Affiliate Ziad Obermeyer co-authors an article for MIT Technologies Review, discussing his research with Ned Augenblick and Jonathan Kolstad that aims to make COVID-19 testing more widely available.
“It’s impossible to contain covid-19 without knowing who’s infected: until a safe and effective vaccine is widely available, stopping transmission is the name of the game. While testing capacity has increased, it’s nowhere near what’s needed to screen patients without symptoms, who account for nearly half of the virus’s transmission.
Our research points to a compelling opportunity for data science to effectively multiply today’s testing capacity: if we combine machine learning with test pooling, large populations can be tested weekly or even daily, for as low as $3 to $5 per person per day.
In other words, for the price per test of a cup of coffee, governments can safely reopen the economy and halt ongoing covid-19 transmission—all without building new labs and without new drugs or vaccines.”
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