Revealing Decision-Making Strategies of Americans in Taking COVID-19 Vaccination

• Published in: Bulletin of mathematical biology Vol. 86; no. 6; p. 72
• Main Authors: Aghaeeyan, Azadeh, Ramazi, Pouria, Lewis, Mark A.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2024; Springer Nature B.V
• Subjects: Cell Biology; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; COVID-19 Vaccines - administration & dosage; Decision Making; Humans; Life Sciences; Mathematical and Computational Biology; Mathematical Concepts; Mathematics; Mathematics and Statistics; Models, Biological; Original Article; Politics; SARS-CoV-2 - immunology; United States - epidemiology; Vaccination - psychology; Vaccination - statistics & numerical data; Vaccination Coverage - statistics & numerical data; Vaccination Hesitancy - psychology; Vaccination Hesitancy - statistics & numerical data; Vaccines; United States; Imitation dynamics; COVID-19; Decision-making strategies; Best-response dynamics; Vaccine uptake
• ISSN: 0092-8240; 1522-9602
• DOI: 10.1007/s11538-024-01290-4

Efficient coverage for newly developed vaccines requires knowing which groups of individuals will accept the vaccine immediately and which will take longer to accept or never accept. Of those who may eventually accept the vaccine, there are two main types: success-based learners, basing their decisions on others’ satisfaction, and myopic rationalists, attending to their own immediate perceived benefit. We used COVID-19 vaccination data to fit a mechanistic model capturing the distinct effects of the two types on the vaccination progress. We proved the identifiability of the population proportions of each type and estimated that 47 % of Americans behaved as myopic rationalists with a high variation across the jurisdictions, from 31 % in Mississippi to 76 % in Vermont. The proportion was correlated with the vaccination coverage, proportion of votes in favor of Democrats in 2020 presidential election, and education score.