A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases

Starting February 2020, COVID-19 was confirmed in 11,946 people worldwide, with a mortality rate of almost 2%. A significant number of epidemic diseases consisting of human Coronavirus display patterns. In this study, with the benefit of data analytic, we develop regression models and a Susceptible-...

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Autores principales:	Saina Abolmaali, Samira Shirzaei
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	covid-19 epidemiology sir linear regression logistic function arima Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/c2bd7a78b6c14fdda5fe7006aa92f4b2
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id	oai:doaj.org-article:c2bd7a78b6c14fdda5fe7006aa92f4b2
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spelling	oai:doaj.org-article:c2bd7a78b6c14fdda5fe7006aa92f4b22021-11-30T00:59:37ZA comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases10.3934/publichealth.20210482327-8994https://doaj.org/article/c2bd7a78b6c14fdda5fe7006aa92f4b22021-08-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/publichealth.2021048?viewType=HTMLhttps://doaj.org/toc/2327-8994Starting February 2020, COVID-19 was confirmed in 11,946 people worldwide, with a mortality rate of almost 2%. A significant number of epidemic diseases consisting of human Coronavirus display patterns. In this study, with the benefit of data analytic, we develop regression models and a Susceptible-Infected-Recovered (SIR) model for the contagion to compare the performance of models to predict the number of cases. First, we implement a good understanding of data and perform Exploratory Data Analysis (EDA). Then, we derive parameters of the model from the available data corresponding to the top 4 regions based on the history of infections and the most infected people as of the end of August 2020. Then models are compared, and we recommend further research.Saina Abolmaali Samira Shirzaei AIMS Pressarticlecovid-19epidemiologysirlinear regressionlogistic functionarimaPublic aspects of medicineRA1-1270ENAIMS Public Health, Vol 8, Iss 4, Pp 598-613 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	covid-19 epidemiology sir linear regression logistic function arima Public aspects of medicine RA1-1270
spellingShingle	covid-19 epidemiology sir linear regression logistic function arima Public aspects of medicine RA1-1270 Saina Abolmaali Samira Shirzaei A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
description	Starting February 2020, COVID-19 was confirmed in 11,946 people worldwide, with a mortality rate of almost 2%. A significant number of epidemic diseases consisting of human Coronavirus display patterns. In this study, with the benefit of data analytic, we develop regression models and a Susceptible-Infected-Recovered (SIR) model for the contagion to compare the performance of models to predict the number of cases. First, we implement a good understanding of data and perform Exploratory Data Analysis (EDA). Then, we derive parameters of the model from the available data corresponding to the top 4 regions based on the history of infections and the most infected people as of the end of August 2020. Then models are compared, and we recommend further research.
format	article
author	Saina Abolmaali Samira Shirzaei
author_facet	Saina Abolmaali Samira Shirzaei
author_sort	Saina Abolmaali
title	A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
title_short	A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
title_full	A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
title_fullStr	A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
title_full_unstemmed	A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
title_sort	comparative study of sir model, linear regression, logistic function and arima model for forecasting covid-19 cases
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/c2bd7a78b6c14fdda5fe7006aa92f4b2
work_keys_str_mv	AT sainaabolmaali acomparativestudyofsirmodellinearregressionlogisticfunctionandarimamodelforforecastingcovid19cases AT samirashirzaei acomparativestudyofsirmodellinearregressionlogisticfunctionandarimamodelforforecastingcovid19cases AT sainaabolmaali comparativestudyofsirmodellinearregressionlogisticfunctionandarimamodelforforecastingcovid19cases AT samirashirzaei comparativestudyofsirmodellinearregressionlogisticfunctionandarimamodelforforecastingcovid19cases
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A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases

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