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

Abstract Policymakers during 1 1 We conducted this research in April-June 2020 during the COVID-19 pandemic. The aim is to provide tools for immediate use during the pandemic: desperate times call for desperate academic measures, and as such this is our direct response to inform practice. We employ a phenomenon-based research methodological approach, engaging in an early phase of a scientific inquiry, observing, researching, and providing solutions for a developing and novel phenomenon. COVID-19 operate in uncharted 2 2 Opinions expressed are solely my own and do not express the views or opinions of my previous or current employers. 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.