The Data Behind the Federal Vaccine Algorithm May Be Skewed

Undocumented residents, tribal communities, and small census blocks are at risk

The federal algorithm for allotting vaccine doses is a “black box” run by the infamous data-processing giant Palantir, Natasha Singer reports in the New York Times.

The algorithm determines how many federally owned doses are sent to 64 jurisdictions, including states, large metro areas, and U.S. territories. It was called “Tiberius” until the Biden administration recently retired the name.

The algorithm’s calculations might be based on faulty data. Vaccine allotment decisions are being made from the American Community Survey, an annual poll that tracks populations more granularly than the census. But crucial stats like populations of tribal and undocumented residents, as well as small census tracts, are known to be unreliable, skewing the algorithm’s eventual results.

Many states that have received the vaccines have implemented their own algorithms and approaches to distributing the doses. For instance, Tennessee bases its vaccine distribution plan on the Center for Disease Control’s “Social Vulnerability Index,” which prioritizes those in poverty and crowded living situations.

Read more at the New York Times:

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Dave Gershgorn

Dave Gershgorn

Senior Writer at OneZero covering surveillance, facial recognition, DIY tech, and artificial intelligence. Previously: Qz, PopSci, and NYTimes.

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