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

dc.creatorBenvenuto, Domenico
dc.creatorGiovanetti, Marta
dc.creatorVassallo, Lazzaro
dc.creatorAngeletti, Silvia
dc.creatorCiccozzi, Massimo
dc.date2020-04-15T20:18:58Z
dc.date2020-04-15T20:18:58Z
dc.date2020
dc.date.accessioned2023-09-26T20:56:27Z
dc.date.available2023-09-26T20:56:27Z
dc.identifierBENVENUTO, Domenico et al. Application of the ARIMA model on the COVID-2019 epidemic dataset. Data in Brief, v. 29, p. 1-5, 2020.
dc.identifier2352-3409
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/40791
dc.identifier10.1016/j.dib.2020.105340
dc.identifier10.1016/j.dib.2020.105340
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8866520
dc.descriptionSince January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
dc.descriptionCoronavirus 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.
dc.formatapplication/pdf
dc.languageeng
dc.publisherElsevier
dc.rightsopen access
dc.subjectEpidemia
dc.subjectModelo ARIMA
dc.subjectControle de infecção
dc.subjectPrevisão
dc.subjectCOVID-19
dc.subjectCoronavírus
dc.subjectEpidemic
dc.subjectARIMA model
dc.subjectForecast
dc.subjectInfection control
dc.subjectCOVID-19
dc.subjectCoronavirus
dc.titleApplication of the ARIMA model on the COVID-2019 epidemic dataset
dc.typeArticle


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