Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions

Konstantinos Nikolopoulos (), Sushil Punia, Andreas Schäfers, Christos Tsinopoulos and Chrysovalantis Vasilakis

European Journal of Operational Research, 2021, vol. 290, issue 1, 99-115

Abstract: Policymakers during COVID-19 operate in uncharted territory and must make tough decisions. Operational Research – the ubiquitous ‘science of better’ – plays a vital role in supporting this decision-making process. To that end, using data from the USA, India, UK, Germany, and Singapore up to mid-April 2020, we provide predictive analytics tools for forecasting and planning during a pandemic. We forecast COVID-19 growth rates with statistical, epidemiological, machine- and deep-learning models, and a new hybrid forecasting method based on nearest neighbors and clustering. We further model and forecast the excess demand for products and services during the pandemic using auxiliary data (google trends) and simulating governmental decisions (lockdown). Our empirical results can immediately help policymakers and planners make better decisions during the ongoing and future pandemics.

Keywords: Forecasting; COVID-19; Pandemic; Excess demand; Lockdown (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (65)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:290:y:2021:i:1:p:99-115

DOI: 10.1016/j.ejor.2020.08.001

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