SAR-CoV-2 流行波进化转变的混合模型

IF 4.033 Q4 Biochemistry, Genetics and Molecular Biology
A. Yu. Perevaryukha
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引用次数: 0

摘要

分析了sars - cov -2毒株定期更新导致当前疫情发展的具体变异,并比较了该感染传播的特殊情景建模方法。建模方法发展的相关性是由于2024年许多地区的COVID病例波重新增长,这是脉动流行病过程的一种不寻常的变体。最近的感染爆发是由BA.2.86 Pirola菌株进化分支的活性决定的,该分支已经成功分裂,并且在亲和力和抗体避免方面比以前占主导地位的Omicron EG.5和XBB.1.5系更有效。2024年,与Delta相比,该菌株对ACE2受体的亲和力降低,复制率降低,保持了足够的传播力,同时病毒的持续时间增加。在群体免疫的情况下,病毒进化的趋势发生了变化,重点是使系统发育树复杂化,选择能够提供复制和抗体回避平衡特性的Spike蛋白变体。冠状病毒蛋白变异性的潜力显然还没有耗尽,预测其有希望的突变的方法正在开发中。讨论了基于扩展办公室个人状态集修正的“SIR模型”的流行病情景计算研究方法。基于sir的方程系统的变体不能描述早在2020年就观察到的COVID波的恢复。状态转换方案原则上不适用于描述流行病的非线性振荡模式,即使在线性SIR方案中包含二阶振荡方程时也是如此。作者基于具有延迟和阈值效应的方程开发的用于衰减COVID波的模型已经进行了修改,以考虑到新的Omicron线改变了振荡模式。振荡模态的变化,我们已经确定了增加的重复情况下,不能仅仅通过重新排列方程的参数与阻尼函数来描述。根据观察到的新冠肺炎疫情时间表,需要对模型中的监管功能进行重组。基于非线性振荡的性质,提出了用特殊的计算方法来模拟现代流行病过渡阶段的各个方面。提出了一种基于非均匀延迟调节参数产生松弛振荡和违反真值准则的重定义谓词的微分方程的右侧集形成混合模型结构的原始方法。研究表明,S蛋白变体与ACE2结合亲和力的变化是模拟与病毒进化相关的波的衰减和激活周期的关键指标,如2024年在菌株j .1中观察到的那样。该混合模型描述了与冠状病毒突变格局扰动相关的流行波形式的事件驱动转换,现在可以通过监测突变和菌株发生的频率来建立。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Hybrid Models of Evolutionary Transformations of SAR-CoV-2 Epidemic Waves

Hybrid Models of Evolutionary Transformations of SAR-CoV-2 Epidemic Waves

The specific variants of the development of the current epidemic situation due to regularly updated SAR-CoV-2 strains are analyzed and methods for modeling special scenarios of the spread of this infection are compared. The relevance of the development of the modeling methodology is due to the renewed growth of waves of COVID cases in a number of regions in 2024 as an unusual variant of the pulsating epidemic process. The latest outbreaks of infections are determined by the activity of the BA.2.86 Pirola strain evolutionary branch, which has managed to split and is more effective in terms of affinity and antibody avoidance than the previously dominant Omicron EG.5 and XBB.1.5 lines. In 2024, the strains maintained sufficient transmissibility with reduced affinity for the ACE2 receptor and a lower replication rate compared to Delta, and at the same time, the virus persistence time increased. In the situation of population immunization, the trend of virus evolution has changed with an emphasis on complicating the phylogenetic tree and selecting Spike protein variants that provide balanced characteristics for replication and antibody avoidance. The potential of variability in coronavirus proteins is clearly not exhausted, and methods for predicting their promising mutations are under development. Methods of computational study of epidemic scenarios based on modified by expanding the set of statuses of individuals in office “SIR models” are discussed. Variants of SIR-based systems of equations do not describe the resumption of COVID waves, which was observed as early as 2020. Status transition schemes are in principle poorly suited for describing nonlinear oscillatory modes of an epidemic, even when second-order oscillatory equations are included in a linear SIR scheme. The models developed by the author for attenuating COVID waves based on equations with delay and threshold effects have been modified to take into account that the new Omicron lines change the modes of oscillations. The changes in oscillation modes that we have identified with an increase in repeated cases are not described only by rearranging the parameters of the equations with damping functions. According to the observed epidemic schedules of COVID waves, a restructuring of regulatory functions is required in the models. It is proposed to model aspects of the transitional phases of the modern epidemic by special computational means, based on the nature of nonlinear oscillations. An original method of forming a structure for a hybrid model based on a set of right-hand sides of differential equations with heterogeneous parameters of delayed regulation generating relaxation oscillations and redefined predicates in violation of the criterion of truth is substantiated. It has been shown that the change in the binding affinity of S protein variants with ACE2 is a key indicator for modeling the periods of attenuation and activation of waves associated with the evolution of the virus, as observed in 2024 in strain JN.1. The hybrid model describes the event-driven transformations of the form of epidemic waves associated with the disturbance of the coronavirus mutation landscape, which can now be established by monitoring mutations and the frequency of occurrence of strains.

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来源期刊
Biophysics
Biophysics Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
1.20
自引率
0.00%
发文量
67
期刊介绍: Biophysics is a multidisciplinary international peer reviewed journal that covers a wide scope of problems related to the main physical mechanisms of processes taking place at different organization levels in biosystems. It includes structure and dynamics of macromolecules, cells and tissues; the influence of environment; energy transformation and transfer; thermodynamics; biological motility; population dynamics and cell differentiation modeling; biomechanics and tissue rheology; nonlinear phenomena, mathematical and cybernetics modeling of complex systems; and computational biology. The journal publishes short communications devoted and review articles.
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