Analysis of COVID-19 and comorbidity co-infection model with optimal control.

IF 2 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Optimal Control Applications & Methods Pub Date : 2021-11-01 Epub Date: 2021-06-02 DOI:10.1002/oca.2748
Andrew Omame, Ndolane Sene, Ikenna Nometa, Cosmas I Nwakanma, Emmanuel U Nwafor, Nneka O Iheonu, Daniel Okuonghae
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Abstract

In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 with re-infection in order to assess the impact of prior comorbidity (specifically, diabetes mellitus) on COVID-19 complications. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection by comorbid susceptibles as well as the rate of reinfection by those who have recovered from a previous COVID-19 infection. Simulations of the cumulative number of active cases (including those with comorbidity), at different reinfection rates, show infection peaks reducing with decreasing reinfection of those who have recovered from a previous COVID-19 infection. In addition, optimal control and cost-effectiveness analysis of the model reveal that the strategy that prevents COVID-19 infection by comorbid susceptibles is the most cost-effective of all the control strategies for the prevention of COVID-19.

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COVID-19与合并症合并感染最优控制模型分析。
在这项工作中,我们开发并分析了COVID-19再感染动态的数学模型,以评估既往合并症(特别是糖尿病)对COVID-19并发症的影响。使用与尼日利亚拉各斯的疾病动态相关的数据对该模型进行模拟,预测在存在或不存在合并症的情况下达到高峰时期。该模型出现了后向分叉现象,这是由于考虑了共病易感人群对COVID-19感染的易感性增加以及之前感染COVID-19的康复者的再感染率的参数造成的。对不同再感染率的累计活动性病例(包括合并病例)的模拟显示,感染高峰随着先前COVID-19感染康复者再感染的减少而减少。此外,模型的最优控制和成本效益分析表明,通过共病易感者预防COVID-19感染的策略是所有预防COVID-19控制策略中最具成本效益的策略。
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来源期刊
Optimal Control Applications & Methods
Optimal Control Applications & Methods 工程技术-应用数学
CiteScore
3.90
自引率
11.10%
发文量
108
审稿时长
3 months
期刊介绍: Optimal Control Applications & Methods provides a forum for papers on the full range of optimal and optimization based control theory and related control design methods. The aim is to encourage new developments in control theory and design methodologies that will lead to real advances in control applications. Papers are also encouraged on the development, comparison and testing of computational algorithms for solving optimal control and optimization problems. The scope also includes papers on optimal estimation and filtering methods which have control related applications. Finally, it will provide a focus for interesting optimal control design studies and report real applications experience covering problems in implementation and robustness.
期刊最新文献
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