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COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions

COVID-19 has now taken a frightening form. As the days pass, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions. If the same situation persists over time, the day is not fa...

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Autores principales: Chaurasia, Vikas, Pal, Saurabh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456206/
https://www.ncbi.nlm.nih.gov/pubmed/33063056
http://dx.doi.org/10.1007/s42979-020-00298-6
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author Chaurasia, Vikas
Pal, Saurabh
author_facet Chaurasia, Vikas
Pal, Saurabh
author_sort Chaurasia, Vikas
collection PubMed
description COVID-19 has now taken a frightening form. As the days pass, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions. If the same situation persists over time, the day is not far when the humanity of all the countries on the globe will be endangered and we yearn for breath. From January 2020 till now, many scientists, researchers and doctors have been trying to solve this complex problem so that proper arrangements can be made by the governments in the hospitals and the death rate can be reduced. The presented research article shows the estimated mortality rate by the ARIMA model and the regression model. This dataset has been collected precisely from DataHub-Novel Coronavirus 2019-Dataset from 22nd January to 29th June 2020. To show the current mortality rate of the entire subject, the correlation coefficients of attributes (MAE, MSE, RMSE and MAPE) were used, where the average absolute percentage error validated the model by 99.09%. The ARIMA model is used to generate auto_arima SARIMAX results, auto_arima residual plots, ARIMA model results, and corresponding prediction plots on the training dataset. These data indicate a continuous decline in death cases. By applying a regression model, the coefficients generated by the regression model are estimated, and the actual death cases and expected death cases are compared and analyzed. It is found that the predicted mortality rate has decreased after May 2, 2020. It will help the government and doctors prepare for the forthcoming plans. Based on short-period predictions, these methods can be used to forecast the mortality rate for a long period.
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spelling pubmed-74562062020-08-31 COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions Chaurasia, Vikas Pal, Saurabh SN Comput Sci Original Research COVID-19 has now taken a frightening form. As the days pass, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions. If the same situation persists over time, the day is not far when the humanity of all the countries on the globe will be endangered and we yearn for breath. From January 2020 till now, many scientists, researchers and doctors have been trying to solve this complex problem so that proper arrangements can be made by the governments in the hospitals and the death rate can be reduced. The presented research article shows the estimated mortality rate by the ARIMA model and the regression model. This dataset has been collected precisely from DataHub-Novel Coronavirus 2019-Dataset from 22nd January to 29th June 2020. To show the current mortality rate of the entire subject, the correlation coefficients of attributes (MAE, MSE, RMSE and MAPE) were used, where the average absolute percentage error validated the model by 99.09%. The ARIMA model is used to generate auto_arima SARIMAX results, auto_arima residual plots, ARIMA model results, and corresponding prediction plots on the training dataset. These data indicate a continuous decline in death cases. By applying a regression model, the coefficients generated by the regression model are estimated, and the actual death cases and expected death cases are compared and analyzed. It is found that the predicted mortality rate has decreased after May 2, 2020. It will help the government and doctors prepare for the forthcoming plans. Based on short-period predictions, these methods can be used to forecast the mortality rate for a long period. Springer Singapore 2020-08-29 2020 /pmc/articles/PMC7456206/ /pubmed/33063056 http://dx.doi.org/10.1007/s42979-020-00298-6 Text en © Springer Nature Singapore Pte Ltd 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Chaurasia, Vikas
Pal, Saurabh
COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title_full COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title_fullStr COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title_full_unstemmed COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title_short COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions
title_sort covid-19 pandemic: arima and regression model-based worldwide death cases predictions
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456206/
https://www.ncbi.nlm.nih.gov/pubmed/33063056
http://dx.doi.org/10.1007/s42979-020-00298-6
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