Selected article for: "infection curve and maximum number"

Author: Moritz Mercker; Uwe Betzin; Dennis Wilken
Title: What influences COVID-19 infection rates: A statistical approach to identify promising factors applied to infection data from Germany
  • Document date: 2020_4_17
  • ID: 09nvausz_10
    Snippet: Finally, the normalised smooth curve has been used for each AD to create two different measures representing the strength of the recent decay: (1) we calculated the value β 1 , which is defined by the curve value of the most current date minus the value 10 days before, and (2) we calculated β 2 , which is defined by the value of the current data divided by the maximum of the curve. Thus, β 1 is proportional to the current slope of the infectio.....
    Document: Finally, the normalised smooth curve has been used for each AD to create two different measures representing the strength of the recent decay: (1) we calculated the value β 1 , which is defined by the curve value of the most current date minus the value 10 days before, and (2) we calculated β 2 , which is defined by the value of the current data divided by the maximum of the curve. Thus, β 1 is proportional to the current slope of the infection curve (averaged over the last 10 days), whereas β 2 rather relates the current infection number to the overall maximum of the smoothed infection curve. Hence, β 1 is a reasonable measure even if most of the local infection curves are still increasing, whereas β 2 is only appropriate if most of the infection curves are already decreasing.

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