Brazil¶

  • Homepage of project: https://oscovida.github.io
  • Plots are explained at http://oscovida.github.io/plots.html
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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: 03/07/2022 09:38:57 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Brazil", weeks=5);
2022-07-03T09:39:01.013585 image/svg+xml Matplotlib v3.5.2, https://matplotlib.org/ 30 May 06 Jun 13 Jun 20 Jun 27 Jun 100 100 150 150 200 200 7-day incidence rate (per 100K people) Brazil, last 5 weeks, last data point from 2022-07-02 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0 20 40 60 daily change normalised per 100K 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0.0 0.1 0.2 daily change normalised per 100K 30 May 06 Jun 13 Jun 20 Jun 27 Jun 1.0 1.0 1.5 1.5 R & growth factor (based on cases) Brazil cases daily growth factor Brazil cases daily growth factor (rolling mean) Brazil estimated R (using cases) 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 1.75 1.75 R & growth factor (based on deaths) Brazil deaths daily growth factor Brazil deaths daily growth factor (rolling mean) Brazil estimated R (using deaths) 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0 500 1000 cases doubling time [days] Brazil doubling time cases (rolling mean) Brazil doubling time deaths (rolling mean) 0 42512 85024 127536 daily change Brazil new cases (rolling 7d mean) Brazil new cases 0.0 212.6 425.1 daily change Brazil new deaths (rolling 7d mean) Brazil new deaths 0 3508 7015 deaths doubling time [days]
In [4]:
overview("Brazil");
2022-07-03T09:39:06.077490 image/svg+xml Matplotlib v3.5.2, https://matplotlib.org/ Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 0 0 200 200 400 400 600 600 7-day incidence rate (per 100K people) 211.1 Brazil, last data point from 2022-07-02 Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 0 50 100 daily change normalised per 100K Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 0.0 0.5 1.0 1.5 daily change normalised per 100K Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 1.0 1.0 1.5 1.5 R & growth factor (based on cases) Brazil cases daily growth factor Brazil cases daily growth factor (rolling mean) Brazil estimated R (using cases) Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 1.75 1.75 R & growth factor (based on deaths)