South Sudan¶

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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 09:42:34 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("South Sudan", weeks=5);
2022-07-03T09:42:37.629839 image/svg+xml Matplotlib v3.5.2, https://matplotlib.org/ 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0.0 0.0 0.2 0.2 0.4 0.4 7-day incidence rate (per 100K people) 0.2 South Sudan, last 5 weeks, last data point from 2022-07-02 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0.00 0.05 0.10 0.15 0.20 daily change normalised per 100K 30 May 06 Jun 13 Jun 20 Jun 27 Jun −0.050 −0.050 −0.025 −0.025 0.000 0.000 0.025 0.025 0.050 0.050 daily change South Sudan new deaths (rolling 7d mean) South Sudan new deaths 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0 0 1 1 2 2 3 3 4 4 R & growth factor (based on cases) South Sudan cases daily growth factor South Sudan cases daily growth factor (rolling mean) South Sudan estimated R (using cases) 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) South Sudan deaths daily growth factor South Sudan deaths daily growth factor (rolling mean) South Sudan estimated R (using deaths) 30 May 06 Jun 13 Jun 20 Jun 27 Jun 0 5000 10000 cases doubling time [days] South Sudan doubling time cases (rolling mean) 0.00 5.60 11.19 16.79 22.39 daily change South Sudan new cases (rolling 7d mean) South Sudan new cases 0.000 0.391 0.781
In [4]:
overview("South Sudan");
2022-07-03T09:42:43.126694 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 5 5 10 10 7-day incidence rate (per 100K people) 0.2 South Sudan, 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 1 2 3 4 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 0.00 0.02 0.04 0.06 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 1 1 2 2 3 3 4 4 R & growth factor (based on cases) South Sudan cases daily growth factor South Sudan cases daily growth factor (rolling mean) South Sudan 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 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) South Sudan deaths daily growth factor South Sudan deaths daily growth factor (rolling mean) South Sudan estimated R (using deaths) Jan 20 Apr 20 Jul 20 Oct 20 Jan 21 Apr 21 Jul 21 Oct 21 Jan 22 Apr 22 Jul 22 0 5000 10000 cases doubling time [days]