Bolivia¶

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  • 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: 26/01/2023 09:25:31 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Bolivia", weeks=5);
2023-01-26T09:25:34.570748 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 50 50 100 100 150 150 7-day incidence rate (per 100K people) 37.7 Bolivia, last 5 weeks, last data point from 2023-01-25 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 20 40 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.00 0.02 0.04 0.06 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) Bolivia cases daily growth factor Bolivia cases daily growth factor (rolling mean) Bolivia estimated R (using cases) 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 deaths) Bolivia deaths daily growth factor Bolivia deaths daily growth factor (rolling mean) Bolivia estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 500 1000 1500 cases doubling time [days] Bolivia doubling time cases (rolling mean) Bolivia doubling time deaths (rolling mean) 0 2335 4669 daily change Bolivia new cases (rolling 7d mean) Bolivia new cases 0.000 2.335 4.669 7.004 daily change Bolivia new deaths (rolling 7d mean) Bolivia new deaths 0 5774 11547 17321 deaths doubling time [days]
In [4]:
overview("Bolivia");
2023-01-26T09:25:43.298307 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 0 200 200 400 400 600 600 7-day incidence rate (per 100K people) 37.7 Bolivia, 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 50 100 150 200 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 5 10 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)