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

Identifieur interne : 000408 ( PubMed/Curation ); précédent : 000407; suivant : 000409

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

Auteurs : Domenico Benvenuto [Italie] ; Marta Giovanetti [Brésil] ; Lazzaro Vassallo [Italie] ; Silvia Angeletti [Italie] ; Massimo Ciccozzi [Brésil]

Source :

Data in brief [ 2352-3409 ] ; 2020.

RBID : pubmed:32181302

Abstract

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.

DOI: 10.1016/j.dib.2020.105340
PubMed: 32181302

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

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

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Abstract

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