Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916341812822016 |
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| author | Chang, Sheryl L. Nguyen, Quang Dang Suster, Carl J. E. Jamerlan, Christina M. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Martiniuk, Alexandra Prokopenko, Mikhail |
| author_facet | Chang, Sheryl L. Nguyen, Quang Dang Suster, Carl J. E. Jamerlan, Christina M. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Martiniuk, Alexandra Prokopenko, Mikhail |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00011 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure Chang, Sheryl L. Nguyen, Quang Dang Suster, Carl J. E. Jamerlan, Christina M. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Martiniuk, Alexandra Prokopenko, Mikhail Quantitative Methods Populations and Evolution 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. |
| title | Impact of opinion dynamics on recurrent pandemic waves: balancing risk aversion and peer pressure |
| topic | Quantitative Methods Populations and Evolution |
| url | https://arxiv.org/abs/2408.00011 |