Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure

Recurrent waves, which are often observed during long pandemics, typically form as a result of several interrelated dynamics, including public health interventions, population mobility and behaviour, varying disease transmissibility due to pathogen mutations, and changes in host immunity due to recency of vaccination or previous infections. Complex nonlinear dependencies among these dynamics, including feedback between disease incidence and the opinion-driven adoption of social distancing (SD) behaviour, remain poorly understood, particularly in scenarios involving heterogeneous population, partial and waning immunity and rapidly changing public opinions. This study addressed this challenge by proposing an opinion dynamics model that accounts for changes in SD behaviour (i.e. whether to adopt SD) by modelling both individual risk perception and peer pressure. The opinion dynamics model was integrated and validated within a large-scale agent-based COVID-19 pandemic simulation that modelled the spread of the Omicron variant of SARS-CoV-2 between December 2021 and June 2022 in Australia. Our study revealed that while holding epidemiological factors constant, the fluctuating adoption of SD, shaped by individual risk aversion and social peer pressure from both household and workplace environments, can reproduce these multi-wave patterns, pointing to the importance of social dynamics in understanding epidemic outcomes.

Authors

Institutions

Publication Details

Journal
Interface Focus
Published
2025-09-26
DOI
https://doi.org/10.1098/rsfs.2024.0038
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
1.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure

Rebecca J. Rockett, Tania C. Sorrell, Quang Dang Nguyen, Mikhail Prokopenko et al.
1 citations
Interface Focus
Opinion Dynamics and Social Influence
1.32
article

Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure

Rebecca J. Rockett, Tania C. Sorrell, Quang Dang Nguyen, Mikhail Prokopenko, Alexandra Martiniuk, Sheryl L. Chang, Carl J. E. Suster, Vitali Sintchenko, Christina M. Jamerlan
article en
1 citations

Abstract

Recurrent waves, which are often observed during long pandemics, typically form as a result of several interrelated dynamics, including public health interventions, population mobility and behaviour, varying disease transmissibility due to pathogen mutations, and changes in host immunity due to recency of vaccination or previous infections. Complex nonlinear dependencies among these dynamics, including feedback between disease incidence and the opinion-driven adoption of social distancing (SD) behaviour, remain poorly understood, particularly in scenarios involving heterogeneous population, partial and waning immunity and rapidly changing public opinions. This study addressed this challenge by proposing an opinion dynamics model that accounts for changes in SD behaviour (i.e. whether to adopt SD) by modelling both individual risk perception and peer pressure. The opinion dynamics model was integrated and validated within a large-scale agent-based COVID-19 pandemic simulation that modelled the spread of the Omicron variant of SARS-CoV-2 between December 2021 and June 2022 in Australia. Our study revealed that while holding epidemiological factors constant, the fluctuating adoption of SD, shaped by individual risk aversion and social peer pressure from both household and workplace environments, can reproduce these multi-wave patterns, pointing to the importance of social dynamics in understanding epidemic outcomes.

Interface FocusVol. 15(4)
The University of Sydney (AU), Taronga Conservation Society Australia (AU), Westmead Hospital (AU), Infectious Diseases Institute (UG)
Openalex Percentile: Top 16%
Opinion Dynamics and Social Influence
1.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.