Category: COVID through 2022

Above:  Trend in new COVID-19 cases/ 100,000/day, my calculation from NY Times Github repository data reported through 12/29/2020.

• Black = already peaked, no longer a concern for “out-of-control COVID”.
• Green = stable rate, possible downward trend.
• Orange = stable rate, possible upward trend.
• Gray = California.

I’m sure you’ve been reading newspaper articles about the crisis in hospitals in Southern California.  I’m just here to point out what you’re not seeing:  Articles like that about anywhere else in the U.S.A.

And that’s because the state of the U.S. is pretty much as pictured above.  There’s California.  And then there’s the rest of the U.S. Continue reading Post #931: Simplifying the picture of COVID-19 in the US

In Post #925, I made the prediction that Tennessee was past its peak daily new infection rate.  That wasn’t based on any detailed analysis.  That was simply based on what had already happened 12 times before, in this pandemic, to states in a similar situation.

The only value-added here was in figuring out that this was the 13th time a state was in this situation, and then quantifying what, exactly, “this situation” was.

That was then:

This is now:

And I’d say that’s looking pretty good, prediction-wise.  So far.  Plus-or-minus a Christmas data-reporting artifact.

And sure, doctors bury their mistakes.  Meaning that people don’t brag on the times that they were wrong.  So if I’d screwed this up, it’s unlikely I’d be writing this post.  (Though I try to be as scientific as I can, announce things ahead of time, and admit when I am wrong.)

But there’s a reason behind this.  This wasn’t a lucky guess.  There’s a reason that Tennessee is the 13th in the series. It’s h*** i*******.  The condition that dare not say its name (Post #928).

And the exceptionally good news is, the same thing that gave me the confidence to call it for Tennessee tells me that the US, as a whole, is (probably) now over the hump on COVID-19.

In short, I think we’ve seen the worst of it.  And we’re starting to leave it in our rear-view mirror.

This is definitely something you won’t read in the mainstream press.  As the news coverage flits from peak awfulness to peak awfulness, state-by-state, try to keep your eye on the big picture.

And the big picture is, we’re over the hump.  It’s light-at-the-end-of-the-tunnel time.  Maybe not for your particular state.  But for the US as a whole.

A few details follow.  But I’ll be fleshing this out in the next several posts. Continue reading Post #930: Odds are that the U.S. is over the hump, COVID-wise.

Source:  Plotted from data from the NY Times Github COVID data repository.  Data reported through 12/26/2020

Edit:  You can now see this clearly, with 20-20 hindsight, in (e.g.) Post #941.  The holidays do, in fact, put a significant dip in the reported infection count.

Holidays introduce several types of artifacts in the data on new COVID-19 cases.

There’s an immediate “reporting” artifact.  Many public health departments are short-staffed on the holiday, and they aren’t able to tabulate all the new COVID-19 test results that arrive on the holiday itself.  That creates a sharp one-day dip-and-rebound in reported rates.  We saw that at Thanksgiving, predicted in Post #901, confirmed just post-Thanksgiving in Post #909).  And, as above, we’ve now seen that same pattern for Christmas day.

There are other artifacts, but they will be more subtle than that, and harder to spot.  Presumably, there’s a slowdown in the actual rate of testing (because who goes out on Thanksgiving to get a COVID-19 test), and that shows up as a dip in the rates a few days later.  Finally, there’s the actual “surge” — if any — the actual increase in infections due to holiday travel and such, that shows up anywhere from 12 days to three weeks after-the-fact.

This post is about an odd discovery that I made when try to smooth out the Christmas reporting artifact, shown above.  The discovery is that there isn’t a simple offsetting dip-and-rebound in the reported rates.  The rebound isn’t as big as the dip.  There’s actually a small, permanent one-off reduction in the number of positive cases found, associated with that holiday day.  True for Christmas.  And, in hindsight, true for Thanksgiving as well.

It’s as if some people who would have tested positive just never bother to get tested.  Presumably, because of the holiday.  And never get tested afterwards, to make up for it.  Presumably because, eh, they probably don’t have a very bad case of COVID-19.  And so, apparently, just deal with their COVID infection.

This is no more than an odd footnote.  My real goal here was to talk about trends.  But, in fact, I just have to let the Christmas data glitches work their way through the system before I can talk about trends again.

A small amount of detail follows. Continue reading Post #929: An odd footnote on the post-Thanksgiving surge that never happened

Sometimes I read newspaper coverage of the pandemic and I wonder if I’m living on the same planet as the reporters.

Yesterday it was a NY Times article on the post-Thanksgiving surge.  There, amidst the waffling, and the “it’s complicated”, the one-hand-other-hand reporting, and the anecdotes, nobody would just plainly say what is obviously true:  There was no post-Thanksgiving surge.  Just use your eyes, below.

Today it’s a Washington Post gloom-and-doom article, where they continue the post-Thanksgiving surge meme, again without reference to any analysis to back that up.

I really have to wonder if anybody at these organizations ever bothers to plot the data.  And look at it.  Or maybe it’s just the constant focus on areas where there are problems, and silence about areas that aren’t in trouble.

But here’s my take on it, starting from best to worst.  To cut to the chase:

• The third wave of COVID has already crested much of the country.
• The big unknown is the South, where there is neither a clear increase nor a clear decease in new cases.
• COVID-19 is out of control in just two states:  CA and TN. Continue reading Post #923: Just two states have out-of-control COVID-19 new infection rates

Today I’m just presenting the graphs of seven-day moving averages of new COVID-19 cases/ 100,000/day, for state grouped by six regions.  They’re at the end of the posting.  I only want to make two points.

No post-Thanksgiving surge

The data now run through 12/17/2020, three full weeks after Thanksgiving.  At this point, with some small risk of being wrong, I’m going to call it.  Just use your eyes.  There was no post-Thanksgiving surge in cases.   If you’ve been reading along, that’s no surprise.  And that matches the lack of a surge in Canada, following Canadian Thanksgiving (Post #).

Wouldn’t we all like to know why, given that we’re about to re-do that, in spades, more-or-less starting this week.  Wouldn’t we like our public health authorities at least to discuss it?  Not gonna happen.

I’ll just hazard my guess here:  I think people who traveled for Thanksgiving were exceptionally cautious, on average.  I think all that messaging around Thanksgiving got through to people.  I have no way to prove that.  But of the possible explanations, that’s the one I think is most plausible.  For sure, sitting next to somebody with COVID, on public transport, has a non-negligible risk of transmission (reference).  (It’s not clear whether passengers were wearing masks in that study.)  Why those transmissions didn’t occur, here, I’d have to chalk up to testing, mask-wearing, and similar preventive behavior.

While the news media were full of warnings prior to Thanksgiving, I have a hard time recalling even one news story focused on the parallel dangers for the coming week.  I guess you can say “skip Thanksgiving this year”, but nobody can plausibly say the same for various year-end holidays.   And so for the coming holiday travel there has been no barrage of public-health messages.  Let’s hope that people act cautiously, regardless.

A surge of cases in just two states:  CA and TN

While new-infection rates are high in many areas, they aren’t rising.  If you look at the lines on the graphs at the end of this posting, most end with level-to-downsloping segments.  The two gross exceptions are CA and TN, with a third possible exception in AZ.  Those are the three with high and rising COVID-19 new-case counts.

Source:  NY Times.

TN is truly an exceptional outlier, because nothing about the geography, population, or weather suggests that they ought to go the way of the Midwest.  As you can see from the graph, their troubles have been building for months (so this isn’t some unique post-Thanksgiving surge.)  And as you can see from the map, their troubles are spread uniformly across the state.

The only thing they have in common with the hardest-hit Midwest states is that they have a Republican governor and, accordingly, minimal response to COVID-19.  (Apologies as always to cousin Larry).  For example, they have no mask mandate, and any business restrictions appear to be strictly local in nature.

To me, similar to much of the Midwest, they now look like a state that did fine until the weather changed, and their risk-taking is now catching up to them.  At the peak, the ND map had that same look — COVID was everywhere.  And so, what worked for them in August isn’t working for them in December, and they’re not nimble enough to figure that out and change behavior accordingly.  My guess, at this point, is that they are going to follow in the footsteps of ND.

But they haven’t quite run out of ICU beds yet.  As of today there are still 161 ICU beds open (reference).   If they stick by the playbook, the state government will take no action until that approaches zero.  Probably have another week or two to wait for that.

CA, by contrast, has both weather and population working against them.  Weather, in the form of an exceptionally dry November in Southern California.  (See Post #894 for the key role that humidity plays.)  If you un-focus your eyes a bit, you’ll see a fairly strong north-south differential across the state.

And population, in the form of a high percentage of individuals of Hispanic origin.  COVID-19 has taken an exceptionally high toll on the Latino population pretty much everywhere, including here in Virginia (Post #719).  I don’t think anyone is quite sure why.  That has been casually attributed to occupational mix, with a purported heavy presence among at-risk health care workers.  But it’s not clear that’s an adequate explanation.  In any case, unlike TN, CA has been doing much to try to prevent spread of disease.  They’re just not succeeding, particularly in the dryer areas.

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Source:  Analysis of data from Centers for Disease Control FluView Interactive.

The graph above shows the development of a typical U.S. flu season.  It averages all U.S. flu seasons from 1997 to 2020.

The vertical axis is the percent of outpatient health care visits that are for “influenza-like illness” (so 1.5 = 1.5% of all visits).  The horizontal axis is the week of the year.  (The whole year would run from 1 to 52, but I’ve only shown July to December here.)  The data are from healthcare providers participating in the CDC U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet).

I’ve drawn in a black trend line.   Assuming your eyes work like mine, you’ll note sharp break from trend starting somewhere around week 49.  You don’t have to guess at it.  It’s not somehow drowned out by the existing trend.  It’s easily visible to the eye.  That is, in a typical year, there a big surge in flu cases starting at that time.

Week 49 is two weeks after Thanksgiving.  More-or-less.  Continue reading Post #920: Now that’s a surge.