Tracking the worldwide COVID-19 pandemic
Since the early start of the COVID-19 outbreak in China we have reported on the available data via Twitter. We try to make a fast developing and complex situation understandable using dashboards and graphs.
We try to update all charts daily.
Only confirmed data used, it doesn't give the full picture, use with care
First a disclaimer. We have only used confirmed data reported by the governments of countries involved. Different countries have implemented different testing strategies and also have different testing capacities. It is resonable to believe most countries under report the actual number of cases and some countries with a wide margin (like China). It makes comparing countries tricky. So please use with care.
Feel free to mail suggestions to us.
Update 14-Apr: We slowed down updating this page. We need some time to look into what charts and data can provide the best insight now many countries are entering a new phase. Some charts we will still push on our Twitter account.
New: we now have an interactive tool available for you to make your own comparisons, changing dimensions and startpoints. You can also share it easy with other people. The tool was created by Innouveau and is filled daily with our data set.
First chart is of all active cases proportional to the population. Active cases are all confirmed cases (cumulative) minus the people who died and minus the people who recovered. So it's about people still being ill. Not all countries do proper reporting on recovered cases so we left out some of the major countries.
This chart starts at the first day with over one case per million inhabitants and uses a log scale, meaning the vertical axis doesn't have steps from 1 to 2, but from 1 to 10. So each horizontal line up means 10 times as much cases per 100.000 inhabitants.
Horizontal line at end most of the times means no update for last day available yet.
New York is New York State (Including New York City, but not the complete New York Metropolitan area),
Again with only active cases, but this one starts on the first day with one case in each country. For selected countries (mostly based on the active number of cases)
Since the data from China is deemed not thrustworthy enough, we've created a version without China. We also switched to linear y-axis to have different view on the relative impact.
A overview on the situation in a dashboard set up.
Note on CFR: the real Case Fatality Rate can only be calculated after an epidemic is over. It should also take into account all mild cases that go undetected. So the CFR's you see here is now only based on the tested people. It might somewhere between 3 and 10 times higher than what will be reported after it's all over.
nCFR = Naïve Case Fatality Rate: all deaths divided by all known cases at a given moment. It's called naïve because people are still ill and might still die. So at the end of the epidemic it will probably higher (based on the tested people).
rCFR = Resolved Case Fatality Rate: all deaths divided by the sum of all deaths and all recovered. This is a more conclusive indicator, but it discounts the possibility that a large part of currently ill people might just have a longer period of recovery and don't die after all, lowering the rCFR.
Another way to look at the growth of cases is to take the factor with which the cases of one day compare to the previous day. Steady growth of *1,2 day over day doubles the number of cases in four days each time.
All cases (cumulative) per 100.000 inhabitants, from the first day with a case, normal scale on vertical axis.
An experimental chart tries to combine multiple factors. The x-axis contains on a log scale the number of confirmed cases, the y-axis the number of deaths. The size of the circles is proportional to the size of the population. The darkness of the circles relates to the population density, darker means more people per square kilometer.
The selected countries are either from the top 30 most populated countries or the countries with a significant number of deaths from Covid-19.
The distribution roughly represents a Case Fatality rate of 2.6%.
Another approach to this chart is to use the cases and deaths proportional to the populations (as cases and deaths per million people). This brings more focus on the relative impact on each country.
- Our World in Data
- Johns Hopkins University (downloads), Dashboard
Tools / trackers elsewhere:
Ook interessant om te lezen
The charts we provide on the global development of Covid-19 always use a selection. So we embraced the help of another country for creating a tool where everybody can make their own selections. The tool is now grown up. So time to give a bit of background info, some explainers and some disclaimers.
ACTUALITEIT - Because of the recent terrorism attacks in Europe we've plotted the GTD data and most recent figures in several graphs for Western Europe.