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

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.

Cited by papers we hold 3

• AnalysingCOVID-19Verified,RecuperateandDeathCasesin Ethiopia Using ARIMA Models · 2022
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• Impact of COVID-19 outbreaks and interventions on influenza in China and the United States · 2021
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• A bivariate prediction approach for adapting the health care system response to the spread of COVID-19. · 2020
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