Selected article for: "growth rate and lag time"

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_10
    Snippet: where k 1 is the current growth rate of infections to be detected, and r is the number of tests per day 3 . The numerical constant C depends on the required signal to noise ratio. A typical value when detecting large values of k 1 is C ≈ 30 − 40. This result shows that the higher the number of tests r per day, the shorter the time to detect a growth or 3 If the fraction of infected people can be measured via sewage water, r will be related to.....
    Document: where k 1 is the current growth rate of infections to be detected, and r is the number of tests per day 3 . The numerical constant C depends on the required signal to noise ratio. A typical value when detecting large values of k 1 is C ≈ 30 − 40. This result shows that the higher the number of tests r per day, the shorter the time to detect a growth or 3 If the fraction of infected people can be measured via sewage water, r will be related to the number of people connected to a given sewage plant. But at this point, the relationship between such data and the actual current number of infections remains a topic for research. Of course, once key parameters such as the lag time between infection and incidence of biomarkers in sewage are known, sewage tests could become highly competitive.

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