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

Authors :
UCL - SSH/LIDAM/IRES - Institut de recherches économiques et sociales
Nikolopoulos, Konstantinos
Punia, Sushil
Schäfers, Andreas
Tsinopoulos, Christos
Vasilakis, Chrysovalantis
UCL - SSH/LIDAM/IRES - Institut de recherches économiques et sociales
Nikolopoulos, Konstantinos
Punia, Sushil
Schäfers, Andreas
Tsinopoulos, Christos
Vasilakis, Chrysovalantis
Source :
European Journal of Operational Research, Vol. 290, no.1, p. 99-115 (2021)
Publication Year :
2021

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.

Details

Database :
OAIster
Journal :
European Journal of Operational Research, Vol. 290, no.1, p. 99-115 (2021)
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1288278361
Document Type :
Electronic Resource