Prediction markets and the future of Covid-19 – STAT

by | Sep 2, 2022 | COVID-19

Forecasters have used all sorts of tools to gauge where the U.S. and the world are headed with Covid-19, ranging from epidemiologic models to historical ones. Here’s another possibility: prediction markets.
Prediction markets use a wisdom of crowds approach to aggregate beliefs and predict future outcomes. They typically function through bets in futures contracts that pay out on expiration of defined “yes or no” outcomes. The Iowa Electronic Markets, for example, successfully predicted the outcomes of every presidential election from 1988 to 2000 to within 1.5 percentage points.
Prediction markets have their own agnostic efficiency and logic. The investor goal is to make money. The market-maker goal is to accurately predict outcomes without the “noise” of morality, science, ideology, politics, or culture. The wisdom of crowdsourced betting is harnessed to make accurate predictions in complex scenarios with significant uncertainties.

In 2008, online prediction market Intrade predicted that Barack Obama would win 364 electoral college votes. He won 365.
The prediction market platform might be used for pandemic forecasting — and may be more effective than traditional approaches.

Morality, science, ideology, politics, and culture are the very forces that have shaped personal and national policy responses to the Covid-19 pandemic. As we approach three years of life with SARS-CoV-2, the virus that causes Covid-19, and deliberations move to the “living with the virus” phase, decision-making alternatives are needed.
Science offers much legitimate guidance about risk levels and actions to mitigate them — whether and when to wear masks, test, quarantine, get vaccinated or boosted, and the like — though each of these have been hotly and sometimes acrimoniously debated. This is where prediction markets could earn their stripes.
Applying a detached prediction market lens approach may produce provocative — and perhaps more accurate — pandemic forecasts than pure evidence-driven a …

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