Month: August 2020

Graphs day 139, pandemic day 146, day 216 since the first cases were diagnosed.

Not just an incremental update today, I’ve got a whole new way of looking at the data.

Total cases of COVID-19 diagnosed worldwide: 18,079,126

Total deaths: 689,347

Everything we have seen so far has been at the level of entire countries or entire states (or in one case, the province of Hubei in China). But I also have county-level data for the United States, so we can look in grater detail at areas smaller than state or country. In particular, we can look at some places that have been identified as “hot zones” – areas with particularly high case rates. The regions we’ll look at today are:

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.

So how does the pattern of cases look in each of these “hot zone” areas?

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.

Two observations:

• The worst case rates have been in Miami, but the worst death rates have been in New York City
• For all the early news coverage of China, Italy, and Brazil, the areas that have been hardest hit so far are all in the United States. Key word: so far.

Want to try these graphs yourself? Go for it!!! I’ve updated my spreadsheet (still version 7) to restore the formulas. The upside is that you can now more easily make changes to make the graphs your own; the downside is that unless you are on a high-end computer, the calculations will be slooooooooooooooooow. To speed up calculations, replace formulas with values once you decide you have the right formulas. If you’re not sure how to do that, just 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. And more of the regular Monday-Wednesday-Friday posts, which are way more interesting anyway.

Graphs day 138, pandemic day 145, day 215 since the first cases were diagnosed.

Total cases of COVID-19 diagnosed worldwide: 17,849,843

Total deaths: 685,054

Dividing those numbers gives the global observed case fatality rate – the percentage of people diagnosed with COVID-19 who go on to die of the disease. That number is 3.8 percent. It has been steadily declining since I’ve been tracking the pandemic, down from 4.1 percent for COVID-19 daily data update I on March 18th. Why the decrease?

I’ll let one of my smart awesome friends explain. Here is Dr. Gretchen Arnoczy, an infectious disease doctor at First Health of North Carolina, with the explanation:

Testing testing testing.

As our testing capacity increases, we are able to identify more mild or asymptomatic cases. If we only test symptomatic people, the mortality rates look bad.

South Korea did this well early on, finding widespread infection across lots of age groups but symptoms only in older and high risk. Their mortality rate was around 1% or less. I expect the true mortality rate to be around 1-3%.

We still struggle with having enough tests. If our hospital only has 50 tests, we only test people who are sick enough to be admitted. If our hospital has 5000 tests, we can test everyone exposed in an outbreak and really understand the scope of disease better.

Dr. Gretchen Arnoczy

Speaking of smart awesome friends, my smart awesome (and excellently named friend) Jordyn Hoyos asked me to take a look at three more U.S. states: Texas, California, and North Dakota. How are these states looking?

Looking only at absolute numbers of cases, California has more cases than Florida or Texas, and North Dakota has very few. But, as I’ve said from the beginning, raw numbers are usually not a useful way of looking at the spread of a disease. It is much more helpful to look at rates of disease, measured in cases per million. And what happens when you look at rates of disease in Florida, Texas, and North Dakota (and also Peru and Ecuador)?

The graph shows that the pandemic is much worse in Florida and Texas than it is in California. And the graph shows that even North Dakota (black line), a state which is frequently cited as having successfully managed the pandemic without major economic disruption, has not actually been all that successful in managing the pandemic. The low number of cases in North Dakota is due to North Dakota’s low population – looking at case rates per million people shows that they are on par with Peru and above Ecuador, two countries I’ve been following for their high case rates.

The good news is that the downward trend in Florida appears to be continuing. Florida’s mistake back in May was to relax its social distancing policies too early. Let’s hope they stay the course this time.

Want to try these graphs yourself? Go for it!!! I’ve updated my spreadsheet (still version 7) to restore the formulas. The upside is that you can now more easily make changes to make the graphs your own; the downside is that unless you are on a high-end computer, the calculations will be slooooooooooooooooow. To speed up calculations, replace formulas with values once you decide you have the right formulas. If you’re not sure how to do that, just 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. And more of the regular Monday-Wednesday-Friday posts, which are way more interesting anyway.

Graphs day 137, pandemic day 144, day 214 since the first cases were diagnosed.

Total cases of COVID-19 diagnosed worldwide: 17,591,968

Total deaths: 679,439

It’s Independece Day in the west African nation of Benin (pronounced ben-EEN), and fortunately like many countries in Africa, Benin has very few cases. Also, by popular demand, I’ve added Ecuador.

As I’ve feared for many days now, the number of cases in Spain and Belgium have both increased to more than five times their values of late June, and are continuing to increase – enough that it’s clear that they need to be moved into the “getting worse” category. But unfortunately, so many countries now fit that description that putting them all on one graph would result in an indecipherable graph. So how to split it up?

I think it makes the most sense to make a distinction between countries experiencing a second wave of COVID-19 infections and those where the first wave is still getting worse. It’s somewhat arbitrary to declare when one wave has ended and another has begun, but I’ve done my best to decide which is which.

Thus, starting today, there are five categories. All graphs are below, in the usual style. Countries are color-coded and labeled by name. The thickness of the lines and the sizes of the labels correspond to the case fatality rate in the country – thicker lines and larger labels indicate countries where a larger percentage of COVID-19 cases have led to death.

Regions where COVID-19 was quickly contained

In honor of Benin’s Independence Day, I’ve added them to my data tracking for today only (purple line). I’m grateful that I can put them in this category.

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

Sadly, Spain and Belgium have left this graph. But the good news is that one country has joined the graph: the rate of new cases diagnosed in Belarus has fallen to below 15 per million.

Regions moving in the right direction(-ish)

Belarus has left this graph for the Under Control graph. Sweden may join them soon – which I absolutely would not have predicted back in April, May, or June. On the other end, cases in Peru have increased to above 150 per million people per day, and so they move into the Getting Worse category.

Regions experiencing a second wave of COVID-19 cases

So many countries fit into Getting Worse category that I have divided it into two. First up, countries where the daily case rate had reached a very low level, then went back up again, and is continuing to increase. The regions I am tracking in this category, at least for now, are Spain, Belgium, Australia, Japan, and Serbia.

Regions where the pandemic is getting worse

As before, I’m tracking cases in Florida separately from the rest of the United States. Ecuador could have gone in the second wave category, but I put them here because

Florida appears to be on a downward trend, thank God. But I’m waiting at least until they return to the main graph before declaring them moving in the right direction.

I’ve updated my spreadsheet (still version 7) to restore the formulas. The upside is that you can now more easily make changes to make the graphs your own; the downside is that unless you are on a high-end computer, the calculations will be slooooooooooooooooow. To speed up calculations, replace formulas with values once you decide you have the right formulas. If you’re not sure how to do that, just ask – leave a comment, messenge me on social media, or send me an email at jordan.raddick@gmail.com.

Have a great rest of the weekend. Another update on the state of the pandemic tomorrow, and every day until the pandemic ends or I do.