Visualising change

Who knows how all this will end, it’s all guesswork. Will the final figures for the UK be between 7,000 and 20,000? Perhaps as high as 66,000? Depends on your model. Can we at least say for certain that this will end at some point? Are things already slowing down?

Three graphs that show a global slowdown in COVID-19 deathsThe Conversation
Other published graphs have shown the number of deaths reported each day for various countries. These are more useful, but the reader is still left trying to discern the extent to which the rise from one day to the next is larger or smaller. The graph below is different. It shows both the number of deaths each day and the rate of change in that number. Most importantly, it uses smoothed data – a moving average from the day before to the day after each date shown.

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OK. I think I follow that.

Here’s something simpler that caught my eye, a way of looking at one of the (positive?) effects of this pandemic.

Traffic data shows how rush hour has all but disappeared in major cities in Britain (and ROW)Reddit
No more rush hour. Declining vehicle usage in cities across the world means journeys at rush hour are almost as quick as those in the middle of the night.

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No easy answers

How bad will this get? It’s a simple enough question…

Why it’s so freaking hard to make a good COVID-19 modelFiveThirtyEight
The number of people who will die is a function of how many people could become infected, how the virus spreads and how many people the virus is capable of killing.

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Straightforward enough, but the trouble begins when you try to fill in the numbers. Look at the factors and assumptions within just the fatality rate, for instance.

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Think of it like making a pie. If you have a normal recipe, you can do it pretty easily and expect a predictable result that makes sense. But if the recipe contains instructions like “add three to 15 chopped apples, or steaks, or brussels sprouts, depending on what you have on hand” … well, that’s going to affect how tasty this pie is, isn’t it? You can make assumptions about the correct ingredients and their quantity. But those are assumptions — not absolute facts. And if you make too many assumptions in your pie-baking process, you might very well end up with something entirely different than what you were meant to be making. And you wouldn’t necessarily know you got it wrong.

There are so many factors as play here. This is the model they end up with. It’s one version, at least.

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Over the next few months, you are going to see many different predictions about COVID-19 outcomes. They won’t all agree. But just because they’re based on assumptions doesn’t mean they’re worthless.

“All models are wrong, it’s striving to make them less wrong and useful in the moment,” Weir said.

See also.

Six unknown factors in coronavirus models and how they could affect predictionsThe Conversation
Since the global outbreak of COVID-19, researchers have scrambled to develop and share models which can predict how the virus will spread. This is inherently tricky, as we know so little about the disease, and a model is only ever as good as the information you put into it.

Excel and the cat’s whiskers

Excel Box and Whisker Diagrams

Excel box and whisker diagrams (box plots)
Box and Whisker Charts (Box Plots) are commonly used in the display of statistical analyses. Microsoft Excel does not have a built in Box and Whisker chart type, but you can create your own custom Box and Whisker charts, using stacked bar or column charts and error bars. This tutorial shows how to make box plots, in vertical or horizontal orientations, in all modern versions of Excel.