Philippines¶

  • 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 09:30:38 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview("Philippines", weeks=5);
2023-01-26T09:30:41.532859 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 2 2 4 4 6 6 7-day incidence rate (per 100K people) 1.1 Philippines, last 5 weeks, last data point from 2023-01-25 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.0 0.2 0.4 0.6 0.8 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.00 0.01 0.02 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) Philippines cases daily growth factor Philippines cases daily growth factor (rolling mean) Philippines estimated R (using cases) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.5 0.5 1.0 1.0 1.5 1.5 R & growth factor (based on deaths) Philippines deaths daily growth factor Philippines deaths daily growth factor (rolling mean) Philippines estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 5000 10000 15000 20000 cases doubling time [days] Philippines doubling time cases (rolling mean) Philippines doubling time deaths (rolling mean) 0 219 438 657 877 daily change Philippines new cases (rolling 7d mean) Philippines new cases 0.00 10.96 21.92 daily change Philippines new deaths (rolling 7d mean) Philippines new deaths 0 3488 6976 10463 13951 deaths doubling time [days]
In [4]:
overview("Philippines");
2023-01-26T09:30:49.717181 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 50 50 100 100 150 150 200 200 7-day incidence rate (per 100K people) 1.1 Philippines, 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 10 20 30 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 0.3 0.4 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)