Buonomo Bruno, Penitente Emanuela
Department of Mathematics and Applications, University of Naples Federico II, via Cintia, I-80126, Naples, Italy.
J Math Biol. 2025 Sep 16;91(4):41. doi: 10.1007/s00285-025-02280-3.
We consider a mathematical model to explore the effects of human behavioural changes on the transmission of two respiratory viruses, where co-infection is possible. The model includes an index to describe the human choices induced by information and rumours regarding the diseases. We first consider the case in which the public health authorities rely only on non-pharmaceutical containment measures and perform a qualitative analysis of the model through bifurcation theory, in order to analyse the existence and stability of both endemic and co-endemic equilibria. We also show the impact of the most relevant information-related parameters on the system dynamics. Then, we extend the model by assuming that a vaccine is available for each of the two viruses. We show how adherence to social distancing may be affected by information and rumours regarding the vaccination coverage in the community. Finally, we investigate the effects of seasonality by introducing a two-state switch function to represent a reduction in both vaccination and transmission rates during the summer season. We found that seasonality causes an increase in the prevalence peaks, suggesting that the detrimental effects due to the reduction of vaccination rates prevail over the beneficial ones due to the reduction of transmission.
我们考虑一个数学模型,以探究人类行为变化对两种呼吸道病毒传播的影响,这两种病毒可能会发生共同感染。该模型包含一个指数,用于描述由有关疾病的信息和谣言引发的人类选择。我们首先考虑公共卫生当局仅依靠非药物防控措施的情况,并通过分岔理论对模型进行定性分析,以便分析地方病平衡点和共同地方病平衡点的存在性与稳定性。我们还展示了最相关的信息相关参数对系统动态的影响。然后,我们通过假设两种病毒都有可用疫苗来扩展该模型。我们展示了关于社区疫苗接种覆盖率的信息和谣言可能如何影响对社交距离的遵守情况。最后,我们通过引入一个双态切换函数来表示夏季疫苗接种率和传播率的降低,从而研究季节性的影响。我们发现季节性会导致流行高峰增加,这表明疫苗接种率降低带来的有害影响超过了传播率降低带来的有益影响。