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

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.