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

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: COVID-19; Excess demand; Forecasting; Lockdown; Pandemic.

Fig. 1

An example of COVID-19 cases and a fitted smooth curve (USA).

Fig. 2

Clusters of Countries at different points of time.

Fig. 3

The impact of Lockdown in Germany: excess demand for products due to the pandemic.

Fig. 4

The impact of alternative Lockdown decisions in excess demand for Groceries in Germany.

Fig. 5

The impact of alternative Lockdown decisions in excess demand for Groceries in India.

Fig. 6

The impact of alternative Lockdown decisions in excess demand for Groceries in UK.

Fig. 7

The impact of alternative Lockdown decisions in excess demand for Groceries in US.

Fig. 8

The impact of alternative Lockdown decisions in excess demand for Groceries in Singapore.