(Dan here…NDd’s post points to more than the impact of the US catching up in testing only recently, but also points to beginning answers readers have asked in comments about what the statistics show regarding re-opening and where we might be failing to report. )
Coronavirus dashboard: emphasis on testing
I want to focus this edition on testing issues.

While the seven day average number of deaths continues to decline:

The seven day average number of new infections has leveled off:

The average number of daily tests *may* also be leveling off again in the past few days:

What is worse is that the number of new cases in the US has only declined -22% from its peak in the last 45 days. Meanwhile, even hard hit countries in Europe like Spain have seen a

Bad news and good news on coronavirus; plus, implications for Election Day
No economic news today as we head into the Memorial Day weekend, but there are a few coronavirus and economic/political developments of note.

First, the bad news: the declining trend in new diagnosed cases of coronavirus in the US has stopped in the past week. Instead new cases have leveled off. Here’s a graph from Conor Kelly’s excellent tableau coronavirus dashboard page:

Cases in the US outside of NY actually increased slightly (2%) in the past week.

Now, the good news: as also shown in the above dashboard, testing has continued to increase dramatically, up 18% again in the past week.
The jury is still out on whether the slight increase in new cases in the past 4 or 5

Initial jobless claims: employment damage continues to spread

Now that there is more than one month of data from initial and continuing jobless claims since the coronavirus lockdowns started, we can begin to trace whether the economic impacts of the virus are being contained, or are continuing to spread out into further damage.

Nine weeks in, it appears that, insofar as employment is concerned, the damage is continuing to spread.

First, let’s look at initial jobless claims both seasonally adjusted (blue) and non- seasonally adjusted (red). The non-seasonally adjusted number is of added importance since seasonal adjustments should not have more than a trivial effect on the huge real numbers:

There were 2.174 million new claims, which after the

New coronavirus cases vs. testing in “reopened” States
Are new coronavirus infections increasing in States that “reopened” on or about May 1? The jury is still out. The number of infections is up in 4 of the 5 biggest States that have done so, but so are the number of tests. The likelihood that most or all of the increase is an artificial of an increase in testing depends on the date on which you start your comparison.

I haven’t been able to find graphs that nicely show both tests and positives together, so let me just show you 2 separate graphs of the 7 day average in number of new cases diagnosed vs. the 7 day average in testing for Texas, which is the state with the biggest number of new cases.

First, here are new coronavirus infections, which are up

Abbreviated coronavirus dashboard for May 19: testing improvement continues

Here is the update through yesterday (May 18).

As usual, significant developments are in italics. The downward trend in new infections and deaths has continued. An important issue is whether we are beginning to see an increase in new infections in States which irresponsibly “reopened.” I will look at that separately from this post.

I will restart giving the daily increase in infections if States that have “reopened” start to increase significantly again. The preliminary evidence is that customers are largely staying away from reopened businesses in those States

Number of new and total reported Infections (from Johns Hopkins via arcgis.com and 91-divoc.com)
Number: 22,215,

Updating the Petri dishes of democracy: population density remains a primary determinant of intensity

Over the weekend I saw a map indicating that new coronavirus infections have been increasing on a relative basis in different and generally more rural parts of the country, especially in the Baltimore-Washington portion of the eastern megalopolis and the “black belt” in the South, the interior Midwest and Mountain West:

Below are two charts consisting of the 12 most and least densely populated States, their respective population densities, and several measures of coronavirus infections.

The first column gives the rank of the State based on the total number of infections recorded since the start of the pandemic. The second column gives their rank

Three virus-related thoughts for Sunday

There are a few posts I have been working on, but haven’t had the energy to complete.  But since I wanted to make the point, let me use this opportunity to quickly set forth a few thoughts.

1. I suspect that the virus has been “burning through the dry tinder” in March and April. At least 1/3, and possibly 1/2, of all deaths from the disease have been at nursing homes. When you consider this disease thrives on indoor spaces, recirculated air, repeated dosing with the virus, compromised immune systems, and those who already have cardiovascular disease, that ought to be no surprise.

What I suspect, but don’t have good sourcing for yet, is that a huge percentage of all residents at such facilities have already been

Jobless claims show new damage ongoing, but some damage repaired

Now that we have more than one month of data from initial and continuing jobless claims since the coronavirus lockdowns started, we can finally begin to trace whether the economic impacts of the virus are being contained, or are continuing to spread out into further damage.

Eight weeks in, the answer is mixed.

First, let’s look at initial jobless claims both seasonally adjusted (blue) and non- seasonally adjusted (red). The non-seasonally adjusted number is of added importance since seasonal adjustments should not have more than a trivial effect on the huge real numbers:

There were 2.614 million new claims, which after the seasonal adjustment became 2.981 million.

By now, virtually all

Coronavirus dashboard: updating the 52 Petri Dishes of democracy
[Note: There is no significant economic data today (Dan here…May 13)  Thursday we’ll get initial claims, and on Friday retail sales and industrial production for April, both of which will be important]
Here is the update through yesterday (May 12).

I will restart giving the daily increase in infections if States that have “reopened” start to increase significantly again. The preliminary evidence is that customers are largely staying away from reopened businesses in those States.

Number of new and total reported Infections (from Johns Hopkins via arcgis.com and 91-divoc.com):  
Number: 22,080, total 1,370,016 (vs. day/day high of +36,161 on April 24)

There has been a 1/3 decrease in the

April deflation follows a typical recessionary pattern

This morning’s consumer price index for April gives us our first indication of what the coronavirus recession has done to inflation.

Overall consumer prices declined by -0.8% (blue), while consumer prices excluding energy (gas) declined -0.2% (red).

Note that in 2015 when gas prices collapsed, prices otherwise continued to increase, showing the underlying strength of the economy. But in March and April of this year, even prices outside of gas declined, showing underlying weakness.

As a result YoY inflation is now only +0.4%, while YoY inflation ex-energy is up +1.7%:

This tells us that the decline wasn’t only in typically volatile gas prices, but showed more widespread weakness – i.e., a real

If you open it, they still won’t come: restaurant edition
In case you haven’t already seen it, here is the OpenTable restaurant reservation data from 3 Confederate States that “reopened” their economy at the end of April:

Even though restaurants were open again, reservations were still down over 80% from a year ago.

This highlights an important behavioral aspect of the pandemic: people did not wait for their State governments to order lockdowns in order to stop face-to-face economic activity. In all States – those that locked down early, late, or not at all – people dramatically slowed down non-“socially distant” participation.

This also explains what we see in the Florida data (which has other issues: e.g., snowbirds who have died in Florida

Testing and the 52 Petri dishes of democracy

Since the federal government has abandoned the field, fighting the coronavirus pandemic has been left to the States, territories, and the District of Columbia. This means that there is no unified response and instead there are 52+ individual responses. That is the biggest challenge in tracking the pandemic.

Which means I’ve been looking for the best resources to show how the States are doing in comparison with one another. I’ve found a couple of good ones, so here are snapshots below.

The first is endcoronavirus.com . They have thumbnail graphs of the 50 States, DC, Puerto Rico, Guam, and the Virgin Islands, divided by the trend in their daily new cases. The list needs to be updated from May 5, as shown in

The humans always observe back: why I am rooting for NY to “crush the curve”
So, in addition to a bunch of States in the Confederacy and a few in the high plains deciding that May 1 was the Day of Virus Jubilee, yesterday saw further discouraging news that not one but two epidemiological models drastically increased their estimates of deaths, while there was another revelation that Trump and the White House were relying on a “cubic” model devised by Kevin Hassett of “Dow 36,000” infamy, showing death abruptly declining to zero by about May 15.

First came the CDC model, that shows deaths beginning to increase exponentially again after May 14 (not coincidentally, two weeks after the Day of Virus Jubilee):

Then, the IHME, whose model had only recently

April jobs report: disastrous, but not as cataclysmic as feared; lower paid part time workers take the biggest hit

HEADLINES:
-20.5 million jobs lost. Between March and April this is a loss of 14.0% of all jobs since February.
U3 unemployment rate up 10.3% from 4.4% to 14.7%
U6 underemployment rate rose 14.1% from 8.7% to 22.8%
February and March were both revised downward, by -45,000 and -169,000 respectively, for a net decline of -214,000 jobs from previous reports.

Leading employment indicators of a slowdown or recession
 
I am still highlighting these because of their leading nature for the economy overall.  These were uniformly very negative:

the average manufacturing workweek fell -2.1 hours from 40.4 to 38.3 hours. This is one of the 10

Infections in US States by population density

Since COVID-19 is a communicable disease, it should hardly be a surprise that the most densely populated States have the most cases per capita, and conversely the least densely States have the least cases.  But since that basic point is lost in a lot of the analysis, let’s take a look.

Below are two charts consisting of the 12 most and least densely populated States, their respective population densities, and several measures of coronavirus infections.

The first column gives the rank of the State based on the total number of infections recorded since the start of the pandemic. The second column gives their rank per capita over time since the start of the pandemic. Finally, the third column gives their rank

Comparing the US’s coronavirus response with its Western European peer group

Western Europe is a reasonable peer group of countries against which to compare the US response to coronavirus. The 5 largest countries in Western Europe in particular – in order, Germany, the UK, France, Italy, and Spain – together have a population of about 324 million, vs. 332 million for the US.
So let’s take a look at this peer group of European States vs. the United States in terms of cases, deaths, and testing.

One significant difference is that Italy was among the first countries struck in force by the pandemic. In early March it was common to note that the US was “two weeks behind Italy” in the number of cases. The other four all saw their pandemics start a few days to

A note about the weekly and monthly economic data

For the past month or so, with the exception of the weekly catastrophe of new jobless claims it hasn’t been very important to keep track of the economic data. Now that it is May, that will start to change with the weekly data as of next week (reporting on this week). The monthly data fo May, of course, won’t be reported for until June starts.

That’s because the month of April was fully involved in the pandemic crisis. So with the month over month May data we will be able to see if the economy is beginning to stabilize at a lower level, sink even further as more second-order effects ripple out from the epicenter, or perhaps even rebound.

With the exception of finding out what happened to wages during

Coronavirus dashboard for May 4: new infections, deaths continue slow decline

Here is the update through yesterday (May 3).

As usual, significant developments are in italics. The bottom line is the same as several days ago: trends in new infections, deaths, and in testing have all turned positive – if not positive enough. But the good news remains primarily a NY story.

I have discontinued giving the % increases day/day in infections and deaths. They were included when important to determine if the US was “bending the curve.” The two issues now are (1) whether any States (beyond the least populated rural or isolated States) can “crush the curve;” and, sadly, (2) whether those States that have “reopened” see a renewed increase in the growth of cases and

Coronavirus dashboard for April 30: the US has the worst record in the world, by far
Here is the update through yesterday (April 29):

Number of new and total reported Infections (from Johns Hopkins via arcgis.com and 91-divoc.com):

Number: South Korea: ZERO (4 detected from incoming flights at airport)
Number: Taiwan: ZERO
Number: Vietnam: ZERO
Number: Germany: 1,627 (up from 988 on April 27; 3 day average of 1,256 down -81.5% from 6,790 peak on April 1-3) (highlighted in graph below)
Number: US: up +24,114 to 1,040,488 (vs. day/day high of +36,161 on April 24; 3 day average of 24,709, down -26.1% from 33,437 peak on April 8-10)(#1 in the world, 5.7x #2 Spain)(outlier at top of graph below)

Figure 1
There has been a slight decrease in the number of

The widely followed IHME model of coronavirus cases has been much too optimistic

The IHME model by the University of Washington has gotten a lot of attention in the past month, most likely because it has always forecast a much lower number of total deaths caused by coronavirus than, for example the Imperial College of London’s model, that forecast over 1 million US deaths if no quarantine measures were put in place.

But that model has come in for a lot of criticism, and I have come to distrust it. Its main feature – and biggest shortcoming in my opinion – is that it assumes that the US path will follow that of China and South Korea, where after the peak is reached, the disease ramps down just as quickly as it ramped up.

Here is what the model predicts

Abbreviated coronavirus dashboard for April 29: actual good news on testing,deaths 
Here is the update through yesterday (April 28). This is somewhat abbreviated since I want to post about a couple of other items.

As usual, new items of significance are in italics. Yesterday was the 3rd day in a row of not just significantly increased testing, but actual lower number of infections found by that testing – a very good sign. The 7 day average of deaths also moved into significant decline. At least those States which are sticking with a “crush the curve” strategy appear to be turning the corner.

Here are yesterday’s numbers.

Number and rate of increase of Reported Infections (from Johns Hopkins via arcgis.com)

Number: up +24,114 to 1,012,583 (vs. day/day

Coronavirus dashboard for April 28: good news on testing at least

Here is the update through yesterday (April 27).

s usual, significant developments are in italics. There were some late-reporting States for testing yesterday, so the initially discouraging number was actually pretty good. We are now seeing much more testing, and for the last two days an actual decrease in new infections being found. One problem is that this is mainly due to one State: New York. 
 
Discouragingly, 11 States have decided to at least partly “open up.” A few of these – Alaska and Idaho – a mainly rural and sparsely populated, with near single-digit new cases, so limited openings with social distancing restrictions can be justified. But most of the rest are recalcitrant States

The biochemistry of how COVID-19 attacks the body: a synopsis of the medical studies

I’ve been doing some reading over the past several weeks, trying to understand how the COVID-19 virus attacks the human body. Below are quotes I found most noteworthy or interesting from these articles.

In essence, they indicate that biochemically the novel coronavirus, COVID-19, mainly binds to the ACE-2 receptor of cell surfaces to gain entrance. These are most prevalent in nasal and mucus cells, alveoli (oxygen-exchanging cells in the longs), and some cells lining the small intestine, which explains why the disease may start as abdominal discomfort in many patients. There are some conditions, especially high blood pressure and diabetes – or, possibly, medications for

What the ratio of positive tests to total test results for coronavirus is telling us

I want to make a comment about the value of measuring the number of coronavirus tests being administered vs. the number of cases found by those tests. This is because a few people are claiming that the ratio of positive tests to total tests does not give us value. Rather, they claim, increased testing simply reveals increased infections.

I will make a bold, unqualified claim: they’re wrong. Here’s why.

Empirically, about 6 weeks ago I looked at the South Korea data and realized that the peak was in once the percentage of positives to total tests started to decline. I suggested tracking that to Bill McBride, who has since included it in his daily testing updates. It

Heads up for tomorrow!
Tomorrow morning I have a very long post quoting about 20 medical articles at length, explaining (what we think we know so far about) the whole biochemistry of how the novel coronavirus attacks the body.
By the time you finish reading it, you will understand a lot about why the disease attacks the organs it does, why it progresses in the order it does, why it produces some extremely unusual complications in victims who otherwise feel perfectly healthy, why there are some special risk factors and possibly a couple of protective ones as well, and finally genetic identification posssibilites for people most or least at risk.
Heads up!
New Deal democrat

Jobless claims still point to over 20,000,000 lost jobs in April, 15%+ unemployment rate
As I’ve written in the past few weeks, the number of initial jobless claims correlates roughly with the number of net new jobs added or subtracted in any given month. Normally there is too much noise for it to be of much value, but with the huge spike in the past month, the signal will come through much more strongly.
Here’s what the crude correlation looks like between initial claims (blue, weekly) and jobs (red, monthly), in the past year through February:

After the leap is what the exact same correlation looks like since the beginning of March:

The reporting week for the April jobs number was last week. In the 4 months ending last week, over 23,000,000 new

The actual US coronavirus trajectory: “flattening the curve” at least until 2021

“Flattening the curve” was not such an appetizing option either, because it meant that *everybody* got infected with the disease during the period of flattening, and so the death toll would still be horrifying, perhaps 1% to 3%. It also meant that the period that the infection would curtail society was extended to several years.

Shortly a much better alternative, based on the success of South Korea, was embraced. Described as “crush the curve,” it meant imposing firm lockdowns for a long enough period of time for thoroughgoing testing of the population, tracing contracts of those infected, and isolating the infected to be ramped up and in place.

Here’s what the three

Trends in US States compared by coronavirus response
I mentioned over the weekend that I wanted to break out and look at some different aspects of the coronavirus pandemic.
Here’s the first: how are States at different ends of the restrictions and testing spectrums faring?
Seven States have never even mandated lockdowns. Let’s look at these, alphabetically:
Arkansas:

Iowa:
Figure 1
Nebraska:
North Dakota
South Dakota:
Utah:
Wyoming:
Four of the seven continue to show a trend of increasing infections. Arkansas and Utah appear to have plateaued, and Wyoming has such a small number that it’s decline is in single digits and not significant.  The virus in the 4 States with increasing numbers isn’t under control at all — but all of these States have small

Towards a modern “History of Republics”: a consideration of William Everdell’s “The End of Kings: A History of Republics and Republicans”

In view of the horrific damage that the Trump Administration has done to the American Republic, during the past year I have done extensive reading of the histories of a number of the most successful or durable Republics over time. The reason has been to try to answer the question of whether there is an overarching narrative to the history of Republics: how they form and evolve over time, and whether they are ultimately doomed, as was Rome, to collapse into autocracy. As I briefly detail below, the answer to that last query, thankfully, appears to be a qualified and very hedged “no,” although maintaining one over the

Coronavirus dashboard for April 20: a few positive development
Here is the update through yesterday (April 19)

As usual, significant developments are in italics. Yesterday saw the biggest number of daily tests, and ratio of total vs. positive tests so far, both positive developments.  The number and rate of daily infections and deaths also declined, but that may be a function of lower weekend reporting.

Here are yesterday’s numbers.

Number and rate of increase of Reported Infections (from Johns Hopkins via arcgis.com)
Number: up +24,499 to 759,786 (vs. 35,354 prior peak on April 17)

***Rate of increase: day/day: 3% (vs. 4% for the past week, and 4% on April 18)

The number of new infections made a new peak last Friday. The numbers seem to go