Selected article for: "decay constant and new infection"

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_25
    Snippet: In Fig. 2 This recently decaying behaviour can also be seen when looking at the raw data of total (country-wide) infection numbers (2 (g)). Indeed, when estimating the average country-wide infection rate curve without the effect of the weekday (2 (h)) the rate decays since approximately 10 days, after being rather constant for 10-20 days before the decay. The partial effect of the weekday shows a distinct minimum at the weekend (2 (e)). New infec.....
    Document: In Fig. 2 This recently decaying behaviour can also be seen when looking at the raw data of total (country-wide) infection numbers (2 (g)). Indeed, when estimating the average country-wide infection rate curve without the effect of the weekday (2 (h)) the rate decays since approximately 10 days, after being rather constant for 10-20 days before the decay. The partial effect of the weekday shows a distinct minimum at the weekend (2 (e)). New infections are first reported to the local health office and then collected by the RKI. During weekends, notifications of new infections are delayed and thus influence the RKI infection dataset, creating the observed decrease at weekends.

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