Luxembourg¶

  • Homepage of project: https://oscovida.github.io
  • Plots are explained at http://oscovida.github.io/plots.html
  • Execute this Jupyter Notebook using myBinder
In [1]:
import datetime
import time

start = datetime.datetime.now()
print(f"Notebook executed on: {start.strftime('%d/%m/%Y %H:%M:%S%Z')} {time.tzname[time.daylight]}")
Notebook executed on: 26/01/2023 09:29:23 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Luxembourg", weeks=5);
2023-01-26T09:29:26.588312 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 0 100 100 200 200 300 300 7-day incidence rate (per 100K people) 54.2 Luxembourg, last 5 weeks, last data point from 2023-01-25 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 50 100 150 200 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.0 0.5 1.0 1.5 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 2 2 4 4 6 6 8 8 10 10 R & growth factor (based on cases) Luxembourg cases daily growth factor Luxembourg cases daily growth factor (rolling mean) Luxembourg estimated R (using cases) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 2 2 4 4 6 6 8 8 10 10 R & growth factor (based on deaths) Luxembourg deaths daily growth factor Luxembourg deaths daily growth factor (rolling mean) Luxembourg estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 2000 4000 6000 cases doubling time [days] Luxembourg doubling time cases (rolling mean) Luxembourg doubling time deaths (rolling mean) 0 313 626 939 1252 daily change Luxembourg new cases (rolling 7d mean) Luxembourg new cases 0.00 3.13 6.26 9.39 daily change Luxembourg new deaths (rolling 7d mean) Luxembourg new deaths 0 430 859 1289 deaths doubling time [days]
In [4]:
overview("Luxembourg");
2023-01-26T09:29:35.070668 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 1000 1000 2000 2000 7-day incidence rate (per 100K people) 54.2 Luxembourg, last data point from 2023-01-25 Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 200 400 600 800 daily change normalised per 100K Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 1 2 3 4 daily change normalised per 100K Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 2 2 4 4 6 6 8 8 10 10 R & growth factor (based on cases) Luxembourg cases daily growth factor Luxembourg cases daily growth factor (rolling mean) Luxembourg estimated R (using cases) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 2