Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12252
Title: Analysis of Covid 19 disease with SIR model and Taylor matrix method
Authors: Uçar, Deniz
Çelik, Elçin
Uşak Üniversitesi
01. Izmir Institute of Technology
Keywords: Collocation points
COVID-19
Nonlinear differential equation
Taylor polynomials
Issue Date: 2022
Publisher: American Institute of Mathematical Sciences
Abstract: Covid 19 emerged in Wuhan, China in December 2019 has continued to spread by affecting the whole world. The pandemic has affected over 328 million people with more than 5 million deaths in over 200 countries which has severely disrupted the healthcare system and halted economies of the countries. The aim of this study is to discuss the numerical solution of the SIR model on the spread of Covid 19 by the Taylor matrix and collocation method for Turkey. Predicting COVID-19 through appropriate models can help us to understand the potential spread in the population so that appropriate action can be taken to prevent further transmission and prepare health systems for medical management of the disease. We deal with Susceptible–Infected–Recovered (SIR) model. One of the proposed model’s improvements is to reflect the societal feedback on the disease and confinement features. We obtain the time dependent rate of transmission of the disease from susceptible β(t) and the rate of recovery from infectious to recovered γ using Turkey epidemic data. We apply the Taylor matrix and collocation method to the SIR model with γ, β(t) and Covid 19 data of Turkey from the date of the first case March 11, 2020 through July 3, 2021. Using this method, we focus on the evolution of the Covid 19 in Turkey. We also show the estimates with the help of graphics and Maple.
URI: https://doi.org/10.3934/math.2022626
https://hdl.handle.net/11147/12252
Appears in Collections:Mathematics / Matematik
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
10.3934_math.2022626.pdfArticle245.87 kBAdobe PDFView/Open
Show full item record



CORE Recommender

SCOPUSTM   
Citations

2
checked on Feb 16, 2024

WEB OF SCIENCETM
Citations

2
checked on Feb 10, 2024

Page view(s)

15,012
checked on Feb 19, 2024

Download(s)

114
checked on Feb 19, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.