Canary in the Coal Mine: Using Early Data to Aid Policy Makers Manage the Spread of COVID-19 Pandemic

5 Pages Posted: 20 Apr 2020

Date Written: April 10, 2020

Abstract

When would the COVID-19 outbreak peak? What is the transmission-rate? How long will the outbreak last? As the COVID-19 pandemic grows around the world, governments and businesses are interested in the answers to these questions. While sophisticated epidemiological studies have appeared in the press, majority of the world cannot run these models, interpret the numbers, and translate them to policy decisions. Consequently, governments and businesses must rely on scientific advisory bodies to enact policies. The wait between translation of scientific insights to actionable policies are leading to loss of precious time. Our work shows that using a classical new-product forecasting model from the marketing domain, policy makers can generate directional outlooks in the early period of the outbreak, especially when lack of data prevents sophisticated epidemiological models to be deployed. With as little as 2-4 weeks of new case data, this model can be implemented on a spreadsheet and answer all the three questions for an outbreak at a country, region, or county level. We test the model on the outbreak data from Hubei province, Korea, Italy, France, India and United States and find meaningful directional outlooks that can be translated to effective policies.

Keywords: Covid-19, Bass Diffusion, Forecast, Non-linear Least Squares, Spreadsheet Model

Suggested Citation

Pathak, Surya and Pathak, Sayan, Canary in the Coal Mine: Using Early Data to Aid Policy Makers Manage the Spread of COVID-19 Pandemic (April 10, 2020). Available at SSRN: https://ssrn.com/abstract=3578244 or http://dx.doi.org/10.2139/ssrn.3578244

Surya Pathak (Contact Author)

Surya Pathak ( email )

18115 Campus Way NE
Bothell, WA 98011-8246
United States

Sayan Pathak

Microsoft Corporation ( email )

One Microsoft Way
Redmond, WA 98052
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
119
Abstract Views
1,739
Rank
600,462
PlumX Metrics