Covid-19感染和波的理论和参数化:一项6国数据分析

H. Nieto-Chaupis
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引用次数: 2

摘要

从美国、日本、德国、英国、意大利和俄罗斯的数据来看,由冠状病毒动态决定的全球大流行表现出与贝塞尔样形态相对应的分布。在假定大流行包含以病毒传播速度和加速度表示的感染阶段的前提下,提出了由整阶贝塞尔函数给出的多项式模型。这些多项式进入统计方法,以确定感染规律作为持续全球大流行的时间函数。据此,根据近几个月至2021年8月的不同阶段(包括Delta变量)来解释数据演变及其不同行为。
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Theory and Parameterization of Infections and Waves by Covid-19: A 6-Countries Data Analysis
From data of USA, Japan, Germany, UK, Italy and Russian, it is claimed that the Global pandemic dictated by the dynamics of Corona virus exhibits distributions that would correspond to a morphology of Bessel-like type. Under the assumption that the pandemic contains phases of infection denoted by the velocity and acceleration of propagation of virus, then a model of polynomials given by the integer-order Bessel functions is proposed. These polynomials enter in a statistical approach to define the law of infections as function of time for the ongoing global pandemic. From this, the data evolution and their different behaviors are interpreted in terms of the different phases including the Delta variant for the recent months until August 2021.
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