Forecasting Long-term trends of the COVID-19 outbreak in Yazd with an SVIR model

Akrami, Mohammad Hossein; Ayatollahi, Jamshid; Sharifyazdi, Mohammad; Mosavi Anari, Seyed Alireza; Akhoundi Meybodi, Zohreh; Heydari, Faezeh

doi:10.22080/cjms.2024.27099.1694

Forecasting Long-term trends of the COVID-19 outbreak in Yazd with an SVIR model

Document Type : Research Articles

Authors

¹ Department of Mathematical Science, Yazd University, Yazd, Iran

² Infectious Diseases Research Center, Shahid Sadoughi Hospital, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

10.22080/cjms.2024.27099.1694

Abstract

‎This article examines the transmission of COVID-19 from a mathematical model perspective‎, ‎analyzing its spread pattern‎. ‎Given the virus's adherence to standard epidemic disease transmission principles and the effectiveness of vaccination in mitigating and controlling its spread‎, ‎we employ the SVIR model to demonstrate the disease's progression in Yazd‎. ‎The data used in this study was provided by the medical care monitoring center of Yazd Shahid Sadoughi University of Medical Sciences‎, ‎Yazd‎, ‎Iran‎, ‎for 770 days between September 27‎, ‎2020 to November 5‎, ‎2022‎. To establish thelparameters‎, ‎we utilized the genetic algorithm (GA) to minimize the cost function between the model's prediction and the real data‎.‎Additionally‎, ‎we conducted our simulations using Matlab software‎. ‎Identifying the factors that contribute to the spread of the virus through mathematical modeling can be a crucial step towards controlling the disease‎, ‎given its catastrophic impact on the economy‎, ‎society‎, ‎and health‎.

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