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关于新冠病毒感染人群的进化模型:以新西兰为例。

On evolution model for SARS-Cov-2-infected population: the case of New Zealand.

作者信息

Khmaladze Estate, Kvizhinadze Giorgi

机构信息

Victoria University of Wellington, Wellington, New Zealand.

Capital and Coast District Health Board, Wellington, New Zealand.

出版信息

J Appl Stat. 2021 Nov 29;50(11-12):2435-2449. doi: 10.1080/02664763.2021.2006153. eCollection 2023.

Abstract

The work proposes a mathematical model of the process of COVID-19 epidemic as it evolved in New Zealand. The model uses a system of differential equations which emanate from natural assumptions on some probability measure and evolution of this measure on evolving family of simplexes. The authors tried to create the model which, at one hand, is simple and easy to follow. and, at the other hand, reflects the observed epidemic process correctly. The practical aim was to come to justifiable estimations of important parameters like the rate of infection as function of time, thus quantifying effectiveness of the Government measures. Another parameters estimated were the probability distribution of detection times and recovery times.

摘要

这项工作提出了一个关于新冠疫情在新西兰演变过程的数学模型。该模型使用了一个微分方程组,这些方程源自对某种概率测度以及该测度在不断演变的单纯形族上的演化的自然假设。作者试图创建一个一方面简单易懂,另一方面又能正确反映观察到的疫情过程的模型。实际目标是对诸如感染率随时间变化等重要参数进行合理估计,从而量化政府措施的有效性。估计的其他参数包括检测时间和康复时间的概率分布。

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Editorial to the special issue: statistical perspectives on analytics for COVID-19 data.特刊社论:关于COVID-19数据分析的统计学视角
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