Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)

Tran, T.T.; Pham, L.T.; Ngo, Q.X.

doi:10.22034/GJESM.2019.06.SI.01

Document Type : CASE STUDY

Authors

¹ Institute of Tropical Biology, Vietnam Academy of Science and Technology, Ho Chi Minh City 700000, Vietnam

² Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi 100000, Vietnam

https://doi.org/10.22034/GJESM.2019.06.SI.01

Abstract

Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran.

Graphical Abstract

Highlights

This is a pioneering study forecasting the number of daily total deaths/new deaths and growth rate in confirmed cases/deaths in the near future in Iran;
All variables, including the total confirmed cases/new cases, total deaths/new deaths, and growth rate in confirmed cases/deaths, are suitable for the ARIMA model;
The ARIMA model forecasts an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future.

Keywords

Main Subjects

Health, safety and environment (HSE)

Citation Metrics & Captures

Copyrights

©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

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Global Journal of Environmental Science and Management

Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)

References

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Letters to Editor

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Volume 6, Special Issue (Covid-19)
2020
Pages 1-10

Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)

References

References

Letters to Editor

Send comment about this article

Volume 6, Special Issue (Covid-19) 2020Pages 1-10

Volume 6, Special Issue (Covid-19)
2020
Pages 1-10