Dynamical evolution of social network polarization and its impact on the propagation of a virus

TL;DR

This paper investigates how social network polarization influences COVID-19 virus spread, showing that increased polarization leads to more widespread infection, emphasizing the importance of considering societal structure in epidemic modeling.

Contribution

It introduces an analysis of social network polarization dynamics and its impact on virus propagation using agent-based modeling, highlighting the effects of vaccination strategies in polarized societies.

Findings

Polarized networks have more clustered communities.

Virus spreads more extensively in polarized social networks.

Vaccination strategies need to account for societal polarization.

Abstract

The COVID-19 pandemic that emerged in 2020 has highlighted the complex interplay between vaccine hesitancy and societal polarization. In this study, we analyse the dynamical polarization within a social network as well as the network properties before and after a vaccine was made available. Our results show that as the network evolves from a less structured state to one with more clustered communities. Then using an agent-based modeling approach, we simulate the propagation of a virus in a polarized society by assigning vaccines to pro-vaccine individuals and none to the anti-vaccine individuals. We compare this propagation to the case where the same number of vaccines is distributed homogeneously across the population. In polarized networks, we observe a significantly more widespread diffusion of the virus, highlighting the importance of considering polarization for epidemic forecasting.