Tracking Rt of COVID-19 Vaccine Effectiveness Using Kalman Filter and SIRD Model

被引：0
|
作者：
Kaddour, Mahmoud [1 ]
Charafeddine, Jinan [2 ]
Moubayed, Nazih [3 ]
机构：
[1] Jean Barriol Inst, LCP A2MC, Lab Chem & Phys Multiscale Approach Complex Media, Metz, France
[2] Paris Saclay Univ, LISV, Lab Syst Engn Versailles, Velizy Villacoublay, France
[3] Lebanese Univ, LaRGES, CRSI, Fac Engn, Tripoli, Lebanon
来源：
2021 SIXTH INTERNATIONAL CONFERENCE ON ADVANCES IN BIOMEDICAL ENGINEERING (ICABME) | 2021年
关键词：
COVID-19; SIRD model; Kalman filter;
D O I：
10.1109/ICABME53305.2021.9604831
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
In this paper, a SIRD model is adapted to study the vaccine's impact on the spread of coronavirus (COVID19) spread in Lebanon. To describe the epidemic development across the country, a Kalman filter is integrated with the SIRD model in order to estimate the time-varying reproduction number R-t - is the most important indicator that predicts the severity of an epidemic outbreak. R-t denotes the number of healthy persons to whom an infected person can spread the disease. The results show a reduction in the spread of the pandemic after employing the vaccine. All the data and relevant codebase are available at https://www.moph.gov.lb
引用
收藏
页码：151 / 154
页数：4
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