Two weeks ago, I started loading data on the CoVid19 outbreak in order to understand, out of any official communication from any country, what is really going on.
From february 29 to march 9 these data come from https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ and from 10 march until now from https://www.worldometers.info/coronavirus/#repro.In all cases the loading is done manually (copy-paste onto a LibreOffice spreadsheet plus correction and save into a xls file)Â for I wasn't capable to find csv data (csv data do exist here https://github.com/CSSEGISandData/COVID-19, by they end febreuary 15th).
So I copied-pasted the results from the two sources above into a LibreOffice spreadsheet, adjusted the names of some countries for they appeared differently (for instance "United States" instead of "USA"), removed the unnessary commas and saved the result in a xls file.
I also used data from https://www.worldometers.info/world-population/population-by-country/ to get the populations of more than 260 countries around the world and, finally, csv data from https://ourworldindata.org/coronavirus#covid-19-tests to get synthetic histories of confirmed and death cases (I have discovered this site only yesterday evening and I think it could replace all the data I initially loaded).
The two worksheet here are aimed to exploratory and visualization only.
An other one is in progress whose goal is to infer the true death rate (also known as CFR, Case Fatality Rate).
No analysis is presented, if for no other reason than that the available data (except the numbers of deaths) are extremely dependent on the testing policies in place. But some features can be drawn from the data used here.
For instance, if you select country = "China" in file Covid19_Evolution_bis.mw, you will observe very well known behaviour which is that the "Apparent Death Rate", I defined as the ratio of the cumulated number of death at time t by the cumulatibe number of confirmed cases at the same time, is always an underestimation of the death rate one can only known once the outbreak has ended. With this in mind, changing the country in this worksheet from China to Italy seems to lead to frightening scary interpolations... But here again, without knowing the test policy no solid conclusion can be drawn: maybe Italy tests mainly elder people with accute symptoms, thus the huge "Apparent Death Rate" Italy seems to have?
The work has been done with Maple 2015 and some graphics can be improved if a newer version is used (for instance, as Maple 2015 doesn't allow to change the direction of tickmarks, I overcome this limitation by assigning the date to the vertical axis on some plots).
The second Explore plot could probably be improved by using newer versions or Maplets or Embeded components.
Explore data from https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ and https://www.worldometers.info/coronavirus/#repro
Files to use
Explore data from https://ourworldindata.org/coronavirus#covid-19-tests
Files to use
I would be interested by any open collaboration with people interested by this post (it's not in my intention to write papers on the subject, my only motivation is scientific curiosity).