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

Sheryl L. Chang, Quang Dang Nguyen, Carl J. E. Suster, Christina M. Jamerlan, Rebecca J. Rockett, Vitali Sintchenko, Tania C. Sorrell, Alexandra Martiniuk, Mikhail Prokopenko
{"title":"Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure","authors":"Sheryl L. Chang, Quang Dang Nguyen, Carl J. E. Suster, Christina M. Jamerlan, Rebecca J. Rockett, Vitali Sintchenko, Tania C. Sorrell, Alexandra Martiniuk, Mikhail Prokopenko","doi":"arxiv-2408.00011","DOIUrl":null,"url":null,"abstract":"Recurrent waves which are often observed during long pandemics typically form\nas a result of several interrelated dynamics including public health\ninterventions, population mobility and behaviour, varying disease\ntransmissibility due to pathogen mutations, and changes in host immunity due to\nrecency of vaccination or previous infections. Complex nonlinear dependencies\namong these dynamics, including feedback between disease incidence and the\nopinion-driven adoption of social distancing behaviour, remain poorly\nunderstood, particularly in scenarios involving heterogeneous population,\npartial and waning immunity, and rapidly changing public opinions. This study\naddressed this challenge by proposing an opinion dynamics model that accounts\nfor changes in social distancing behaviour (i.e., whether to adopt social\ndistancing) by modelling both individual risk perception and peer pressure. The\nopinion dynamics model was integrated and validated within a large-scale\nagent-based COVID-19 pandemic simulation that modelled the spread of the\nOmicron variant of SARS-CoV-2 between December 2021 and June 2022 in Australia.\nOur study revealed that the fluctuating adoption of social distancing, shaped\nby individual risk aversion and social peer pressure from both household and\nworkplace environments, may explain the observed pattern of recurrent waves of\ninfections.","PeriodicalId":501266,"journal":{"name":"arXiv - QuanBio - Quantitative Methods","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Quantitative Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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 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 social distancing behaviour (i.e., whether to adopt social distancing) 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 the fluctuating adoption of social distancing, shaped by individual risk aversion and social peer pressure from both household and workplace environments, may explain the observed pattern of recurrent waves of infections.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
舆论动态对经常性流行病浪潮的影响:平衡风险规避和同伴压力
在长期大流行期间经常观察到的反复波通常是由几个相互关联的动态因素造成的,包括公共卫生干预、人口流动和行为、病原体突变导致的不同疾病传播性,以及接种疫苗的时间或先前感染导致的宿主免疫力变化。人们对这些动态变化之间复杂的非线性依赖关系,包括疾病发病率与公众意见驱动的社会疏远行为之间的反馈,仍然知之甚少,尤其是在涉及异质性人口、部分免疫力和免疫力减弱以及公众意见快速变化的情况下。为了应对这一挑战,本研究提出了一个舆论动态模型,该模型通过对个人风险认知和同伴压力进行建模,来解释社会疏远行为(即是否采取社会疏远)的变化。我们的研究表明,个人风险规避和来自家庭和工作场所的社会同伴压力形成的社会疏远行为的波动性,可以解释所观察到的反复出现的感染浪潮模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities Automating proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks Active learning for energy-based antibody optimization and enhanced screening Comorbid anxiety symptoms predict lower odds of improvement in depression symptoms during smartphone-delivered psychotherapy
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1