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_1
Snippet: Effective large scale testing and contact tracing have been successfully used in a number of countries for controlling the spread of the SARS-CoV-2 virus (CoV-2) which causes COVID-19 disease [1] . However, in resource-limited settings, it may not be feasible to do large scale testing unless the efficiency of existing tests is improved in terms of number of tests required for a given number of samples. In this short paper, we discuss a computer-s.....
Document: Effective large scale testing and contact tracing have been successfully used in a number of countries for controlling the spread of the SARS-CoV-2 virus (CoV-2) which causes COVID-19 disease [1] . However, in resource-limited settings, it may not be feasible to do large scale testing unless the efficiency of existing tests is improved in terms of number of tests required for a given number of samples. In this short paper, we discuss a computer-science inspired divide and conquer strategy based on pooling samples from multiple individuals that can improve test efficiency by a significant amount under a minimalistic set of assumptions.
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