Prediction of peak and termination of novel coronavirus COVID-19 epidemic in Iran

Sepehr Rafieenasab, Amir-Pouyan Zahiri and Ehsan Roohi
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Sepehr Rafieenasab: Department of Mechanical Engineering, Ferdowsi University of Mashhad, P.O.B. 91775-1111 Mashhad, Iran
Amir-Pouyan Zahiri: Department of Mechanical Engineering, Ferdowsi University of Mashhad, P.O.B. 91775-1111 Mashhad, Iran
Ehsan Roohi: Department of Mechanical Engineering, Ferdowsi University of Mashhad, P.O.B. 91775-1111 Mashhad, Iran†State Key Laboratory for Strength and Vibration of Mechanical Structures, International Center for Applied Mechanics (ICAM), School of Aerospace Engineering, Xi’an Jiaotong University (XJTU), Xi’an, P. R. China

International Journal of Modern Physics C (IJMPC), 2020, vol. 31, issue 11, 1-17

Abstract: The growth and development of COVID-19 transmission have significantly attracted the attention of many societies, particularly Iran, that have been struggling with this contagious, infectious disease since late February 2020. In this study, the known “Susceptible-Infectious-Recovered (SIR)” and some other mathematical approaches were used to investigate the dynamics of the COVID-19 epidemic to provide a suitable assessment of the COVID-19 virus epidemic in Iran. The epidemic curve and SIR model parameters were obtained with the use of Iran’s official data. The recovered people were considered alongside the official number of confirmed victims as the reliable long-time statistical data. The results offer important predictions of the COVID-19 virus epidemic such as the realistic number of victims, infection rate, peak time and other characteristics. Besides, the effectiveness of infection and immunization rates to the number of infected people and epidemic end time are reported. Finally, different suggestions for decreasing victims are offered.

Keywords: Model-identification; parameter identification; statistical methods; mathematical modeling of infection diseases; Susceptible-Infectious-Recovered (SIR) model; contamination models (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0129183120501521

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