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Akrami, Mohammad Hossein, Ayatollahi, Jamshid, Sharifyazdi, Mohammad, Mosavi Anari, Seyed Alireza, Akhoundi Meybodi, Zohreh, Heydari, Faezeh. (1403). Forecasting long-term trends of the COVID-19 outbreak in Yazd with an SVIR model. پژوهشنامه مدیریت اجرایی, 13(2), 296-310. doi: 10.22080/cjms.2024.27099.1694
Mohammad Hossein Akrami; Jamshid Ayatollahi; Mohammad Sharifyazdi; Seyed Alireza Mosavi Anari; Zohreh Akhoundi Meybodi; Faezeh Heydari. "Forecasting long-term trends of the COVID-19 outbreak in Yazd with an SVIR model". پژوهشنامه مدیریت اجرایی, 13, 2, 1403, 296-310. doi: 10.22080/cjms.2024.27099.1694
Akrami, Mohammad Hossein, Ayatollahi, Jamshid, Sharifyazdi, Mohammad, Mosavi Anari, Seyed Alireza, Akhoundi Meybodi, Zohreh, Heydari, Faezeh. (1403). 'Forecasting long-term trends of the COVID-19 outbreak in Yazd with an SVIR model', پژوهشنامه مدیریت اجرایی, 13(2), pp. 296-310. doi: 10.22080/cjms.2024.27099.1694
Akrami, Mohammad Hossein, Ayatollahi, Jamshid, Sharifyazdi, Mohammad, Mosavi Anari, Seyed Alireza, Akhoundi Meybodi, Zohreh, Heydari, Faezeh. Forecasting long-term trends of the COVID-19 outbreak in Yazd with an SVIR model. پژوهشنامه مدیریت اجرایی, 1403; 13(2): 296-310. doi: 10.22080/cjms.2024.27099.1694

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

Caspian Journal of Mathematical Sciences
دوره 13، شماره 2 - شماره پیاپی 26، 2024، صفحه 296-310    اصل مقاله (414.31 K)
نوع مقاله: Research Articles
شناسه دیجیتال (DOI): 10.22080/cjms.2024.27099.1694
نویسندگان
Mohammad Hossein Akrami* 1؛ Jamshid Ayatollahi2؛ Mohammad Sharifyazdi2؛ Seyed Alireza Mosavi Anari2؛ Zohreh Akhoundi Meybodi2؛ Faezeh Heydari2
1Department of Mathematical Science, Yazd University, Yazd, Iran
2Infectious Diseases Research Center, Shahid Sadoughi Hospital, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
تاریخ دریافت: 19 اردیبهشت 1403،  تاریخ بازنگری: 07 مرداد 1403،  تاریخ پذیرش: 09 مرداد 1403 
چکیده
‎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.
کلیدواژه‌ها
Epidemic mode؛ SVIR؛ Public health؛ Pandemic؛ COVID-19
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