Italy¶

  • 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 09:28:24 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Italy", weeks=5);
2023-01-26T09:28:28.183977 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 100 100 150 150 200 200 250 250 7-day incidence rate (per 100K people) 85.8 Italy, 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 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Italy cases daily growth factor Italy cases daily growth factor (rolling mean) Italy estimated R (using cases) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on deaths) Italy deaths daily growth factor Italy deaths daily growth factor (rolling mean) Italy estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 1000 2000 cases doubling time [days] Italy doubling time cases (rolling mean) Italy doubling time deaths (rolling mean) 0 30231 60462 90693 120924 daily change Italy new cases (rolling 7d mean) Italy new cases 0.0 302.3 604.6 daily change Italy new deaths (rolling 7d mean) Italy new deaths 0 829 1659 deaths doubling time [days]
In [4]:
overview("Italy");
2023-01-26T09:28:36.772907 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 0 500 500 1000 1000 1500 1500 2000 2000 7-day incidence rate (per 100K people) 85.8 Italy, 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 0 100 200 300 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 0.0 0.5 1.0 1.5 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 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Italy cases daily growth factor Italy cases daily growth factor (rolling mean) Italy estimated R (using cases) Jan 20 May 20 Sep 20