Application of the ARIMA model on the COVID-2019 epidemic dataset

Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. H...

Full description

Saved in:
Bibliographic Details
Published inData in brief Vol. 29; p. 105340
Main Authors Benvenuto, Domenico, Giovanetti, Marta, Vassallo, Lazzaro, Angeletti, Silvia, Ciccozzi, Massimo
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Inc 01.04.2020
Elsevier
Subjects
ARIMA model
COVID-19 infection
COVID-2019 epidemic
data collection
econometric models
evolution
Forecast
Immunology and Microbiology
Infection control
prediction
ARIMA model
COVID-2019 epidemic
Forecast
Infection control
Online AccessGet full text

Cover

More Information
Summary:Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. Here, we propose a simple econometric model that could be useful to predict the spread of COVID-2019. We performed Auto Regressive Integrated Moving Average (ARIMA) model prediction on the Johns Hopkins epidemiological data to predict the epidemiological trend of the prevalence and incidence of COVID-2019. For further comparison or for future perspective, case definition and data collection have to be maintained in real time.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
These authors contributed equally to this article.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2020.105340