Prediction Market for Disease Surveillance: A Case Study of Influenza Activity

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Anson T Y Ho
Philip M Polgreen
Tim Prendergast


We conducted a pilot study on the use of prediction markets to aggregate private information for disease surveillance. Influenza activity in Iowa, North Carolina, and Nebraska between 2008-2010 was forecast through prediction markets operated on the Iowa Electronic health Markets (IEhM). We found that prediction markets were well utilized by participants, and they achieved high level of forecasting accuracy as far as 4 weeks before actual influenza-level outcomes were announced. Trading activities indicate that new information continuously flowed into the markets during the trading window, which further improved prediction accuracy as contracts drew down to expiry. This project demonstrates that a prediction market is a practical infectious disease surveillance mechanism that provides low-cost useful information for public health administration in a timely manner.

Article Details

Author Biographies

Anson T Y Ho, Kansas State University

Assistant Professor, Department of Economics

Philip M Polgreen, University of Iowa

Associate Professor, Department of Internal Medicine


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