SimpleFunctions

Above 300000 gonorrhea cases in the United States during 2026

Above 300000 gonorrhea cases in the United States during 2026: Above 300k is priced at 80¢ on Kalshi. Current book: 78¢ bid, 79¢ ask, 1¢ spread. This outcome ranks #2 of 9 inside KXGONORRHEACOUNT-27JAN01.

Price history

80¢ current

+78¢
0¢25¢50¢75¢100¢
May 14, 2026May 26, 2026

Contract brief

If the total number of gonorrhea cases reported in the United States during 2026 is above 300000, then the market resolves to Yes.

Outcome

Above 300000 gonorrhea cases in the United States during 2026: Above 300k

Rank

#2 of 9

Leader

Above 285000 gonorrhea cases in the United States during 2026: Above 285k 83¢

Range

18¢-83¢

Family volume

$268

Identifier

KXGONORRHEACOUNT-27JAN01-A300000

May 26, 2026, 9:08 PM UTC · 6m ago

Implied probability

80¢
Latest venue quote
May 26, 2026, 9:08 PM UTC · 6m ago

Bid

78¢

Ask

79¢

Spread

24h volume

$153

Family rank

#2 of 9

9 outcomes · KXGONORRHEACOUNT-27JAN01

Closes

Jan 1, 2027

Family volume

$268

Orderbook snapshot

78 / 79¢

Kalshi
1¢ spread
BidSize
78¢10
77¢32
76¢62
75¢500
70¢128
AskSize
79¢5
82¢229
83¢500
86¢158
91¢81

Contract terms

What resolves this market.

YES condition

If the total number of gonorrhea cases reported in the United States during 2026 is above 300000, then the market resolves to Yes.

Venue

Kalshi

Closes

Jan 1, 2027

Identifier

KXGONORRHEACOUNT-27JAN01-A300000

SF Signal
SF Index
588.91
Regime
neutral

Indicators

Yield, cliff risk, volatility, and regime.

IY (Yes)

46.8%

IY (No)

588.9%

Adj IY

589%

CRI

4

RV

157%

VR

2.21

Regime

neutral

Score

0.5

Full indicator table

46.8%
588.9%
Adj IY
589%
4
RV
157%
VR
2.21
IAR
0.2/h
Overround
4.0%

Odds pages

Related prediction questions

Browse odds

Related readings

Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.

Browse library
Blogmarkets

Kalshi vs Polymarket: Which Prediction Market Should You Trade?

In-depth comparison of Kalshi and Polymarket for prediction market traders. Regulatory structure, liquidity, fees, API tooling, and cross-venue trading with SimpleFunctions.

Opinioncomparison

Kalshi vs Polymarket: Mechanics, Fees, Regulation, Liquidity (2026)

Side-by-side comparison of Kalshi and Polymarket in 2026. Fee math, calibration data, withdrawal speed, and a decision tree for picking the right venue.

Technicalguide

Kalshi vs Polymarket: A Developer's Comparison of APIs, Orderbooks, and Liquidity

Data-driven comparison of Kalshi and Polymarket APIs, orderbooks, rate limits, and liquidity. Code examples for building on both prediction markets.

Conceptmethodology

Maker / Taker Regime in Prediction Markets: How to Read the Orderbook State

Three regime states (maker-dominated, taker-dominated, neutral) and how to read which one a Kalshi or Polymarket contract is in. Strategy follows regime, not thesis.

Opinionanalysis

Liquidity Availability Is the Real Edge in Prediction Markets

Implied yield, cliff risk, and overround all describe what to trade. Liquidity Availability Score describes whether the orderbook can absorb the trade. Why LAS is the indicator that decides who actually books P&L.

Technicalguide

Computing Liquidity Availability Score from the Orderbook

Step-by-step guide to computing the Liquidity Availability Score in TypeScript and Python, with edge cases for thin orderbooks, missing data, and the warm-cron coverage limitation.

SimpleFunctions context

Index, screen, query, and monitor.

Open index

How we compute these odds

SimpleFunctions aggregates live prediction-market contracts from Kalshi and Polymarket. Each slug groups contracts that resolve on the same underlying event, identified by venue event_id.

For binary slugs, the headline probability is the liquidity-weighted mid-price across all bound contracts. For multi-outcome slugs (e.g. elections with 3+ candidates), the headline is the leader’s price; we never arithmetically average disjoint outcomes — that would produce a number with no real-world meaning.

Snapshots refresh every 5 minutes during market hours; daily aggregates are computed at 04:00 UTC. The 30-day sparkline is drawn from per-ticker daily means stored in market_indicator_daily; 24h delta and movement events are derived from the same source.