Echo chambers and opinion dynamics explain the occurrence of vaccination hesitancy

Abstract

Vaccination hesitancy is a major obstacle to achieving and maintaining herd immunity. Therefore, public health authorities need to understand the dynamics of an anti-vaccine opinion in the population. We introduce a spatially structured mathematical model of opinion dynamics with reinforcement. The model allows as an emergent property for the occurrence of echo chambers, i.e. opinion bubbles in which information that is incompatible with one’s entrenched worldview, is probably disregarded. We scale the model both to a deterministic limit and to a weak-effects limit, and obtain bifurcations, phase transitions and the invariant measure. Fitting the model to measles and meningococci vaccination coverage across Germany, reveals that the emergence of echo chambers dynamics explains the occurrence and persistence of the anti-vaccination opinion in allowing anti-vaxxers to isolate and to ignore pro-vaccination facts. We predict and compare the effectiveness of different policies aimed at influencing opinion dynamics in order to increase vaccination uptake. According to our model, measures aiming at reducing the salience of partisan anti-vaccine information sources would have the largest effect on enhancing vaccination uptake. By contrast, measures aiming at reducing the reinforcement of vaccination deniers are predicted to have the smallest impact.

Behavioural interventions to reduce vaccine hesitancy driven by misinformation on social media

“…Such closed environments are unlikely to include different viewpoints or corrective information, so misinformation is more likely to be reinforced. Rather than rely on outright bans, policy makers and content managers should explore methods that limit the spread and influence of misinformation 92…”

Intellectual Virtues and Scientific Endeavor: A Reflection on the Commitments Inherent in Generating and Possessing Knowledge

“…Meanwhile, environmental and health crises represent a fertile ground for uncertainty, confusion, disinformation, and misinformation (Nelson et al, 2020; Wang et al, 2022). It is not surprising, given the diversity of social structures that characterize the post-truth culture, such as epistemic bubbles that arise from an inadequate (though usually unintentional) coverage resulting from the omission of important epistemic resources (e.g., hypotheses, evidence, arguments), as well as echo chambers, in which diverse viewpoints relevant to the discussions at hand are actively excluded and discredited (Nguyen, 2020), the latter being particularly relevant when explaining the resistance to evidence that characterizes climate change deniers (Nguyen, 2020) and the anti-vaccine attitudes in COVID-19 pandemic (Müller et al, 2022).…”

Opinion Models, Election Data, and Political Theory

“…In that, these papers are able discuss possible mechanisms that generate striking patterns in data [ 11 , 12 , 13 , 14 , 15 ], aim to reveal changes in communication patterns in the course of time [ 16 ], or address spatial communication distances [ 17 ]. Not only in political processes, but also in other fields such as vaccination hesitancy, opinion models contribute to an adequate description of the underlying communication mechanisms and, in that, potentially open up ways to handle (in this case) public health problems [ 9 , 20 , 21 ]. It is, however, noticeable that all these aforementioned approaches from socio-physics and socio-mathematics up to now only have a small or no echo in the social and political sciences.…”

“…In the second part, we analyze election data from the United States (US), United Kingdom (UK), France (FRA), and Germany (GER) based on four opinion dynamics models (the Curie–Weiss model, the weak and strong effects continuum limit of the q-voter model, and, additionally, the weak effects limit of the reinforcement model [ 21 ]). We use this analysis to test the models to find out to what extent they are able to describe the data not only qualitatively, but also quantitatively.…”