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APPLICATION OF THE ARIMA MODEL ON THE COVID-2019 EPIDEMIC DATASET
Benvenuto, Domenico et al. | Date Issued: 2020
Author
Benvenuto, Domenico
Giovanetti, Marta
Vassallo, Lazzaro
Angeletti, Silvia
Ciccozzi, Massimo
Affilliation
University Campus Bio-Medico of Rome. Unit of Medical Statistics and Molecular Epidemiology. Rome, Italy.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brasil.
University of Salerno. Department of Financial and Statistical Sciences. Salerno, Italy.
University Campus Bio-Medico of Rome. Unit of Clinical Laboratory Science. Rome, Italy.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brasil.
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.
Keywords in Portuguese
Epidemia
Modelo ARIMA
Controle de infecção
Previsão
COVID-19
Coronavírus
 
Keywords
Epidemic
ARIMA model
Forecast
Infection control
COVID-19
Coronavirus
 
Publisher
Elsevier
Citation
BENVENUTO, Domenico et al. Application of the ARIMA model on the COVID-2019 epidemic dataset. Data in Brief, v. 29, p. 1-5, 2020.
DOI
10.1016/j.dib.2020.105340
ISSN
2352-3409
Notes
Since 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.