Modeling the interplay between seasonal flu outcomes and individual vaccination decisions

TL;DR

This paper introduces a new model of seasonal flu vaccination decisions that incorporates social psychology insights, revealing complex population behaviors like biennial oscillations around herd immunity thresholds.

Contribution

It develops a coupled disease and vaccination model based on experimental social psychology data, improving realism over traditional rational choice assumptions.

Findings

Model reproduces known epidemiological results.

Identifies conditions for herd immunity self-organization.

Discovers biennial oscillations in vaccination coverage.

Abstract

Seasonal influenza presents an ongoing challenge to public health. The rapid evolution of the flu virus necessitates annual vaccination campaigns, but the decision to get vaccinated or not in a given year is largely voluntary, at least in the United States, and many people decide against it. In early attempts to model these yearly flu vaccine decisions, it was often assumed that individuals behave rationally, and do so with perfect information -- assumptions that allowed the techniques of classical economics and game theory to be applied. However, the usual assumptions are contradicted by the emerging empirical evidence about human decision-making behavior in this context. We develop a simple model of coupled disease spread and vaccination dynamics that instead incorporates experimental observations from social psychology to model annual vaccine decision-making more realistically. We investigate population-level effects of these new decision-making assumptions, with the goal of understanding whether the population can self-organize into a state of herd immunity, and if so, under what conditions. Our model agrees with established results while also revealing more subtle population-level behavior, including biennial oscillations about the herd immunity threshold.