Bhutan¶

  • 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 09:25:39 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Bhutan", weeks=5);
2023-01-26T09:25:42.905857 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 0 1 1 2 2 3 3 7-day incidence rate (per 100K people) 2.7 Bhutan, last 5 weeks, last data point from 2023-01-25 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 1 2 3 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan −0.050 −0.050 −0.025 −0.025 0.000 0.000 0.025 0.025 0.050 0.050 daily change Bhutan new deaths (rolling 7d mean) Bhutan new deaths 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 2 2 4 4 6 6 R & growth factor (based on cases) Bhutan cases daily growth factor Bhutan cases daily growth factor (rolling mean) Bhutan estimated R (using cases) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 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) Bhutan deaths daily growth factor Bhutan deaths daily growth factor (rolling mean) Bhutan estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 20000 40000 60000 cases doubling time [days] Bhutan doubling time cases (rolling mean) 0.00 7.72 15.43 23.15 daily change Bhutan new cases (rolling 7d mean) Bhutan new cases 0.000 0.327 0.655 0.982
In [4]:
overview("Bhutan");
2023-01-26T09:25:50.922936 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 7-day incidence rate (per 100K people) 2.7 Bhutan, 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 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 0.1 0.2 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 2 2 4 4 6 6 R & growth factor (based on cases) Bhutan cases daily growth factor Bhutan cases daily growth factor (rolling mean) Bhutan estimated R (using cases) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 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)