| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| At least 1000 | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| ✓ At least 500 | 0% | 0¢ | 0¢ | — | $0 | Resolved |
| ✓ At least 200 | 0% | 0¢ | 0¢ | — | $0 | Resolved |
| ✓ At least 100 | 0% | 0¢ | 0¢ | — | $0 | Resolved |
| ✓ At least 50 | 0% | 0¢ | 0¢ | — | $0 | Resolved |
| At least 2000 | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| At least 5000 | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks traders to predict the average number of measles cases that will occur during a presidential term served by Donald Trump. It matters because measles incidence is a sensitive indicator of vaccination coverage, public-health policy, and international disease pressure, all of which have large population-health implications.
Measles is a highly contagious vaccine-preventable disease; the United States achieved elimination of endemic transmission in 2000, but outbreaks have recurred due to under-vaccination and importations. Changes in vaccination policy, public trust, federal and state public-health resources, and global measles activity during a presidential term will influence the observed average case counts.
Market prices reflect the collective judgment of traders about which outcome is most likely given available information and will update as new data and policy developments occur. Treat the market as a dynamic summary of expectations rather than a definitive forecast.
Check the contract specification on the platform for the exact start and end dates used by this event; the market page or official contract document will list the precise term window the outcomes reference.
The contract should specify which data sources and case definitions are authoritative (for example CDC confirmed cases, state-reported counts, or WHO data); consult the event’s specification to see whether laboratory-confirmed cases, probable cases, or combined totals are used.
Refer to the event’s rules: the market will define whether the average is annual, per-calendar-year, a mean across the term years, or another metric, and whether it uses arithmetic mean or another averaging method.
Announcements that affect vaccination uptake or importation risk typically move expectations fastest—examples include federal funding changes for vaccination programs, major state-level school vaccine law changes, emergency responses to outbreaks, or travel advisories tied to large international outbreaks.
Watch federal agencies (CDC, HHS), state and local health departments, major hospitals and laboratory networks that report cases, vaccine manufacturers and supply-chain announcements, and international bodies (WHO and major foreign public-health agencies) that signal importation risk.