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新型冠状病毒2(SARS-CoV-2)感染、生存及检测努力变量的行为:基于优化技术的理论建模

The behaviour of infection, survival and testing effort variables of SARS-CoV-2: A theoretical modelling based on optimization technique.

作者信息

Bhattacharya Subhasis, Paul Suman

机构信息

Department of Economics, Sidho-Kanho-Birsha University, Purulia, West Bengal, India.

Department of Geography, Sidho-Kanho-Birsha University, Purulia, West Bengal, India.

出版信息

Results Phys. 2020 Dec;19:103568. doi: 10.1016/j.rinp.2020.103568. Epub 2020 Nov 11.

Abstract

BACKGROUND

The experiences of SARS-CoV-2 are different in nature among the different states of the world. Studies on survival analysis of such pandemic mainly based on differential equation analysis, but the main limitation of such models is non-universal applicability. Consideration of improper functional relation in case of identification, survival and testing effort variables of the disease may be the cause of such non-universal applicability.

METHODS

Present study using optimization techniques try to find the general functional form for the variables like identification of the carrier's and testing effort. The study uses both the discrete and continuous time procedure of optimization technique. The main objective of the study is to institute relation between the identified carrier's and effort taken for identification.

RESULTS

The study considers test as the pseudo variable for effort of identification. The study found that the relationship between test and identified is not a linear one, rather it is nonlinear quadratic type. The study does not go for using data driven methods to verify the results.

摘要

背景

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)在世界不同国家的情况本质上有所不同。关于此类大流行的生存分析研究主要基于微分方程分析,但此类模型的主要局限性在于缺乏普遍适用性。在确定疾病的携带者、生存情况和检测力度变量时考虑不适当的函数关系可能是导致这种缺乏普遍适用性的原因。

方法

本研究使用优化技术试图找到诸如携带者识别和检测力度等变量的一般函数形式。该研究使用了优化技术的离散和连续时间程序。该研究的主要目的是建立已识别携带者与识别所付出努力之间的关系。

结果

该研究将检测视为识别努力的伪变量。研究发现检测与已识别者之间的关系不是线性的,而是非线性二次型的。该研究未采用数据驱动方法来验证结果。

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