The public do not understand logarithmic graphs used to portray Covid-19
blogs.lse.ac.uk
blogs.lse.ac.uk
As a person who creates and looks at charts all day, I can read complex charts. But I really prefer other people use linear charts of simple bars or trend lines. You're conveying a new idea to me, so don't assume I have all the context you do when reading the chart.
If you want to show acceleration, remember to use different units. Choose a unit that can be shown on a linear scale. E.g., the ratio of today's cases over the cases from a week ago.
Your suggestion about changing what is represented in order to avoid a log scale is good but does not solve the root of the issue: many members of the public will not understand the information however it is represented because the concept itself is too complex.
It really is a numeracy problem.
When you look at the 2 graphs side-by-side, as in the article, it's apparent which conveys more meaning (the linear one), unless I suppose you read log graphs all day. The public does not.
Throwing more math, tech notes, or gentle introductions at the communication problem has never worked for me. What has worked is expressing the concept in the most "real" terms possible.
Epidemiologists are worried about exponential growth because it means hospitals will be swamped. That worry should be the topic when communicating with the public. How long until that's projected to happen? Maybe show the linear trend with a horizontal line for capacity and dotted line for a forecast of need. Put a huge red circle around where they intersect. Even better: just write "X days predicted until overrun."
Also, charts are terrible for reading data. They're good for comparisons, trends, and distributions. I only use them for exploring or summarizing. Tables are for readable numbers.
The second you use any of those words, people's eyes glaze over and there's an audible mumble sigh of "Ugh! Maths!"
It's sad, but it's the way it is.
Graphs should have a purpose and communicate information as clearly as possible. Scales and units should be chosen to most effectively convey information. Logarithmic scales are a poor choice for the information being displayed.
For a given set of parameters (of measures such as social distancing, mask wearing, weather, etc.) new infections will not rise by some specific, absolute number. Rather, similar environments result in similar rates of new infections as a percentage of existing, active infections.
Again graphs should serve one purpose. The purpose of those graphs is clearly, by the axis labels, supposed to display continuous deaths over a set period of time.
The linearly scaled graph displays this clearly, the logarithmic one does not. If the x-axis displayed into some future time, yes I'd agree a logarithmic scale may be more appropriate. But that would be displaying a graph of predictions at that point, which is something totally different than the two example graphs are showing.
One suggestion would be to make the logarithmic scale super-obvious and in your face.
"1 10 100 1k 10k 100k" in small print obscures the unusual nature of the scale.
Instead, show 1 10 100 1000 10000 100000 and show those numbers in a large bold font so that they are the most noticeable feature of the graph.
(Possibly use an increasing font size.)
What actually happened? Some people were shown linear data on a linear scale, others were shown the same linear data on a logarithmic scale. The people who saw a straight line, because the scale matched the data, were better able to interpret and extrapolate the data.
The spread of the novel coronavirus in the USA used to be exponential, but it was linear at the time the subjects were asked to analyse.
You don't say! Before the the authors recruited 2000 subjects to investigate that, maybe they could have enrolled in Physics Practical 101 and listened to the demonstrator. If they went to an old-school physics department, they would have seen some real semi-log graph paper, designed for people to read actual values off. It doesn't look anything like the scales on their graphs.
Oh, but the subjects who saw a linear graph were more likely to accept the authors' opinion on what to do about that data.
The authors are right: the USA and UK should do more to contain the coronavirus. But it's still propaganda to advocate that data be presented in a certain format because that makes readers agree with your opinion, even when your opinion is right.
> Admittedly, we cannot know which policy preferences are superior. However, we do know that unlike the people who saw the graph on a logarithmic scale, the people exposed to a linear scale graph can form their preferences based on information that they can understand better.
While they're using pandemic data, they're asking people about their basic understanding of data in the graph.
> The public do not understand logarithmic graphs used to portray Covid-19
- does the public include our leaders? Very likely.
- although I know what a log plot is, I didn't have an intuitive answer to the question posed in the article. So instead of informing people, it adds further confusion.
Related:
- the Santa Clara (Bay Area) hospitals dashboard is confusing and takes about 2 minutes to load, so another example of poor crisis communications - inexcusable in 2020:
https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx#ho...
If anybody is familiar with that BI software, is there a way to cache it?
I use them regularly (nearly every time I plot data to figure out trends or whatever), and have a hard time imagining not having them for problem solving.
Yesterday I was looking at a COVID-19 log graph and I was interested in a point of the curve right at the middle between the 100 and the 1000 tick mark. It's hard to have an intuition on what the value was.
edit: I double checked for the record, the value halfway between 100 and 1000 is 316.2.
I have seen all kinds of junk nonsensical charts in my career that somehow made it into reports, because nobody thought it was necessary to take the time to READ the chart and ask a few questions to see if it made any sense.