The graph above is extracted from the presentation given during the UK government’s Covid-19 press conference on Wednesday 6 May.  It  shows the cumulative number of deaths per million population for a number of countries. 

The UK is doing badly on that measure, as it’s just below Spain. But it doesn’t appear to be doing very much worse than the US. Neither does the difference between Germany and the UK  seem fantastically dramatic. It appears that Japan and South Korea are doing quite badly as well.

However, the graph is using a logarithmic scale (or log scale), which is a way of displaying numerical data over a very wide range of values in a compact way—typically the largest numbers in the data are hundreds or even thousands of times larger than the smallest numbers. The numbers 10 and 100, and 100 and 1000 are equally spaced. 

If the graph is redrawn using a standard scale, things look dramatically different:

The UK is still the second worst, but look how the gap between the UK (red line) and the USA (brown dashes) has dramatically widened, as has the gap between the UK and Germany (amber line). The death rates in Korea (blue line) and Japan (hidden by Korea) appear to be virtually zero. They’re not of course, but they aren’t yet in double digits.

Using a log scale tells a completely different story, and can be highly misleading.  I wonder whether the original graphic was deliberately designed to be misleading?

Note: The government’s figures came from John Hopkins University and Public Health England (PHE).  Mine are from the European Centre for Disease Prevention and Control (ECDC), so they might be slightly different.

This graph shows the value of R in Germany before they relaxed  their lockdown rules (the amber line) and after they were relaxed (the blue line). The red horizontal line represents an R value of one.  If R is higher than one the infection is still spreading exponentially. If it’s lower than one the spread is slowing and will eventually die out. The goal is keep the R value below one and to lower it as much as possible. 

The slight rise in the German COVID-19 R value on 27 April to just below one prompted news reporting  such as this in the British press:
“WAVE OF FEAR Germany faces having to bring BACK strict coronavirus lockdowns as cases surge just days after easing them”.
“Germany has seen a worrying rise in its coronavirus infection rate after becoming one of the first countries in Europe to start easing lockdown measures”

This sort of misleading, and frequently sensationalist, reporting is rife, ands gets repeated ad nauseam online, and particularly on social media. 

Unfortunately some people inform their decision making based on reading stories such as these, rather than relying on facts. 

For those who would like to know the source of my data, it’s taken from the website of the Robert Koch Institut (RKI) in Germany and is available in German and English:
https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Situationsberichte/Gesamt.html
The facts and figures on COVID-19 that the RKI publishes on a daily basis makes the UK’s efforts to do the same seem inadequate.

EDIT: I’ll be updating the graph on a regular basis. So far the R-value shows no sign of increasing