Scott provides a real-world example of how the phrase 'no evidence' can be misused in science reporting, contrasting it with a prediction market's more nuanced response. Longer summary

This post is an addendum to Scott's previous article about the misuse of the phrase 'no evidence' in science communication. He provides a recent example from the Financial Times, which claimed there was 'no evidence' that the Omicron variant of COVID-19 was less deadly than Delta, based on a single study. Scott contrasts this with the Metaculus prediction market's response to the same study, showing how the market briefly dipped but quickly recovered and increased its prediction that Omicron was indeed less lethal. He presents this as a clear illustration of the difference between classical (frequentist) and Bayesian approaches to evidence and probability. Shorter summary

Scott Alexander analyzes prediction market forecasts about the Omicron COVID-19 variant, discussing its potential transmissibility, lethality, and prevalence. Longer summary

Scott Alexander discusses predictions about the Omicron variant of COVID-19 using data from prediction markets, particularly Metaculus. He examines forecasts on the variant's transmissibility (R0), lethality compared to Delta, and its expected prevalence in the US. The post highlights that Metaculus predicts Omicron to be more transmissible than Delta, with a 34% chance of being deadlier, and likely to become the dominant US variant by mid-March. Scott concludes with a humorous tweet about the rapid emergence of new variants. Shorter summary