Day eight. Once again presenting the graphs of COVID-19 cases and deaths per million people for various countries that have been discussed in the “news” in the last few weeks. Remember that these are per-capita graphs, which make the data easier to interpret in some ways and harder in some other ways.

Some good news and some bad news in today’s charts. First, the charts:

Cases per million people

Deaths per million people

The bad news comes from the Deaths per million people graph. Italy is now literally off the chart. For the past few days, I have been plotting the vertical axis (deaths per million people) between 0 and 75, but the cumulative death rate from COVID-19 in Italy today has hit 113 per million (6,820 deaths so far in a country of 60 million people). I reset the scale to run from 0 to 120 cumulative deaths per million people. I fear I will likely have to reset the scale a few more times before the dying levels off.

The maybe good news might come from the graph of cases per million people. It looks like the slope of the line for Italy is starting to turn over. While the total number of cases in Italy is still increasing because new cases are still being reported, fewer new cases are being reported today than a few days ago. Some experts (which I am not) have interpreted this as showing that social distancing measures in Italy have begun to work. We’ll see if this trend continues.

As always, I’d love to hear your thoughts. You can find the data from the European Centers for Disease Control’s Coronavirus Source Data site (download the CSV file from the “Full dataset” lin), and you are welcome to use my Microsoft Excel template. Some of you have sent me graphs and ideas (hi David! hi Aimee! Hi Ed!), and I’ll respond to you once I’m more caught up on my Actual Job.

Update tomorrow, and every day until this f@cking terrible pandemic is over.

Day seven of me doing this. You all seem fairly comfortable with the graphs of cases and deaths per million people for various countries, so those are the graphs I’ll show today. But please remember that these are per capita, so low values here for the U.S. and China still represent a lot of cases and deaths.

I also realized that the per-capita graphs contain a bit of an optical illusion, making it look like the line for China is going down. That is of course impossible – these are cumulative total cases, so the numbers can only either stay the same or go up as new cases are reported. I’ll look at ways to make this clearer in tomorrow’s update.

Cases per million people

Reported rates of COVID-19 continue to grow at an alarming rate throughout Europe, and are approaching that growth rate in the U.S. as well. Case rates in Iran, the U.K., and Australia are growing more slowly.

I am wondering if, instead of total numbers of diagnosed cases, I should be graphing the number of new cases diagnosed each day. That would mean that people diagnosed in the past who have recovered would not be included on the graph, and it would also make it more directly comparable with the “flatten the curve” diagrams that many people are sharing.

Deaths per million people

Countries that have recently seen an increase in reported cases per million people are just now beginning to see an increase in reported deaths per million people. These numbers are likely to increase as more time passes.

For this plot, I’m pretty sure that cumulative deaths is the right thing to graph, because once someone becomes dead, they stay dead.

Remember the purpose of all of this – the data are out there, and you can understand it with the tools that you already have. You can find the data from the European Centers for Disease Control’s Coronavirus Source Data site (download the CSV file from the “Full dataset” lin), and you are welcome to use my Microsoft Excel template.

Update tomorrow, and every day until this pandemic is over.

Day six of me doing this. Same four graphs as usual, same color scale as usual. The United States has now passed China in terms of all-time COVID-19 cases per million people.

Total cases

Total deaths

Cases per million people

Deaths per million people

Remember the purpose of this – the data are out there, and you can understand it with the tools that you already have. You can find the data from the European Centers for Disease Control’s Coronavirus Source Data site (download the CSV file from the “Full dataset” lin), and you are welcome to use my Microsoft Excel template.

Update tomorrow, and every day until this pandemic is over.

Day five of me doing this. Since yesterday, another 34,000 people worldwide were diagnosed with COVID-19, and another 1,700 died.

Several friends asked me to plot cases and deaths per capita, so we can get a sense of infection rates across different countries. I’ve done that, and I’ll show those graphs further down the page. But it’s important to be able to directly compare these graphs between one day and the next.

So, while I think the per capita graphs will end up being more useful, for the time being I will continue to show the plots of absolute numbers as well.

Below is the total number reported cases of COVID-19 by country. I have removed South Korea, since the disease appears to be well-contained there. I have replaced it with the United Kingdom, where the number of cases is likely to increase significantly (but that’s a testable hypothesis, we’ll see in a few weeks). The line for the UK is the same light blue color as South Korea, but now has a dot-dash pattern. I also added Australia (gray dot-dot-dash line), where there is also reason to believe that cases will increase.

And here is the graph of absolute number of deaths by country – same countries, same color schemes. The uptick in deaths in the United States that I pointed out yesterday continues today.

COVID-19 cases and deaths per capita

Looking at absolute numbers of cases is important, but when comparing China (which has about 1,400,000,000 people) to Belgium (about 11,000,000), they can give a misleading sense of how far the disease has spread in different places. A better measure could be to look at how the number of cases (or deaths) compares to the population of the country.

The graph below shows the number of reported cases of COVID-19 per million people for each of the countries shown in the other graph. Current values vary between 43 cases per million people in Australia to nearly 900 per million in Italy. This graph looks different from the one graph of total cases. And when you look at the lines for Italy, Spain, and France, you can see why Europe is being described as the new epicenter of infection.

Note that I also changed the scale of the horizontal axis on this graph. The ones above were from February 15th to today, while the ones below show all cases since the first ones were reported on December 31, 2019.

Here is the graph of deaths per million people – same countries, same color schems:

Since COVID-19 is transmitted by person-to-person contact, a better comparison might be population density rather than absolute population. I’ll look at that later. I’m also playing with some simple curve fitting models, but I’m a long way from being ready to share any of those.

Remember: I’m not an epidemiologist, and not even any kind of healthcare worker. I’m just some guy on the Internet that likes to graph things. Listen to the actual experts. And as always, follow the recommendations of your regional health authorities (if you’re in the U.S., follow the CDC recommendations).

What I hope I can contribute to the effort is to help you to realize that data about the virus are publicly available, and that you have access to the tools to understand the trends for yourself. I get the data from the European Centers for Disease Control’s Coronavirus Source Data site (even though it’s a European entity, the reports are from all over the world). I download the CSV file from the “Full dataset” link. I make my graphs in Microsoft Excel using this template.

Update tomorrow, and every day until this pandemic is over.

Who will make the Sweet 16 in our imaginations?

Find out half the answer today at @fixthemadness!

Here is the bracket as it stands now:

Here is today’s schedule:

Here is the schedule for today’s Round of 32 games, the legacy of a day of #Upsets and #Cinderellas:

Noon ET: (6) Kentucky vs. (14) Hofstra (Midwest, Greensboro)
1 PM ET: (3) BYU vs. (11) Rutgers (South, Cleveland)
3 PM ET: (1) Duke vs. (8) Marquette (South, Omaha)
4 PM ET: (7) St. Mary’s (CA) vs. (15) UC Irvine (West, Sacramento)

7 PM ET: (5) Seton Hall vs. (13) Bradley (East, Greensboro)
8 PM ET: (1) Dayton vs. (9) Richmond (East, Cleveland)
9 PM ET: (1) Kansas vs. (9) Auburn (Midwest, Omaha)
10 PM ET: (4) Arizona vs. (5) Ohio State (Midwest, Sacramento)

Let the madness continue!