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A systematic approach for COVID-19 predictions and parameter estimation
Personal and Ubiquitous Computing ( IF 3.006 ) Pub Date : 2020-11-06 , DOI: 10.1007/s00779-020-01462-8
Vishal Srivastava 1 , Smriti Srivastava 1 , Gopal Chaudhary 2 , Fadi Al-Turjman 3
Affiliation  

The world is currently facing a pandemic called COVID-19 which has drastically changed our human lifestyle, affecting it badly. The lifestyle and the thought processes of every individual have changed with the current situation. This situation was unpredictable, and it contains a lot of uncertainties. In this paper, the authors have attempted to predict and analyze the disease along with its related issues to determine the maximum number of infected people, the speed of spread, and most importantly, its evaluation using a model-based parameter estimation method. In this research the Susceptible-Infectious-Recovered model with different conditions has been used for the analysis of COVID-19. The effects of lockdown, the light switch method, and parameter variations like contact ratio and reproduction number are also analyzed. The authors have attempted to study and predict the lockdown effect, particularly in India in terms of infected and recovered numbers, which show substantial improvement. A disease-free endemic stability analysis using Lyapunov and LaSalle’s method is presented, and novel methods such as the convalescent plasma method and the Who Acquires Infection From Whom method are also discussed, as they are considered to be useful in flattening the curve of COVID-19.



中文翻译:

COVID-19 预测和参数估计的系统方法

世界目前正面临一种名为 COVID-19 的大流行,它极大地改变了我们人类的生活方式,并对其造成严重影响。每个人的生活方式和思维过程都随着当前形势而改变。这种情况是不可预测的,并且包含着很多的不确定性。在本文中,作者尝试预测和分析该疾病及其相关问题,以确定最大感染人数、传播速度,最重要的是,使用基于模型的参数估计方法对其进行评估。在本研究中,不同条件下的易感-感染-恢复模型已用于分析 COVID-19。还分析了锁定、灯开关方法以及接触比和繁殖数等参数变化的影响。作者试图研究和预测封锁效果,特别是在印度的感染和康复人数方面,这显示出显着的改善。提出了使用 Lyapunov 和 LaSalle 方法进行的无病流行稳定性分析,还讨论了恢复期血浆法和谁从谁获得感染方法等新方法,因为它们被认为有助于拉平 COVID-19 的曲线。 19.

更新日期:2020-11-06
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