Graphs day 70, pandemic day 76, day 147 since the first cases were diagnosed.
Total cases of COVID-19 diagnosed worldwide: 5,459,526
Total deaths: 345,944
Cases and deaths worldwide
I am continuing to track the predictions that I made on May 17th, based on data from April and the first half of May. We hit five million global cases a day early. Up next is six million cases, which I predicted would happen next Thursday, June 4th – and will almost certainly happen sooner. I figured out how to get Excel to forecast a trendline ahead, so I can compare my predictions (the black line in the graph below) to reality (the red dots from May 17th to today). We are, sadly, far ahead of schedule, and getting farther ahead every day.
The good news is that we are running slightly behind my predictions of the number of deaths. I had predicted 400,000 deaths on this Sunday, June 1st. It might still happen then, or it might happen a bit later. I would be happy to be wrong about this, because it would mean less dead people by this time next week. Less dead people is good, I hope that’s not controversial.
The maps are back today (yay!) and day 70 is an even number, so we’ll look at case and death rates on a relative scale, with day zero being the date on which each country’s case rate reached one in 1,000,000. Both case and death data are given below, but I’d like you to focus particularly on deaths for reasons I will explain in a moment.
Cases per million people by country
I’ve started referring to our usual group of countries – the United States, Spain, Italy, the United Kingdom, Belgium, Russia, Sweden, Brazil, Saudi Arabia, and India – as the Big 10. Unlike the Big 10 of college football, this Big Ten actually has 10 entities.
Maps of case rates in the Big 10 plus several other countries:
And the history of cases per million since each country’s day zero:
It’s now day 80 in the U.S., and we are ahead of where every other country was on its day 80.
Deaths per million people by country
Here’s the map of deaths per million people by country:
Note that Sweden now has 10 times the death rate of neighboring Norway.
Today’s most interesting data comes from the graph of deaths per million people in each of the Big 10 countries. See if you can spot something that looks incredibly weird here:
This is a graph of cumulative deaths in each country – so what’s up with Spain, where the curve goes DOWN at day 86? Have people come back to life? Is it a miracle? Are there now zombies roaming the plain in Spain?
Obviously not – it’s an adjustment to the data. Some deaths that had been previously classified as being due to COVID-19 have been reclassified as being due to other causes. The adjustment changed the total number of COVID-19 deaths in Spain (remember, this is total, not per million) from 28,752 to 26,384.
That’s a six percent adjustment to Spain’s total, and not even a blip to the global totals because another 5,000 people died yesterday and the global total still went up.
This adjustment is important because there are persistent ridiculous conspiracy rumors that every country is inflating its COVID-19 death count by intentionally classifying non-COVID-19 deaths as being due to COVID-19. They are doing this to make COVID-19 appear like a bigger problem than it actually is, because… reasons. I’m not clear on that, and I don’t think they are either.
Spain just bid adiós to those conspiracies by adjusting their numbers down to better reflect reality as we now understand it. And for people who say that this adjustment just proves there is a conspiracy – well, which is it? Are numbers intentionally overreported or intentionally underreported? Would you like some to have some of the delicious cake that you just finished eating?
A milder form of this objection is making an adjustment to the data just proves that all the data is unreliable anyway, and I’m wasting my time even trying to graph it. First, dude, seriously? If you’re reading this blog, you probably know me and don’t mean to insult me – and even if you do, well, it was never about me.
Setting that aside, I can see why someone would ask that question, but actually the adjustment proves exactly the opposite – that they are doing everything they possibly can to get it right. Scientists don’t try to hide their mistakes, and a scientist’s first duty is always to the truth.
If you still think the data is useless, I’ll ask a question I often ask: what’s the alternative?
Would you prefer that they not adjust the data, and just stick with data that they once thought was correct but now know to be incorrect?
Are you proposing that everyone should always get it right the first time, and that anyone who changes their mind is completely unreliable? If so – then, since I know you’re the kind of person who would never be hypocritical enough to hold someone else to different standards than yourself – how is the “always get it right the first time” approach going for you?
Are you instead saying that since the data is unreliable, we should just give up? And not only ignore the data, but also ignore 300+ years of medical knowledge on how to stop epidemics in favor of useless half-measures like “wear a mask, but only when you feel like it?”
I continue to stand behind the data I am using here as the best estimate we have for the extent of COVID-19 in the world, and I continue to stand for using it to make the best decisions we know how to make.
If you want to try any of this analysis for yourself, you can get the data that I used to make these graphs from the European Centers for Disease Control’s Coronavirus Source Data; choose “all four metrics.” You are welcome to use my Excel template (version 3.3). I’d love to see what you can build with it, and I’m happy to help you figure it out!
Update tomorrow, and every day after that until this pandemic comes to an end.