期刊
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
卷 70, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.bspc.2021.102999
关键词
Basis function; COVID-19; Linear parameter varying (LPV) model; Pandemic; Quarantine; Social distancing; Stability analysis; SARS-CoV-2
This paper proposes a conceptual model for the COVID-19 pandemic, using real data and solving linear least square problems to obtain parameters that are updated in real-time. The system behavior is modeled according to the changes in parameters, and the impact of social distancing and quarantine on severe infection and hospitalization numbers is studied.
Current outbreaks of the COIVD-19 pandemic demonstrate a global threat. In this paper, a conceptual model is developed for the COVID-19 pandemic, in which the people in society are divided into Susceptible, Exposed, Minor infected (Those who need to be quarantined at home), Hospitalized (Those who are in need of hospitalization), Intensive infected (ventilator-in-need infected), Recovered and Deceased. In this paper, first, the model that is briefly called SEMHIRD for a sample country (Italy as an example) is considered. Then, exploiting the real data of the country, the parameters of the model are obtained by assuming some basis functions on the collected data and solving linear least square problems in each window of data to estimate the time-varying parameters of the model. Thus, the parameters are updated every few days, and the system behavior is modeled according to the changes in the parameters. Then, the Linear Parameter Varying (LPV) Model of COVID19 is derived, and its stability analysis is presented. In the end, the influence of different levels of social distancing and quarantine on the variation of severely infected and hospitalized people is studied.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据