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

Nikolopoulos, Konstantinos; Punia, Sushil; Schäfers, Andreas; Tsinopoulos, Christos; Vasilakis, Chrysovalantis

Abstract

Policymakers during 1COVID-19 operate in uncharted 2territory 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.

Citation

Nikolopoulos, K., Punia, S., Schäfers, A., Tsinopoulos, C., & Vasilakis, C. (2020). Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. European Journal of Operational Research, 290(1), 99-115. https://doi.org/10.1016/j.ejor.2020.08.001

• Journal Article Type: Article
• Acceptance Date: Aug 3, 2020
• Online Publication Date: Aug 8, 2020
• Publication Date: 2020
• Deposit Date: Aug 4, 2020
• Publicly Available Date: Aug 8, 2022
• Journal: European Journal of Operational Research
• Print ISSN: 0377-2217
• Electronic ISSN: 1872-6860
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 290
• Issue: 1
• Pages: 99-115
• DOI: https://doi.org/10.1016/j.ejor.2020.08.001
• Public URL: https://durham-repository.worktribe.com/output/1295464