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. 2020 Feb 26:29:105340.
doi: 10.1016/j.dib.2020.105340. eCollection 2020 Apr.

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

Domenico Benvenuto  1 , Marta Giovanetti  2 , Lazzaro Vassallo  3 , Silvia Angeletti  4 , Massimo Ciccozzi  2
Affiliations

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

Domenico Benvenuto et al. Data Brief. .

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: ARIMA model; COVID-2019 epidemic; Forecast; Infection control.

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Figures

Fig. 1
Fig. 1
Correlogram and ARIMA forecast graph for the 2019-nCoV prevalence.
Fig. 2
Fig. 2
Correlogram and ARIMA forecast graph for the 2019-nCoV incidence.
See this image and copyright information in PMC

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