An integral renewal equation approach to behavioural epidemic models with information index.

IF 2.2 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-12-17 DOI:10.1007/s00285-024-02172-y
Bruno Buonomo, Eleonora Messina, Claudia Panico, Antonia Vecchio
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Abstract

We propose an integral model describing an epidemic of an infectious disease. The model is behavioural in the sense that the force of infection includes the information index that describes the opinion-driven human behavioural changes. The information index contains a memory kernel to mimic how the individuals maintain memory of the past values of the infection. We obtain sufficient conditions for the endemic equilibrium to be locally stable. In particular, we show that when the infectivity function is represented by an exponential distribution, stability is guaranteed by the weak Erlang memory kernel. However, through numerical simulations, we show that oscillations, possibly self-sustained, may arise when the memory is more focused in the disease's past history, as exemplified by the strong Erlang kernel. We also show the model solutions in cases of different infectivity functions taken from studies where specific diseases like Influenza and SARS are considered.

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我们提出了一个描述传染病流行的整体模型。该模型是行为模型,即感染力包括信息指数,信息指数描述了由舆论驱动的人类行为变化。信息指数包含一个记忆内核,用于模拟个体如何保持对过去感染值的记忆。我们获得了地方性均衡局部稳定的充分条件。我们特别指出,当感染率函数由指数分布表示时,弱二郎记忆核可以保证稳定性。然而,通过数值模拟,我们表明,当记忆更集中于疾病的过去历史时,可能会出现振荡,而且可能是自我维持的振荡。我们还展示了在不同感染率函数情况下的模型解决方案,这些感染率函数来自对流感和 SARS 等特定疾病的研究。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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