OBJECTIVES: To value the fear of COVID-19 contagion.

METHODS: A cross-sectional, web-based discrete choice experiment was conducted among 500 U.S. adults. A Bayesian efficient design was used to generate choice sets. Each choice set contained two hypothetical COVID-19 vaccine alternatives described by seven attributes—the chance of infection, the chance of having severe symptoms from infection, the protection duration, the chance of mild to moderate adverse events from vaccination, the chance of serious adverse events from vaccination, the chance of future exposure to COVID-19 as a result of vaccination, and out-of-pocket cost—and no vaccine as a reference alternative. Mixed logit (ML) and latent class (LC) models were developed. Willingness-to-pay (WTP) for eliminating the possibility of COVID-19 exposure was calculated to value the fear of contagion.

RESULTS: ML model showed all attributes were significantly associated with the preferences for COVID-19 vaccines and captured significant preference heterogeneity for all attributes. Overall, WTP for no chance of COVID-19 exposure as a result of vaccination was $9,966, compared to the medium chance of exposure. LC model revealed two participant classes. All attributes were significantly important for participants in class 1 (average class probability 75%), while all attributes, except the chance of infection, the chance of having severe symptoms from infection, and the chance of either mild to moderate or serious adverse events from vaccination, were significant for participants in class 2. Class 1 had higher proportions of infected (44%) and fully vaccinated (84%) participants. The participants in class 1 were willing to pay higher than those in class 2 ($9,460 vs. $2,651) for no chance of COVID-19 exposure.

CONCLUSIONS: This study affirmed that people valued the elimination of the possibility of COVID-19 exposure (fear of contagion) in addition to other benefits and risks of COVID-19 vaccines. However, preference heterogeneity was observed.