Seriously I had to look it up. This is daily COVID-19 data update XIV (14), day XX (20) of the pandemic, and day XCI (91) since the first cases were reported in Wuhan. Chinese health authorities are looking back at potential cases before COVID-19 was identified as a new disease, and they have found likely cases as early as CXXXV days ago (November 17, 2019, which was 135 days ago).

I hate Roman numerals, why did I decide to use them here?

Speaking of forced segues between slightly-related concepts, I’ve been noting encouraging news out of Italy, where the rate of new diagnoses is slowing down. But remember that COVID-19 is still a disaster in the only geographic unit that really matters, Earth. The disease has now reached even highly isolated South Sudan and the far-flung Northern Mariana Islands. COVID-19 cases worldwide continue their depressing exponential growth, as shown in the graph below. Nearly 800,000 people have been diagnosed and nearly 40,000 have died.

Cases and deaths in individual countries

As long as it continues to be useful and interesting, I will keep tracking case and death rates in eight countries: China, the United States, Iran, Italy, Spain, France Belgium, the United Kingdom, and Australia.

The graph of cases rates per country is first (diagnosed cases per million people), and the graph of deaths is next. See the legend at the bottom of each graph below to see which line represents which country. As always, suggestions on how to improve the graph are welcome.

Spain is running up the score on Italy in terms of cases per million people, and is on pace to become the leader in COVID-19 death rate soon. The case rate in the U.S. has passed that of Iran, and Belgium is nearly tied with France in death rate.

A word about China – the solid red line in both graphs. The flat line means either that they haven’t had any cases or deaths in a while, or that they are vastly underreporting their true cases, or both. And although I don’t trust the Chinese government any further than I can kick them, I think the amount of lying required to hide a raging epidemic in Wuhan or Guangzhou or Beijing is beyond even their ability to lie. There are enough foreigners with tunnel access to the open Internet that we’d at least be hearing about full hospitals and cemeteries from them. So I think we need to at least approximately take them at their word until we get evidence of additional Chinese cases from someone. I might remove China from the graphs starting tomorrow.

As always, I’m not an expert, I’m just a guy on the Internet who likes to make graphs of things. I hope I’ve shown you some ways you can look into COVID-19 data for yourself. 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” link), and you are welcome to use my Excel template.

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

While we wait for the start of the Imaginary Final Four on Saturday, imaginary college basketball goes on!

The NIT and CBI tournament first rounds have finished, and the second rounds are ready to begin. Here are the results, the brackets, and the upcoming schedules. First, the CBI.

College Basketball Invitational (CBI)

Results from Round 1:

Here is the updated bracket for the CBI – scrawled on a sheet of notebook paper because the CBI is a low-budget affair.

National Invitational Tournament (NIT)

The NIT first round is done, with only one major upset – and it’s a big one, as the East regional’s top seed, Indiana, lost to Radford. Here is the full list of results:

And here is the updated NIT bracket:

Upcoming schedule

Imaginary college basketball returns tonight with four NIT second round games, and continues tomorrow with four CBI and four NIT second round games, followed by the CBI semifinals in prime time.

Tuesday March 31st: NIT second round

8 PM ET: (1) Alabama vs. (5) Oklahoma State (South)
9 PM ET: (4) Syracuse vs. (8) Radford (East)
10 PM ET: (2) Minnesota vs. (3) Connecticut (Midwest)
11 PM ET: (1) Stanford vs. (4) Texas (West)

Wednesday April 1st: CBI second round

8 AM ET: (3) Furman vs. (6) Clemson
9 AM ET: (2) Xavier vs. (7) UNC Greensboro
10 AM ET: (4) Georgetown vs. (12) Georgia
11 AM ET: (1) North Carolina vs. (9) Missouri

Wednesday April 1st: NIT second round

Noon ET: (2) NC State vs. (3) Rhode Island (East)
1 PM ET: (1) Northern Iowa vs. (5) Akron (Midwest)
2 PM ET: (2) Oklahoma vs. (3) Purdue (West)
3 PM ET: (2) Arizona State vs. (3) North Texas (South)

Wednesday April 1st: CBI semifinals

8 PM ET: North Carolina / Missouri vs. Georgetown / Georgia
10 PM ET: Xavier / UNC Greensboro vs. Furman / Clemson

Watch it all happen live at @fixthemadness!

Day thirteen of me graphing data, day nineteen of the pandemic (as declared by the World Health Organization), day ninety since the first cases were reported in Wuhan. Worldwide as of 5:45 AM ET this morning, more than 700,000 people have been diagnosed with COVID-19, and more than 33,000 have died.

Yesterday I posted graphs of the total number of cases and deaths worldwide. Today the number of cases and deaths continues on the same trend as before. On the level of national data, I am continuing to track the number of cases and deaths in China, the United States, Iran, Italy, Spain, France, Belgium, the United Kingdom, and Australia. The graphs below show cases and deaths per million people in each country. As always, suggestions on how to improve the graphs are welcome.

Cases per million people

Spain has taken the lead over Italy as the country with the most cases of COVID-19 per million people, with 1,673 cases per million versus 1,622 per million in Italy. Belgium has moved into third place with 940 cases per million people. And the growth rate in the U.S. (blue dotted line) continues to increase.

Deaths per million people

Italy still leads the world in per-capita deaths, with 179 deaths per million people. Belgium has overtaken France as well.

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” link). And here is my Excel template.

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

Just because all sports have been cancelled due to our impending doom doesn’t mean that we have to give up sports.

For the past three weeks, I’ve been simulating the NCAA college basketball tournament, which would have been happening right now all over the country. On Sunday, March 15th, I announced the 68 teams that would play for the national championship of college basketball.

Over the last three weeks, we’ve seen some exciting games, buzzer beaters, and shocking upsets. From 68 teams, we are down to four. The Final Four teams are: East Tennessee State, Creighton, Duke, and Oregon.

Here is the bracket leading in to the Final Four:

Final Four Schedule

The schedule of Final Four games is:

As always, results will be posted in real time (what would have been real time) on my Twitter feed at @fixthemadness. But there’s no reason we have to go without imaginary basketball between now and Saturday! I will also be simulating two other postseason tournaments: the National Invitational Tournament (NIT) and the College Basketball Invitational (CBI).

Here are the bracket and schedules for these two tournaments, starting with the NIT.

NIT Bracket and First Round Schedule

Monday March 30th

Noon ET: (3) Rhode Island vs. (6) Tennessee (East)
1 PM ET: (4) Syracuse vs. (5) Yale (East)
2 PM ET: (1) Alabama vs. (8) Prairie View A&M (South)
3 PM ET: (3) UConn vs. (6) South Carolina (Midwest)
4 PM ET: (2) Oklahoma vs. (7) Eastern Washington (West)
5 PM ET: (4) St. John’s vs. (5) Akron (Midwest)
6 PM ET: (3) North Texas vs. (6) SMU (South)
7 PM ET: (4) Texas vs. (5) Oregon State (South)
8 PM ET: (4) Memphis vs. (5) Oklahoma State (South)
9 PM ET: (1) Indiana vs. (8) Radford (East)
10 PM ET: (2) NC State vs. (7) Colgate (East)
11 PM ET: (3) Purdue vs. (6) Washington (West)

Tuesday March 31st

Midnight ET: (2) Minnesota vs. (7) Davidson (Midwest)
1 AM ET: (1) Northern Iowa vs. (8) Arkansas-Little Rock (Midwest)
2 AM ET: (2) Arizona State vs. (7) Virginia Commonwealth (South)
3 AM ET: (1) Stanford vs. (8) Wright State (West)
8:40 PM: (12) USC vs. (12) Mississippi State (East regional play-in game, Dayton)

CBI Bracket and Schedule

The CBI is low-budget, here’s the bracket handwritten on a sheet of scratch paper:

Tuesday March 31st

4 AM ET: (7) UNC Greensboro vs. (10) Utah
5 AM ET: (3) Furman vs. (14) Kansas State
6 AM ET: (5) Tulsa vs. (12) Georgia
7 AM ET: (6) Clemson vs. (11) Duquesne
8 AM ET: (2) Xavier vs. (15) Loyola-Chicago
9 AM ET: (8) DePaul vs. (9) Missouri
10 AM ET: (4) Georgetown vs. (13) Virginia Tech
11 AM ET: (1) North Carolina vs. (16) Northern Colorado

Twenty-four straight hours of college basketball starts right now!

Watch it happen live at @fixthemadness!

Over the last twelve days, I have been tracking the number of cases and deaths from the COVID-19 pandemic across various countries. I will continue to do that as long as it is useful. But this morning I asked a question – what’s the graph that I haven’t made yet?

More important than the data for individual countries is the data for the world as a whole. We are all passengers together on Spaceship Earth. So how does it look for us so far?

Worldwide COVID-19 cases per day

Worldwide COVID-19 deaths per day

Aw shi—

Day twelve of me graphing data, day eighteen of the pandemic (as declared by the World Health Organization), day eighty-nine since the first cases were reported in Wuhan. Worldwide as of 5:30 AM ET this morning, more than 650,000 people have been diagnosed with COVID-19, and more than 30,000 have died. For comparison, that is nearly 10 times the number that died in the 9/11 terrorist attacks.

I am continuing to track the number of cases and deaths in China, the United States, Iran, Italy, Spain, France, Belgium, the United Kingdom, and Australia. As always, the graphs below show cases and deaths per million people in each country.

I have redone the graphs, so they are not directly comparable with the ones I’ve made before, but they show the same countries with the same lines. I also set the horizontal axis (date) to always show the current date on the far right, so that you can tell by just looking at the graph what day it comes from.

Hopefully the graphs are more readable today as well. Click on them to open a larger version in a new tab. Suggestions welcome!

Cases per million people

Countries are shown on the same color scale as before, but I have rescaled the graph. The highest case rate in the world is Italy’s at 1,535 per million (80,539 cases in about 60,000,000 Italians).

The vertical axis scale (cases per million people) in my graph now extends to 3,000, so there is now some room for the graph to grow into. But since the doubling time of cases is about 3 days, this room is likely to only last about 3 days, and then I’ll have to rescale again.

That’s what doubling time means – in three days, as many people will have caught COVID-19 as have ever caught it since it began at the seafood market in Wuhan.

Looking at patterns in individual countries, the number of reported cases in Spain continues to grow at a frightening rate. The cases per million people in Spain has not quite passed the cases per million in Italy (which was my prediction yesterday), but it’s damn close, and Spain will certainly take over the top spot tomorrow. The rate seems to have slowed down in Australia, but the same caveats apply.

It looks like the rate has started to increase again in Iran, but that could be due to better testing and reporting, and it could be random chance. Let’s keep a close eye in Iran over the next few days.

Deaths per million people

Sigh, I rescaled the graph yet again, and I hope the new rescaling will last three days before I have to do it yet again (remember, three day doubling time, and it might be even faster). The death rate is now 166 per million in Italy and 121 per million in Spain.

Per capita death rate has some lag behind per capita case rate – the time it takes patients to get sick and die.

My goal in doing this it to help you realize that you can make these kinds of graphs yourself. Links that will help you do that are in the postscript.

I’ll leave you with a question:

What important graph have I not yet shown you?

I’ll answer this, and show you the graph, later today.

Postscript: Data Resources

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” link).

I have revised my Excel template make the graphs above, plus the secret one I’m working on. It should also be easier to add new data each day, although it still takes several manual steps. Here is the new template.

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