As measles cases rise across the United States, a new and controversial trend is emerging in the financial world: gamblers are betting millions of dollars on the spread of the virus.
Since January, nearly $9 million has been wagered on prediction markets like Kalshi and Polymarket regarding future measles infections. While the ethics of profiting from a public health crisis are highly debated, these markets are revealing a surprising potential benefit: they may actually serve as a functional tool for epidemiological forecasting.
How Prediction Markets Work
Prediction markets operate on the principle of buying and selling “shares” in a future event. Unlike traditional sports betting, these markets function more like a stock exchange for real-world outcomes.
- Price as Probability: The cost of a “share” reflects the collective belief of the market. If 86% of traders believe an event will happen, a “yes” share will cost 86 cents.
- The Payout: If the event occurs, the winner receives $1 per share. If it does not, the share becomes worthless, and the losing traders effectively fund the winners’ profits.
- The “Wisdom of Crowds”: Proponents, such as Hypermind CEO Emile Servan-Schreiber, argue that these markets succeed because they harness “cognitive diversity.” Even if individual bettors lack medical expertise, the collective intelligence of a diverse crowd can often aggregate into a highly accurate forecast.
From Academic Research to Commercial Controversy
The concept of using markets to forecast events began in 1988 at the University of Iowa, where economists used small-scale markets to predict US elections. By 2003, researchers began incorporating infectious diseases into these models, viewing them as a way to serve the “public good” through better forecasting.
However, the transition from academic exercise to commercial enterprise has brought significant friction:
1. Ethical Backlash: Critics argue that betting on wars (such as those in Ukraine or Iran) is immoral.
2. Security Concerns: High-profile wins—such as a trader netting $553,000 by predicting the removal of Iran’s Ayatollah Ali Khamenei—have led US lawmakers to question whether traders are using insider information or state secrets to gain an edge.
3. Regulatory Scrutiny: While companies like Kalshi are regulated by the Commodity Futures Trading Commission, they face increasing pressure from both federal and state governments.
A New Data Stream for Epidemiologists?
Despite the moral gray areas, scientists are beginning to see a “silver lining” in the data generated by these bets.
In June 2025, prediction markets forecasted approximately 2,000 measles cases by year-end. The actual number was 2,288. For epidemiologists, this level of accuracy is notable. Spencer J. Fox of Northern Arizona University, who specializes in forecasting viruses like COVID-19 and RSV, noted that this forecast was actually superior to many traditional scientific models.
“Everyone is looking for an edge for forecasting infectious diseases, and we’re constantly on the lookout for new data streams.” — Spencer J. Fox
The Limits of “Crowd Intelligence”
While prediction markets offer a novel data stream, they are not a replacement for traditional science. Experts highlight several critical limitations:
- Lack of Granularity: Scientific models can produce thousands of specific, highly detailed forecasts. To replicate this via prediction markets, a user would have to place thousands of individual bets every week.
- The “Rare Event” Problem: While crowds are good at predicting general trends, experts argue that only specialists can accurately predict rare, high-impact events.
- Complexity of Variables: Traditional epidemiology relies on complex data—such as vaccination rates, genomic sequencing, and climate patterns—which prediction markets do not inherently process.
As the world prepares for future pandemics, the tension remains: can we rely on the “wisdom of the crowd” to protect public health, or does the commercialization of outbreaks undermine the very expertise needed to manage them?
Conclusion: While prediction markets offer a controversial and ethically complex way to track disease outbreaks, their ability to provide accurate, real-time data suggests they could become a valuable, albeit supplementary, tool for modern epidemiology.
