Biology Reference
In-Depth Information
at al. 2003), emergency department visits (Irvin et al. 2003, Yaun et al. 2004,
Suyama et al. 2003), absentee data (Lenaway et al. 1995) and Internet search
query log data (Polgreen et al. 2008, Ginsberg et al. 2009). In the case of sea-
sonal influenza, these approaches have provided improved lead-time over
traditional disease activity reports (Dailey et al. 2007). However, all of these
approaches rely on quantitative data that can produce “false alarms” or miss
abrupt changes. Often the addition of human interpretation can supplement
such quantitative data streams, but it is difficult to aggregate subjective data.
In this chapter we propose a relatively new method for gathering and aggre-
gating disease information. This method involves operation of specialized
futures markets called
prediction markets
and inviting health experts to trade
in these markets. The prices generated in these markets can provide a con-
sensus view regarding the likelihood of future disease-related events. After
a brief discussion of futures markets and prediction markets, we present
data from a pilot novel influenza A (H1N1) prediction market.
8.2 Futures Markets
In traditional futures markets, traders buy and sell contracts that specify
the quantity and quality of commodities to be delivered by a certain date. In
some cases, these contracts are associated with crops that have not yet been
planted or oil that is still in the ground. These markets exist to help producers
and consumers of commodities plan for the future. For example, they enable
farmers to lock in prices for their crops before those crops are planted. On
the other side of the market, food processors use futures markets to ensure
a steady supply of raw materials at a specific price. Widespread adoption of
futures markets have led to dramatic stabilization of agricultural prices.
The prices in futures markets change because they incorporate informa-
tion that might affect the supply and demand for goods in the future. For
example, geopolitical events can dramatically affect oil futures prices. It is
not surprising that these prices change according to expectations of future
events, but what is surprising is how fast new information is incorporated
into futures prices. Orange juice futures markets provide a classic example.
In these markets, commodity traders buy and sell contracts for the future
delivery of orange juice. The prices they pay for these contracts reflect trad-
ers' beliefs about the future price of orange juice. Because the size of the
orange crop is affected by the weather, orange juice prices are also influ-
enced by the weather. A severe frost can decimate the U.S. orange crop in
Florida. Therefore, the price of futures contracts should be, and is, influenced
by weather forecasts. If a heavy freeze is predicted, traders anticipate that
orange juice prices will go up and, therefore, they bid up the price of orange
juice futures. Interestingly, an analysis of the timing of the changes in orange
