Prediction markets as a collective expectation signal for disease surveillance
Public health increasingly uses unofficial signals such as rumors, media, search, and self-reported symptoms to detect emergencies before official counts. Commercial prediction markets, where people bet on disease events, are a candidate new source, built for forecasting; but the expectation they price is itself a further unofficial signal. Their use as a public health signal is unvalidated in this domain and ethically contested: no study has yet shown that these prices anticipate official indicators, and whether public health should read bets on disease at all is disputed. A 2026 study judged them poor forecasters, but accuracy and surveillance value differ. Using thirteen Kalshi markets, we describe what such a reading would involve (a watchlist, an implied distribution, and fast repricing) as a collective expectation signal adjacent to participatory surveillance, and we set out the validation and governance agenda that would have to precede any use.
Authors
- Onicio Batista Leal Neto (ORCID: https://orcid.org/0000-0001-5785-1867)
Institutions
- University of Arizona (US)
Publication Details
- Journal
- npj Digital Public Health
- Published
- 2026-10-01
- DOI
- https://doi.org/10.1038/s44482-026-00042-6
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00