TY - JOUR
T1 - Dynamics models for identifying the key transmission parameters of the COVID-19 disease
AU - Shahzad, Muhammad
AU - Abdel-Aty, Abdel Haleem
AU - Attia, Raghda A.M.
AU - Khoshnaw, Sarbaz H.A.
AU - Aldila, Dipo
AU - Ali, Mehboob
AU - Sultan, Faisal
N1 - Funding Information:
The authors extend their appreciation to the Deanship of Scientific Research at the University of Bisha, Saudi Arabia for funding this work through the COVID-19 Initiative Project under Grant Number (UB-COVID-31-1441).
Publisher Copyright:
© 2020 Faculty of Engineering, Alexandria University
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/2
Y1 - 2021/2
N2 - After the analysis and forecast of COVID-19 spreading in China, Italy, and France the WHO has declared the COVID-19 a pandemic. There are around 100 research groups across the world trying to develop a vaccine for this coronavirus. Therefore, the quantitative and qualitative analysis of the COVID–19 pandemic is needed along with the effect of rapid test infection identification on controlling the spread of COVID-19. Mathematical models with computational simulations are the effective tools that help global efforts to estimate key transmission parameters and further improvements for controlling this disease. This is an infectious disease and can be modeled as a system of non-linear differential equations with reaction rates. In this paper, we develop the models for coronavirus disease at different stages with the addition of more parameters due to interactions among the individuals. Then, some key computational simulations and sensitivity analysis are investigated. Further, the local sensitivities for each model state concerning the model parameters are computed using the model reduction techniques: the dynamical models are eventually changed with the change of parameters are represented graphically.
AB - After the analysis and forecast of COVID-19 spreading in China, Italy, and France the WHO has declared the COVID-19 a pandemic. There are around 100 research groups across the world trying to develop a vaccine for this coronavirus. Therefore, the quantitative and qualitative analysis of the COVID–19 pandemic is needed along with the effect of rapid test infection identification on controlling the spread of COVID-19. Mathematical models with computational simulations are the effective tools that help global efforts to estimate key transmission parameters and further improvements for controlling this disease. This is an infectious disease and can be modeled as a system of non-linear differential equations with reaction rates. In this paper, we develop the models for coronavirus disease at different stages with the addition of more parameters due to interactions among the individuals. Then, some key computational simulations and sensitivity analysis are investigated. Further, the local sensitivities for each model state concerning the model parameters are computed using the model reduction techniques: the dynamical models are eventually changed with the change of parameters are represented graphically.
KW - COVID-19 outbreak
KW - Reduction
KW - Sensitivity-analysis
KW - Simulations techniques
UR - http://www.scopus.com/inward/record.url?scp=85094098926&partnerID=8YFLogxK
U2 - 10.1016/j.aej.2020.10.006
DO - 10.1016/j.aej.2020.10.006
M3 - Article
AN - SCOPUS:85094098926
SN - 1110-0168
VL - 60
SP - 757
EP - 765
JO - AEJ - Alexandria Engineering Journal
JF - AEJ - Alexandria Engineering Journal
IS - 1
ER -
