Coronavirus trajectory tracker explained
The FT's senior data-visualisation journalist John Burn-Murdoch explains the must-see daily graphs, which show how cases and deaths are growing around the world
Produced by Tom Hannen
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JOHN BURN-MURDOCH: A lot of people have been asking why we designed and built the FT's Coronavirus Trajectories Tracker. And some of these questions come up time and time again, so we just wanted to take five of these and go through the explanations with you today.
Question number one is, why are we using a log scale, a logarithmic scale, on the y-axis, the vertical axis? Viruses spread exponentially. So by that, we mean it doesn't go from one person infected today, then two, then three, then four. It's more like one, then two, then four, then eight. It rises at an ever-increasing, ever-accelerating rate. And so the great thing about log scales is that they naturally take that into account. So instead of a line that looks a bit like a hockey stick and shoots up into the sky, you get a nice straight line.
And now, some people will counter and say, well, doesn't that mean that people are going to be less concerned? They're going to think this is only going up at a steady pace, rather than an exponential one. But I'd say a couple of things to that. The first is that what we want to do with these charts is to inform people and make people aware of the severity of the issue, but not to panic people.
And so by showing this on a straight line, we're emphasising that there's an inevitability about how coronavirus spreads. So most countries we're seeing are on this line of cases doubling every two, three, four days. And we want to emphasise that, even if there are only a few cases in your country today, based on all the data we have, you will end up going along that path, the same path that the likes of Italy and Spain have been on so tragically.
So yeah, with the log scale, we're not trying to play down the rate at which it increases. We're trying to emphasise that the exponential nature of this spread is something that we see everywhere, and we're trying to make it easier to see here's where you are today, here's where you might be in five, six, seven days, and how does that compare to other countries, whose cases you'll be familiar with, where they were at the same stage.
The second question I often get asked is, why aren't we adjusting for countries' population sizes in this chart? So this one is a bit more of a judgement call. What we have with this virus is something which spreads at a fairly consistent rate regardless of the situation on the ground. We tend to see over a certain number of days the same number of cases, after day one, day two, day ten, et cetera.
And that's because this virus, it does spread fast, but it doesn't, you know, ripple through a country's entire population in a matter of days. So the overall population of a country is not any sort of limiting factor on how fast it spreads. It will tend to spread as the people in those cities, in those areas mix at similar rates at the same rate.
Now, we could, of course, still adjust for population, and give you sort of per capita or per million people numbers of cases or deaths. What that would do is essentially just make larger countries look like their outbreaks aren't quite as bad, and smaller countries look like theirs are much worse. With this chart, we're focusing on trajectory. We're focusing on saying, where are things right now, where are they going to be in a few days, and how does this compare to other countries that you're already familiar with from following the news.
So if we changed to per capita, the slopes wouldn't actually change. All that would change is the vertical positioning of different countries' lines. And they would change in such a way that, for example, the American outbreak would look less alarming than it is, and the Danish or Swiss outbreaks would look worse. The numbers that come up in the news, and the numbers that we as humans instinctively react to are numbers of people, numbers of deaths.
I think if we start moving into per capita, per million people rates, first of all, you lose a bit of the immediacy, a bit of the sort of visceral nature of these numbers. We would lose that connection with the numbers that we're seeing in the news. We're hearing about hundreds and thousands of people being infected and dying tragically in countries like Italy and Spain. And I want people to be able to see on that y-axis where they are in relation to that, not where they are in relation to some more abstract number, which loses, as I say, some of the sort of emotional power that I hope this chart has.
So another of the questions we get asked is, isn't there an issue when we talk about numbers of cases, where the number of confirmed cases in a country is more a function of its testing regime than of the actual number of people infected? We need to be very clear about referring to confirmed test cases, and not just the number of cases, because of course, much as our governments are all trying to test as many people as they can, there are going to be hundreds, thousands of people in countries all over the world who do have coronavirus.
They may be completely symptom-free, but they've not yet been tested. And so in the earlier versions of our chart, showing the case trajectories, the y-axis title talked about the cumulative number of cases. Now, a few days ago, we actually changed that to the cumulative number of confirmed positive tests, and not ground truth in terms of number of cases.
So another thing people have asked is, should we not be showing some indication of when countries actually started imposing their various measures to get the virus under control? We immediately felt, yes, we should be doing something here. We need to emphasise when Italy, France, Spain, and so on asked their citizens to be confined to their homes, partly, you know, just to add that important context to the chart, but also because it's then going to be very interesting for us to be able to look at when do those curves hopefully start flattening down, bending down after lockdowns have been put in place. Because of course, the number of deaths, for example, in a country isn't going to start flattening overnight after a lockdown has been instituted, because it takes two weeks or more for someone to go from being infected with the virus to dying, if they unfortunately reach that stage.
Another thing we've been asked over the last few days is, can we, as well as showing these national numbers of cases and deaths, go down into countries and look at specific regions? The virus tends to spread in small, but gradually growing pockets. This tends to come from one outbreak and spread from there.
So initially, of course, this all started in the city of Wuhan in China. We then saw a nasty outbreak in Daegu in Korea, and then Lombardia was the worst affected region in Italy. So we wanted to get into that with this chart, and look at how different regions have been affected, rather than countries as a whole. When you think about the impacts of the lockdowns that are now being put in place, we're really talking about cities, which are usually these vibrant, dynamic, busy, noisy hubs, falling silent.
We're going to be updating these charts, and any charts that we add, daily. So if you have any more ideas for features that we should consider adding or changing, then please give us an email or a tweet. And for the latest versions on the charts, you can go to ft.com/coronavirus-latest.