• Corpus ID: 218613916

Crackovid: Optimizing Group Testing

@article{Abraham2020CrackovidOG,
  title={Crackovid: Optimizing Group Testing},
  author={Louis Abraham and Gary B{\'e}cigneul and Bernhard Sch{\"o}lkopf},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.06413}
}
We study the problem usually referred to as group testing in the context of COVID-19. Given $n$ samples taken from patients, how should we select mixtures of samples to be tested, so as to maximize information and minimize the number of tests? We consider both adaptive and non-adaptive strategies, and take a Bayesian approach with a prior both for infection of patients and test errors. We start by proposing a mathematically principled objective, grounded in information theory. We then optimize… 

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