Selected article for: "case number and sample size"
Author: Cassidy Mentus; Martin Romeo; Christian DiPaola
Title: Analysis and Applications of Non-Adaptive and Adaptive Group Testing Methods for COVID-19
  • Document date: 2020_4_7
    • ID: 3sr4djft_96
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.05.20050245 doi: medRxiv preprint Figure 11 .1: For GBS32 we sample a population of size 10,000 and record the number of times each case is tested. Note that for prevalence of p = .1% a sample is used at most 5 times in the population. In gure 11.2 where we perform the same experiment we nd cases that are tested up to 9 times. We apply GB.....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.05.20050245 doi: medRxiv preprint Figure 11 .1: For GBS32 we sample a population of size 10,000 and record the number of times each case is tested. Note that for prevalence of p = .1% a sample is used at most 5 times in the population. In gure 11.2 where we perform the same experiment we nd cases that are tested up to 9 times. We apply GBS32 to nd at most D .99 . We see in gure 11.3 that the proportion of cases that are tested many times (more than 6) is very low. This is evidence that testing the cases indivually when we are running low (if we are limited to 6 uses) adds up to less than 1% extra tests. If we are able to test a sample more than this many times, individually testing when we are about to run out eects the eciency negligibly.

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