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Increasing testing throughput and case detection with a pooled-sample Bayesian approach in the context of COVID-19

Rodrigo Noriega, Matthew H. Samore
doi: https://doi.org/10.1101/2020.04.03.024216

Article Information

doi 
https://doi.org/10.1101/2020.04.03.024216
History 
  • April 5, 2020.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Author Information

  1. Rodrigo Noriega1,* and
  2. Matthew H. Samore2,3
  1. 1Department of Chemistry, University of Utah, Salt Lake City, UT USA
  2. 2Division of Epidemiology, University of Utah, Salt Lake City, UT USA
  3. 3Division of Epidemiology, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah
  1. ↵*Correspondence to: noriega{at}chem.utah.edu
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Posted April 05, 2020.
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Increasing testing throughput and case detection with a pooled-sample Bayesian approach in the context of COVID-19
Rodrigo Noriega, Matthew H. Samore
bioRxiv 2020.04.03.024216; doi: https://doi.org/10.1101/2020.04.03.024216
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