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使用改进的SIRD模型分析新冠肺炎数据。

Use of a Modified SIRD Model to Analyze COVID-19 Data.

作者信息

Sen Devosmita, Sen Debasis

机构信息

Department of Chemical Engineering, Indian Institute of Technology, Bombay, Mumbai 400076, India.

Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400085, India.

出版信息

Ind Eng Chem Res. 2021 Feb 2;60(11):4251-4260. doi: 10.1021/acs.iecr.0c04754. eCollection 2021 Mar 24.

Abstract

Since the starting of the year 2020, the whole world is facing a challenge due to an outbreak of an unprecedented COVID-19 pandemic owing to a novel coronavirus. Here, a modified susceptible-infected-recovered-dead model has been used to analyze the time series data of the pandemic for five countries. It is established that the present model is capable of simultaneously explaining the temporal evolution of active-infected, recovered, and dead population of all these five countries. The key parameters governing the temporal evolution of the spread of this pandemic are estimated and compared.

摘要

自2020年初以来,由于一种新型冠状病毒引发了前所未有的新冠肺炎大流行,全世界都面临着挑战。在此,我们使用了一种改进的易感-感染-康复-死亡模型来分析五个国家大流行的时间序列数据。结果表明,该模型能够同时解释这五个国家活跃感染、康复和死亡人口的时间演变。对控制这种大流行传播时间演变的关键参数进行了估计和比较。

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