Complex dynamics of a fractional-order delayed epidemic model incorporating waning immunity and optimal control

Suvankar Majee, Soovoojeet Jana, T. K. Kar, Bidhan Bhunia
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Abstract

To explore the effect of memory, we first incorporate the fractional-order derivative in our defined model, which is a SIR-type epidemic model with logistic growth in susceptible and incubation delay in saturated incidence rate. Based on the value of a threshold parameter \(R_0\), called basic reproduction number, there exist two equilibria. Also, depending on that threshold value, stability and Hopf bifurcation analysis were performed in our formulated model. To study the effects of vaccination and treatment on Hopf bifurcation, we include these measures in our model and derive that these measures may increase the length of the critical delay. We also looked into a fractional-order optimal control problem to better understand the optimal role of treatment and vaccination in reducing disease prevalence and lowering associated costs. We have run simulations to verify the analytical results, considering the model’s feasible parameter values. Finally, to study the uncertainty analysis, we have used the partial rank correlation coefficient technique.

Abstract Image

包含免疫力减弱和优化控制的分数阶延迟流行病模型的复杂动力学
为了探索记忆的影响,我们首先在定义的模型中加入了分数阶导数,该模型是一个 SIR 型流行病模型,易感者呈对数增长,饱和发病率呈潜伏延迟。根据阈值参数 \(R_0\)(称为基本繁殖数)的值,存在两个均衡点。同时,根据该临界值,我们对所建立的模型进行了稳定性和霍普夫分岔分析。为了研究疫苗接种和治疗对霍普夫分岔的影响,我们在模型中加入了这些措施,并得出这些措施可能会增加临界延迟的长度。我们还研究了分数阶最优控制问题,以更好地理解治疗和疫苗接种在减少疾病流行和降低相关成本方面的最佳作用。考虑到模型的可行参数值,我们进行了模拟来验证分析结果。最后,为了研究不确定性分析,我们使用了偏等级相关系数技术。
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