Selected article for: "positive probability and propose strategy"
Author: Fayyaz Minhas; Dimitris Grammatopoulos; Lawrence Young; Imran Amin; David Snead; Neil Anderson; Asa Ben-Hur; Nasir Rajpoot
Title: Improving COVID-19 Testing Efficiency using Guided Agglomerative Sampling
  • Document date: 2020_4_14
    • ID: 7rip6wtu_3
    Snippet: Given a set of individuals to be tested for CoV-2, the number of tests required for identifying positive individuals can be reduced from by considering the fact that the probability of testing positive is small (say, = 0.1) and individual test results are typically not independent of each other (e.g., members in the same household or people in contact with each other or other CoV-2 infected individuals can have dependencies in their test results).....
    Document: Given a set of individuals to be tested for CoV-2, the number of tests required for identifying positive individuals can be reduced from by considering the fact that the probability of testing positive is small (say, = 0.1) and individual test results are typically not independent of each other (e.g., members in the same household or people in contact with each other or other CoV-2 infected individuals can have dependencies in their test results). In this work, we propose a divide and conquer agglomerative sampling strategy that is built on these ideas and can be used to reduce the number of tests. Before delving into the details of the method, we present a list of assumptions underlying the proposed method:

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