Covid-19 predictions using a Gauss model, based on data from April 2

Janik Schuttler; Reinhard Schlickeiser; Frank Schlickeiser; Martin Kroger

Each new seriously sick person per day (SSP) requires a respiratory machine for some days or even weeks before passing away or recovering from Covid-19. According to other works [19] , people to have died from Covid-19 occupied respiratory equipment for an average of 7 days prior to their death, but respiratory equipment may be in use for up to about one month for cases that later recovered. Thus, we may roughly estimate the number of active SSPs per date as the sum of people that became seriously sick within the past 10 days. Please note, however, that we try to only conceptually link the GM to useful quantities, we leave a thorough search of exact numbers to the reader. As a final step, we need relate SSPs and deaths. Assume that each SSP dies with a constant probability γ after some days, i.e. γ times SSPS gives the daily fatalities some days ahead. Taking again numbers from Ref. [19] , we could use that each deceased patient had used a respiratory machine for an average of 7 days prior to death and thus estimate the daily number of SSPs at a given date by the number of daily fatalities 7 days in the future divided by probability γ.