What will the average number of measles cases be during Trump's term?

**Stage 1 — Blind analysis (ignore market prices):**

- The question as written in the recent context is explicit: the Trump Administration is defined as January 20, 2017–January 20, 2021 and the recent news provides CDC-confirmed calendar-year counts for 2017–2020: 121, 372, 1,282 and 13 respectively. Summing those gives 1,788 total cases across the four calendar years and dividing by 4 yields an average of **447 cases per year**.

- If the contract’s intended measure is the simple arithmetic mean of annual confirmed U.S. measles cases for the four calendar years overlapping the administration (2017, 2018, 2019, 2020), that calculation is deterministic and supported by primary-source CDC surveillance numbers. The only realistic sources of error are (a) any deliberate alternate interpretation of the date range (e.g., counting partial years differently), or (b) retrospective revisions to surveillance totals by the CDC.

- Historical practice: many retrospective event-statistics questions use calendar-year aggregates when asking for per-year averages for a presidential term. Under that conventional interpretation, the figure 447 is not an estimate but a computed fact from published surveillance data.

- Likelihood of substantive CDC revision that would shift the average materially is very low. Measles case counts are confirmed case surveillance that can be adjusted slightly on rare occasions, but changes large enough to move a 447 average materially (e.g., tens or hundreds of cases) are improbable.

- Given these points, my independent (blind) probability that the correct resolved average—under the conventional calendar-year interpretation—is essentially certain. I assign **~99%** to the 'Yes' outcome if 'Yes' means that the average equals the computed 447 (or that the canonical calculation using those four years yields 447). I avoid stating absolute 100% only to allow for the tiny chance of classification/revision/resolution-operator interpretation edge cases.

**Stage 2 — Market calibration (now consider market prices):**

- Current market pricing is: Yes 0.3 / No 0.7. That implies market participants assign only a 30% chance that the event will resolve to 'Yes'. This is a large divergence from the near-certain arithmetic result.

- Potential explanations for the market discount (why price is low): - *Ambiguity in the contract wording or resolution criteria.* If the contract actually uses a different numerator/denominator (for example, counts during Jan 20, 2017–Jan 20, 2021 daily totals rather than calendar-year totals), traders may believe the canonical 4-calendar-year method is not the one that will be used to resolve the market. The event title mentioning 2025–2028 (contradiction in the metadata) could be sowing confusion. - *Participants may suspect a nonstandard rounding or threshold.* If the binary contract tests a comparison (e.g., “Is average > X?”) rather than equality to 447, traders may be pricing that alternate predicate rather than the explicit average calculation shown in the news context. - *Illiquid or misinformed trading.* Despite sizable volume, a subset of traders might be betting on phrasing ambiguity or on the improbable chance of data revision. Some traders may not have inspected CDC totals and are relying on gut instincts about measles trends. - *Possible disagreement about whether the administration period includes a partial 2017 and partial 2021 and should use those partial-year counts instead of full calendar years.* If the contract were interpreted by the resolution source to compute the average using cases that fell strictly inside Jan 20, 2017–Jan 20, 2021 (i.e., excluding 2017 calendar days before Jan 20 and including 20 days of 2021), the total could differ slightly from the 1,788 figure used above.

- Calibration conclusion: the market likely reflects confusion or ambiguity rather than new evidence that the arithmetic is wrong. If the contract actually resolves using the calendar-year totals explicitly named in the provided context, the market is mispriced and 'Yes' is dramatically underpriced. If, however, the contract uses a nonstandard resolution methodology (partial-year counts, alternative denominator, or a comparative threshold), then the market price may reflect that interpretation and my high-confidence assessment would not apply.

- Practical implication for traders: If you can verify the contract’s precise resolution language (what exact counts/dates and rounding rules the oracle will use), there is likely an actionable edge: if the resolution uses calendar-year totals 2017–2020 as stated, buying Yes is a high-probability arbitrage play; if the resolution uses a different definition, evaluate that definition against CDC datasets before trading.