Author: Markus Mueller; Peter Derlet; Christopher Mudry; Gabriel Aeppli
Title: Using random testing to manage a safe exit from the COVID-19 lockdown Document date: 2020_4_14
ID: loi1vs5y_57
Snippet: To reach decisions on policy measures, data is acquired by daily testing of random sets of people for infections. We assume that the tests are carried out at a limited rate r (a finite number of tests divided by a nonvanishing unit of time). Let i(t, ∆t) be the fraction of positive infections detected among the r ∆t 1 tests carried out in the time interval [t, t + ∆t]. By the law of large numbers, it is a Gaussian random variable with mean.....
Document: To reach decisions on policy measures, data is acquired by daily testing of random sets of people for infections. We assume that the tests are carried out at a limited rate r (a finite number of tests divided by a nonvanishing unit of time). Let i(t, ∆t) be the fraction of positive infections detected among the r ∆t 1 tests carried out in the time interval [t, t + ∆t]. By the law of large numbers, it is a Gaussian random variable with mean
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