-19 contagion, health effects from contagion, vaccine efficacy and vaccine harm for the Italian population by considering its original features with respect to other vaccines (differential effects on age classes, compressed time for vaccine testing, risk of lockdown, effects of web and social media communication, large scale target population). Our findings show that the vaccine campaign can get close to (but not reach) herd immunity if the under 16 are not vaccinated and the negationist remain contrary to vaccination. Policies that can raise the vaccinated share are communication of news about short term positive outcome of the first vaccinated group to the skeptic group and campaigns creating solidarity frames in the young. We as well discuss the options of mandatory rules and/or soft constraints (introduced by the private or the government sector) versus voluntariness. We however show that sub-herd immunity equilibria can be sufficient to reduce significantly pressure on hospitals thereby creating conditions to bring social and economic life to normality.

Keywords: vaccine, COVID-19, nudging

JEL Classification: D71, I12, I18