Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)
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 th...
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GJESM Publisher
2020-08-01
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| Series: | Global Journal of Environmental Science and Management |
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| Online Access: | https://www.gjesm.net/article_39687_f9da19cb04c9cc2776cd691f2f2fa756.pdf |
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| author | T.T. Tran L.T. Pham Q.X. Ngo |
| author_facet | T.T. Tran L.T. Pham Q.X. Ngo |
| author_sort | T.T. Tran |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-81dbc9b8fdf9466c93c698dab5d81957 |
| institution | Kabale University |
| issn | 2383-3572 2383-3866 |
| language | English |
| publishDate | 2020-08-01 |
| publisher | GJESM Publisher |
| record_format | Article |
| series | Global Journal of Environmental Science and Management |
| spelling | doaj-art-81dbc9b8fdf9466c93c698dab5d819572025-02-02T16:40:54ZengGJESM PublisherGlobal Journal of Environmental Science and Management2383-35722383-38662020-08-016Special Issue (Covid-19)11010.22034/GJESM.2019.06.SI.0139687Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran)T.T. Tran0L.T. Pham1Q.X. Ngo2Institute of Tropical Biology, Vietnam Academy of Science and Technology, Ho Chi Minh City 700000, VietnamInstitute of Tropical Biology, Vietnam Academy of Science and Technology, Ho Chi Minh City 700000, Vietnam|Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi 100000, VietnamInstitute of Tropical Biology, Vietnam Academy of Science and Technology, Ho Chi Minh City 700000, Vietnam|Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi 100000, VietnamCurrently, 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.https://www.gjesm.net/article_39687_f9da19cb04c9cc2776cd691f2f2fa756.pdfauto-regressive integrated moving average (arima)covid-19 (coronavirus)epidemiciranprediction |
| spellingShingle | T.T. Tran L.T. Pham Q.X. Ngo Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) Global Journal of Environmental Science and Management auto-regressive integrated moving average (arima) covid-19 (coronavirus) epidemic iran prediction |
| title | Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) |
| title_full | Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) |
| title_fullStr | Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) |
| title_full_unstemmed | Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) |
| title_short | Forecasting epidemic spread of SARS-CoV-2 using ARIMA model (Case study: Iran) |
| title_sort | forecasting epidemic spread of sars cov 2 using arima model case study iran |
| topic | auto-regressive integrated moving average (arima) covid-19 (coronavirus) epidemic iran prediction |
| url | https://www.gjesm.net/article_39687_f9da19cb04c9cc2776cd691f2f2fa756.pdf |
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