Germany: LK Fulda (Hessen)¶

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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: 07/03/2023 12:28:10 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Fulda", weeks=5);
2023-03-07T12:28:24.383303 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 200 200 300 300 400 400 7-day incidence rate (per 100K people) 120.3 LK Fulda, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 20 40 60 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.0 0.1 0.2 0.3 0.4 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.4 0.4 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Germany-LK Fulda cases daily growth factor Germany-LK Fulda cases daily growth factor (rolling mean) Germany-LK Fulda estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 0 1 1 2 2 3 3 4 4 R & growth factor (based on deaths) Germany-LK Fulda deaths daily growth factor Germany-LK Fulda deaths daily growth factor (rolling mean) Germany-LK Fulda estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 1000 2000 3000 4000 cases doubling time [days] Germany-LK Fulda doubling time cases (rolling mean) 0.0 44.7 89.4 134.1 daily change Germany-LK Fulda new cases (rolling 7d mean) Germany-LK Fulda new cases 0.000 0.224 0.447 0.671 0.894 daily change Germany-LK Fulda new deaths (rolling 7d mean) Germany-LK Fulda new deaths 0.000 0.238 0.476 0.714 0.952
In [4]:
overview(country="Germany", subregion="LK Fulda");
2023-03-07T12:28:43.974786 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 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) 120.3 LK Fulda, Germany, last data point from 2023-03-06 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 100 200 300 400 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2 4 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.4 0.4 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases)