Department of Mathematics "F. Casorati", University of Pavia, Pavia, Italy.
Bull Math Biol. 2023 Mar 29;85(5):36. doi: 10.1007/s11538-023-01147-2.
Understanding the impact of collective social phenomena in epidemic dynamics is a crucial task to effectively contain the disease spread. In this work, we build a mathematical description for assessing the interplay between opinion polarization and the evolution of a disease. The proposed kinetic approach describes the evolution of aggregate quantities characterizing the agents belonging to epidemiologically relevant states and will show that the spread of the disease is closely related to consensus dynamics distribution in which opinion polarization may emerge. In the present modelling framework, microscopic consensus formation dynamics can be linked to macroscopic epidemic trends to trigger the collective adherence to protective measures. We conduct numerical investigations which confirm the ability of the model to describe different phenomena related to the spread of an epidemic.
理解集体社会现象对传染病动力学的影响是有效控制疾病传播的关键任务。在这项工作中,我们建立了一个数学描述,用于评估意见极化与疾病演变之间的相互作用。所提出的动力学方法描述了描述属于流行病学相关状态的个体的聚合量的演变,并将表明疾病的传播与意见极化可能出现的共识动态分布密切相关。在当前的建模框架中,微观共识形成动力学可以与宏观流行趋势联系起来,以引发对保护措施的集体遵守。我们进行了数值研究,证实了该模型描述与传染病传播有关的不同现象的能力。