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Pushing the Limits (Daily COVID-19 data update CLII)

Graphs day 152, pandemic day 159, day 229 since the first cases were diagnosed.

Total cases of COVID-19 diagnosed worldwide: 21,239,780

Total deaths: 767,692

I am continuing to use data retrieved by the Corona Data Scraper, which collects online reports from county, state, and national health departments all over the world. I am getting worried that I might be approaching the limit of what I can do with Excel running on my laptop. I could easily make these graphs in Python with SciServer or Kaggle, but that would be a wasted opportunity. There’s a reason I’ve been making these graphs in Excel all along – I want to show you how you can study the COVID-19 pandemic using a tool you probably already have and probably already know how to use.

If you know anything about how to speed up computation in Excel, or if you know of any other resources I can bring to this, please let me know! Comment here or reach out to me in one of the ways you know how to reach me.

Today’s graph compares some of the major global hotspots, and adding a new one today: the Atlanta metropolitan area.

COVID-19 in some of the hotspot areas worldwide

Just when it looked like the epidemic in Florida was getting better, cases are back up again in Miami. We’ll keep watching closely.

Want to give it a try? Please do! Here is my new spreadsheet (version 8), although God help you until I document it better. The good news is that you should only need to change the worksheet called Graphs, and only refer to the sheet called Daily to get the codes for each country. Also be warned, it’s so big that it calculates sloooooooooooooooowly. You will probably want to go to Settings -> Calculation and change Calculation Options to Manual. Then the spreadsheet will only calculate its updated numbers when you tell it to, by pressing F5 on Windows or Shift-Enter on Mac.

Pandemic updates tomorrow, and every day until the pandemic ends or I do.

Meanwhile in Australia (Daily COVID-19 data update CXLVIII)

Graphs day 148, pandemic day 155, day 225 since the first cases were diagnosed. And we’ve hit another milestone.

Total cases of COVID-19 diagnosed worldwide: 20,097,141

Total deaths: 748,616

A man lays down back-to-back with a kangaroo

Today, let’s take a look in detail at another country: Australia.

The epidemic in Australia has come in two waves. The first wave began in late February and peaked in late March. The second wave began in June and seems to be slowing a bit, but not even close to enough that we can declare it passed. But looking in more detail reveals a difference between the two waves; see the graph below. The first wave had cases all over Australia, while the second wave has been almost completely confined to one state: Victoria.

Australia consists of six states and three territories – yes, they’re called states rather than provinces. And like any county of states, there is plenty of good-natured trash talking among the states, and lately the other five states have had enormous fun at Victoria’s expense.

And while Victoria is the hot zone of Australia, let’s keep it in perspective. Victoria has about the same population as the U.S. state of Maryland. So as a comparison, I added Maryland to the graph, along with the usual comparison of Hubei Province in China.

The graph is below. We’re back to the usual format with labels, format explained below.

COVID-19 in Victoria (42 deaths per milion people), the rest of Australia (3 dpm), Hubei (78 dpm), and Maryland 596 dpm)

The main graph is on the traditional regular scale, from zero to 200 new cases diagnosed per day per million people. Each region gets a unique color in each graph: Hubei is blue, Victoria is green, the rest of Australia is red, and Maryland is purple. Line labels show the name of the region, and also the mortality rate (cumulative deaths per million people) in the region – cumulative because the dead stay dead. The thickness of the lines and the size of the labels depend on the cumulative case fatality rate – the number of people who died divided by the number diagnosed.

Victoria has had it far worse than the rest of Australia, but similarly-sized Maryland has had it even worse than that.

Want to give it a try? Please do! Here is my new spreadsheet (version 8), although God help you until I document it better. The good news is that you should only need to change the worksheet called Graphs, and only refer to the sheet called Daily to get the codes for each country. Also be warned, it’s so big that it calculates sloooooooooooooooowly. You will probably want to go to Settings -> Calculation and change Calculation Options to Manual. Then the spreadsheet will only calculate its updated numbers when you tell it to, by pressing F5 on Windows or Shift-Enter on Mac.

Pandemic updates tomorrow, and every day until the pandemic ends or I do.

Shop Local (Daily COVID-19 data update CXLVII)

Graphs day 147, pandemic day 154, day 224 since the first cases were diagnosed. Remember that Very Exciting New Idea that I was talking about last week? Here it is!

I’m going to skip the overall global numbers for today, because I want to make sure I understand what I’m presenting to you. I’m going the other way today – looking at numbers at an unprecedentedly local scale.

To enable this more focused look, I’ve changed data sources. I’m now using data provided by the Corona Data Scraper global citizen science collaboration. It’s not their data, of course, it’s our data – data reported by hundreds of national, state, and local health departments. The Corona Data Scraper simply crawls the Internet and downloads the latest data from each of these hundreds of local sources.

If you don’t believe the U.S. Centers for Disease Control (CDC) or the World Health Organization (WHO) – first of all, why? That’s like wanting to see a basketball game but refusing to watch anything from the NBA, the NCAA, the Olympics, high schools, Eurobasket, or the Chinese Basketball Association. But if you’re determined to not believe the experts, you no longer have to! All the numbers come from local sources all over the world.

This kind of distributed data collection is simple, but it’s not easy. Volunteers all over the world have spent countless hours writing software and communicating with health departments and other volunteers. And it hasn’t been easy on my end either. I’ve spent probably 35 hours the past two weeks – including almost all day on both Saturday and Sunday – turning Corona Data Scraper reports into an Excel spreadsheet. A four-sheet, 900,000+ line, 64 MB Excel spreadsheet.

And it’s all worth it to show you this graph.

It’s a much simpler version of the graphs that I’ve been showing you – the lines are about equal thickness and there are no data labels; instead I use different styles of dashed lines along with color to show you which regions are which.

The difference? Instead of showing the case rate for the entire countries of the U.S., China, Italy, and Switzerland, I show you the case rates only for specific, hard-hit areas of those countries. In the U.S.: the metropolitan areas of New York City (purple dotted line) and Miami (orange solid line). In China: the province of Hubei (blue long dash), whose capital is the infamous Wuhan. In Italy: the region of Lombardy, home of the Milan metropolitan area, the largest in Italy. In Switzerland, the canton of Geneva.

Cases reported per day per million people in each of five particularly hard-hit regions

I’m damn proud of this.

And this shows just one basic answer to one of the incredible variety and depth of questions that the Corona Data Scraper dataset can help us understand together.

Much, much, much more to come.

Want to give it a try yourself? You can get all the data from the Timeseries CSV link of the Corona Data Scraper website. Let me clean up my spreadsheet and share it as version 8 tomorrow.

Pandemic updates tomorrow, and roughly every day after that until the pandemic ends or I do.

19 million cases (Daily COVID-19 data update CXLV)

Graphs day 145, pandemic day 152, day 222 since the first cases were diagnosed. Remember that Very Exciting New Idea that I was working on last week? I’ve spent almost the entire weekend working on it, and It’s almost done – you’ll definitely see it this week! For today, here’s a quick update on COVID-19 numbers around the world.

Total cases of COVID-19 diagnosed worldwide: 19,637,506

Total deaths: 726,781

Happy Independence Day to Singapore, we’ll include their numbers in today’s graphs. And some countries have changed categories today.

Usual graphs and labels for all five categories today. All five graphs are in the usual styles. The main graph is on the regular scale, from zero to 200 new cases diagnosed per day per million people. Where there are smaller inset graphs, they are on the “Qatar scale,” which runs from zero to 700 cases per million people. Each country gets a unique color in each graph (although the colors can repeat across graphs). Line labels show the name of the region, and also the mortality rate (cumulative deaths per million people) in the region – cumulative because the dead stay dead. The thickness of the lines and the size of the labels depend on the cumulative case fatality rate – the number of people who died divided by the number diagnosed.

Regions where COVID-19 was quickly contained

Regions where COVID-19 was quickly contained

No changes to this category. In fact, New Zealand has now gone 100 days without community transmission (virus transmission from one person to another within New Zealand). That is an incredible achievement.

Regions where COVID-19 is currently under control(-ish)

Regions where COVID-19 is currently under control

The last two weeks have seen a worrying increase in cases in France, but not enough to move France out of the under control category.

Regions moving in the right direction(-ish)

Regions where cases are decreasing

Welcome to getting better, Serbia!

And the rate of new cases reported in Sweden continues at a level lower than Russia and Saudi Arabia. Sweden took a risk by having less restrictive social distancing laws than nearby countries. Is the risk paying off? Not so far – even though cases are low right now, the death rate in Sweden is far higher than other countries. Sweden is playing the long game, betting that in the long run their approach will be more sustainable and deaths in other countries will inevitably catch up. We’ll see. The long game is the only game worth playing.

Regions experiencing a second wave of COVID-19 cases

Regions experiencing a second wave of COVID-19

This is the graph where Singapore goes, where cases have been increasing since early July. Also, it’s been a while since we’ve checked in with Iran, where cases started to increase in late April but have stayed at a fairly low level since.

Regions where the first wave of COVID-19 continues to get worse

Regions where things are getting worse

Reported cases continue to decrease in Florida.

Want to give it a try? Please do! Here is version 7.2 of my spreadsheet.

Pandemic updates tomorrow, and every day until the pandemic ends or I do.

Georgia on my mind (Daily COVID-19 data update CXLIII)

Graphs day 143, pandemic day 150, day 220 since the first cases were diagnosed.

I can’t believe it’s been CXLIII days and I haven’t made this joke yet, but let’s look at COVID-19 cases in Georgia. And Georgia.

But first, we hit another milestone number today:

Total cases of COVID-19 diagnosed worldwide: 19,097,149

Total deaths: 714,940

While COVID-19 continues to ravage Georgia, Georgia has mostly escaped the heavy toll of the disease so far. The graph below shows the number of cases reported per day in both places. The main graph is on the regular scale, from zero to 200 new cases diagnosed per day per million people. The smaller inset graph is on the “Qatar scale,” which runs from zero to 700 cases per million people. The label also gives the mortality rate (cumulative deaths per million people) in the region – cumulative because the dead stay dead. The thickness of the lines and the size of the labels depend on the cumulative case fatality rate – the number of people who died divided by the number diagnosed.

Trends in the COVID-19 epidemic in Georgia

Which Georgia is which? You can probably guess.

Want to try these graphs yourself? Go for it!!!

I have updated my template spreadsheet to version 7.2 to include The Georgias, and also a special bonus graph I’ll show tomorrow. If you have questions about how to use it, please ask – leave a comment, messenge me on social media, or send me an email at jordan.raddick@gmail.com.

Another update on the state of the pandemic tomorrow, and every day until the pandemic ends or I do.

I’m right and I hate it (Daily COVID-19 data update CXLI)

Graphs day 141, pandemic day 148, day 218 since the first cases were diagnosed.

I hope you enjoyed Rules for protest, in the style of Dr. Seuss – or at least found it an uncomfortably accurate depiction of current attitudes toward the racial justice protests all over the world.

Two months ago, I made a prediction that Earth would reach seven hundred thousand deaths on August 5, 2020. Here we are, it’s August 5th, and:

Total cases of COVID-19 diagnosed worldwide: 18,540,119

Total deaths: 700,647

I hate being right.

Beyond this successful prediction, a quick graph to update the high case rates the regions that I first showed on Monday:

New York City, Miami, Houston, Phoenix, Orlando, Hubei, Italy, Brazil

For the areas in the United States, what we’re looking at is metropolitan statistical area (MSAs), which usually consists of several counties around the core city. Wikipedia’s List of metropolitan statistical areas shows which counties are included in which MSAs. The graph is below. The graph is on the “Qatar scale,” which runs from zero to 700 cases per million people. Each region gets a unique color and is labeled close to the line with the same color. The label also gives the mortality rate (cumulative deaths per million people) in the region – cumulative because the dead stay dead. The thickness of the lines and the size of the labels depend on the cumulative case fatality rate – the number of people who died divided by the number diagnosed.

New cases diagnosed per day per million people in hot zones around the world

The precipitous drop in cases in Miami looks like good news, and it probably is. But keep in mind that testing centers in Florida were closed for a few days this week because of Hurricane Isaias. Cases had started to drop before that, so I think cases are really dropping – but not dropping as quickly as it appears from this graph.

Want to try these graphs yourself? Go for it!!!

I have updated my template spreadsheet to version 7.1. If you have questions about how to use it, please ask – leave a comment, messenge me on social media, or send me an email at jordan.raddick@gmail.com.

Another update on the state of the pandemic tomorrow, and every day until the pandemic ends or I do.