CovidV2, new, Analysis, bibRecord, 000641

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

Identifieur interne : 000641 ( new/Analysis ); précédent : 000640; suivant : 000642

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 : PMC:7063124

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.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063124

DOI: 10.1016/j.dib.2020.105340
PubMed: 32181302
PubMed Central: 7063124

Affiliations:

Links to Exploration step

PMC:7063124

Le document en format XML

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<author><name sortKey="Aman, Z" uniqKey="Aman Z">Z. Aman</name>
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<author><name sortKey="El Moussami, H" uniqKey="El Moussami H">H. El Moussami</name>
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<author><name sortKey="Tse, L A" uniqKey="Tse L">L.A. Tse</name>
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<author><name sortKey="Kim, J H" uniqKey="Kim J">J.H. Kim</name>
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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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