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Poolkeh Finds the Optimal Pooling Strategy for a Population-wide COVID-19 Testing (Israel, UK, and US as Test Cases)

Eliaz, Y.; Danovich, M.; Gasic, G. P.

2020-04-30 public and global health
10.1101/2020.04.25.20079343 medRxiv
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AO_SCPLOWBSTRACTC_SCPLOWThe SARS-CoV-2 pandemic has changed the lifestyle of citizens of the world. In order for decision makers to manage the viral spread of COVID-19 both in the intra-national and the international frontiers, it is essential to operate based on data-driven assessments. Its crucial to do so rapidly and frequently, since the nature of the viral spread grows exponentially and can burst worldwide again. A fast and accurate health status of individuals globally during a pandemic can save many lives and bring life back to a new normal. Herein, we present a data-driven tool to allow decision-makers to assess the spread of the virus among the world population. Our framework allows health agencies to maximize the throughput of COVID-19 tests among the world population by finding the best test pooling that fits the current SIR-D [1] status of the nation.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.