Less-sensitive COVID-19 tests may still achieve optimal results if enough people tested
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A computational analysis of COVID-19 tests suggests that, in order to minimize the number of infections in a population, the amount of testing matters more than the sensitivity of the tests that are used. Philip Cherian and Gautam Menon of Ashoka University in Sonipat, India, and Sandeep Krishna of the National Centre for Biological Sciences TIFR, Bangalore, India, present their findings in the open-access journal PLOS Computational Biology.
