ARIMA-based forecasting of the dynamics of confirmed Covid-19 cases for selected European countries

Tadeusz Kufel ()

Equilibrium. Quarterly Journal of Economics and Economic Policy, 2020, vol. 15, issue 2, 181-204

Abstract: Research background: On 11 March 2020, the Covid-19 epidemic was identified by the World Health Organization (WHO) as a global pandemic. The rapid increase in the scale of the epidemic has led to the introduction of non-pharmaceutical countermeasures. Forecast of the Covid-19 prevalence is an essential element in the actions undertaken by authorities. Purpose of the article: The article aims to assess the usefulness of the Auto-regressive Integrated Moving Average (ARIMA) model for predicting the dynamics of Covid-19 incidence at different stages of the epidemic, from the first phase of growth, to the maximum daily incidence, until the phase of the epidemic's extinction. Methods: ARIMA(p,d,q) models are used to predict the dynamics of virus distribution in many diseases. Model estimates, forecasts, and the accuracy of forecasts are presented in this paper. Findings & Value added: Using the ARIMA(1,2,0) model for forecasting the dynamics of Covid-19 cases in each stage of the epidemic is a way of evaluating the implemented non-pharmaceutical countermeasures on the dynamics of the epidemic.

Keywords: Covid-19 epidemic; ARIMA model; forecasting; infection control; non-pharmaceutical intervention (search for similar items in EconPapers)
JEL-codes: C22 C53 C82 I12 I18 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:pes:ierequ:v:15:y:2020:i:2:p:181-204

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