Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control

TL;DR

This study analyzes online social media data to measure vaccine sentiments, revealing how sentiment clusters influence disease spread and offering a cost-effective method for public health intervention planning.

Contribution

It introduces a novel approach to quantify vaccine sentiments from social media and links sentiment clusters to infectious disease dynamics.

Findings

Strong correlation between online sentiments and CDC vaccination rates

Information flows more within same-sentiment communities

Negative sentiment clusters increase outbreak risk

Abstract

There is great interest in the dynamics of health behaviors in social networks and how they affect collective public health outcomes, but measuring population health behaviors over time and space requires substantial resources. Here, we use publicly available data from 101,853 users of online social media collected over a time period of almost six months to measure the spatio-temporal sentiment towards a new vaccine. We validated our approach by identifying a strong correlation between sentiments expressed online and CDC- estimated vaccination rates by region. Analysis of the network of opinionated users showed that information flows more often between users who share the same sentiments - and less often between users who do not share the same sentiments - than expected by chance alone. We also found that most communities are dominated by either positive or negative sentiments towards the novel vaccine. Simulations of infectious disease transmission show that if clusters of negative vaccine sentiments lead to clusters of unprotected individuals, the likelihood of disease outbreaks are greatly increased. Online social media provide unprecedented access to data allowing for inexpensive and efficient tools to identify target areas for intervention efforts and to evaluate their effectiveness.