Category: COVID through 2022

All my various postings tracking the COVID-19 pandemic through the end of 2022.

Post #919: Still waiting to see that surge

Source:  Calculated from NY Times Github data repository, data reported through 12/14/2020, or two weeks and four days after Thanksgiving day.  The apparent one-day spike in the South Central states is an artifact of change in Texas data reporting, as explained at the end of Post #915.

Well, we’ve got about three days left for the much-anticipated post-Thanksgiving COVID-19 spike to show up.  Estimates for when cases contracted at Thanksgiving would appear in the data range from T+12 (12/8/2020, my best guess  as to median lag between infection and reporting) to as late as T+21 (12/17/2020, “three weeks”, the longest lag I’ve ever seen any source suggest).

I’m sure not seeing that spike.  Yet.

This isn’t quite a done deal yet.  Possibly that spike will occur.  But with every passing day, the odds are shifting in favor of no spike.

My continued harping on this point is NOT about pointing the finger at public officials who predicted a large post-Thanksgiving spike in COVID-19.  But if we can’t say “we didn’t have a spike”, then we can’t have the conversation about why we didn’t have a spike.

And that’s a shame, given that the holidays are here and/or right around the corner, depending on what you celebrate.   Wouldn’t it be nice to know what we did right, so we could try to do that again?

I have argued that the “spike” of cases following Canadian Thanksgiving is pure fiction.  Never happened.  All that news derived from ludicrously poor data analysis (Post #916).  So we also ought to ask what the Canadians did right, while we ask what we did right.

Did people mostly stay home?  That doesn’t quite seem to square with news report that air travel was 40% of historical norms on the day before Thanksgiving.

Were travelers and socializers ultra-cautious in their behavior, thanks to that warning about a COVID-spike?  Getting tested before traveling, being scrupulous about mask use and distancing, holding dinner outdoors, and so on?  In which case, are we really just looking at the outcome of good public policy (the warning) that averted the very disaster that the public policy warned about?

Or was this really just not that big a risk in the first place?

Beats me.  But it’s now about two weeks to New Year’s Eve, and nobody’s even asking the questions.

The key public health officials who made the prediction of a post-Thanksgiving COVID surge aren’t going to be jumping at the chance to discuss why they were wrong.  They’d be just as happy if this slipped into the past without anybody noticing.  Somebody needs to hold their feet to the (toasty holiday) fire and at least try to get some answers to those questions.

Did we learn anything from this, or not?

 

Post #918: An N95 surprise on Amazon — but not Home Depot or Lowe’s.

Source:  A plausibly legitimate N95 mask for sale on Amazon.com

As you may or may not recall, the first sign of pandemic panic buying was the disappearance of face masks from the shelves.  As of 2/28/2020, every mask of every description had been bought up at our local Home Depot (Post #535).  And that was before there was even a single known case of COVID-19 in Virginia. Continue reading Post #918: An N95 surprise on Amazon — but not Home Depot or Lowe’s.

Post #916: But wait, what about that huge Canadian post-Thanksgiving surge?

Stop: Before you read any further, take 30 seconds, study the graph above, and identify when Canadian Thanksgiving occurred, based on the huge surge in cases that occurred two weeks afterwards.  Answer given at the end of this posting. Continue reading Post #916: But wait, what about that huge Canadian post-Thanksgiving surge?

Post #915: Still no post-Thanksgiving COVID surge

A few weeks back, it was widely (and reasonably) predicted that Thanksgiving travel and socializing would result in a spike in new COVID-19 cases. 

 

 

You don’t see much talk about that, now.  But you should.  Because that spike ought to be showing up any time now.

It’s not perfectly clear when that spike should occur, due to the lag between getting infected and having that infection counted in the data.  It takes about five days, on average, for symptoms to develop.  After that, it depends.  I’ve used a median value of 12 days total lag, both because that’s seemingly reasonable, and because that seems to be the lag from the Chinese experience in Wuhan, adjusted for more rapid American testing.  But I have seen others offer a vague “two to three weeks”, without offering any data analysis to support that.  I have not seen anyone suggesting a lag greater than three weeks.

We now have data through 12/12/2020, or two weeks and two days after Thanksgiving day.  And while the Thanksgiving holiday definitely scrambled the data reporting, the much-anticipated spike in new cases does not seem to be happening.  Yet.

Bear in mind that everybody looks at a seven-day moving average (I address this graphically at the end of the posting).  So even if a spike had begun, that data-averaging practice would blur it on all the charts you commonly see.   So it’s too early to say that we aren’t going to see that Thanksgiving spike.  Yet.  But every day that it fails to appear increases the odds in favor of no spike.

What should we expect to see if there were a Thanksgiving spike?  The signature of a Thanksgiving spike would be simultaneity.  We should expect to see a sharp upturn in cases, well above existing trends, across all the states, all at the same time.  That’s because Thanksgiving is celebrated in all states, all on the same day.  There would be some variation for the speed with which states report cases.  There would be some variation for the fraction of each state’s population that did or did not travel and meet with larger family groups.  Variation due to all the other diverse things going on in those states.  But in general, we ought to see almost everybody’s new cases departing sharply upward from trend, more-or-less all at the same time.

And I certainly don’t see that.  Yet.  What I see looks mostly like continuation of recent existing trends.  But you can look at the data (below) and see for yourself.  These are data through 12/12/2020, or 16 days after Thanksgiving day.

I note that California’s departure from trend occurred well before Thanksgiving-generated cases would have entered their data.  I casually have attributed that to a very dry November in Southern California.

One problem with all the graphs above is that they are seven-day moving averages.  Everybody does that to even out the large daily transient variations in case counts.  But that comes at the expense of having data that respond sluggishly to changes.  My final data point (12/12/2020) actually represents data with an average age of around 12/8/2020 – 12/9/2020.

Averaging across time is not the only way you can get rid of unwanted daily variation in each state’s reported cases.  You can simply average up different sets of states, day by day.  That will also get rid of some random daily fluctuations in counts, but will let any simultaneous changes be visible.  (For example, the “blip” that Thanksgiving put into the data report should remain visible, because those state-level “blips” all occurred on the same day).

So let’s try it that way, showing the daily count of new cases (not the seven-day moving average), but showing the population-weighted average within six regions.  And because the numbers still jump around from day to day, let me also show a three-day moving average of that.  That gives me some smoothing, and the last data point is, on average, just one day older than the raw daily data.

The regions here match the graphs above:  New England/Mid-Atlantic, South Atlantic, South Central, Midwest, Mountain, and Pacific.

Across the regions, the only thing that even looks like a spike, with the right timing, is in the South Central region (gray line)– and that turns out to be an artifact of data reporting.  On December 11, it appears that Texas did what North Dakota (Post #912) had some a few days earlier — added probable cases (presumably based on antigen testing) to their case counts.

On Dec. 11, probable case counts were added, and the dashboard was reconfigured to improve performance. For more information about probable cases, ...

Source:  Texas Department of State Health Services COVID-19 dashboard.

Far as I can tell, the Thanksgiving-related spike in COVID-19 cases hasn’t occurred.  Yet.

This does not mean that the advice to avoid Thanksgiving travel and gatherings was bad advice at the time it was given.  It was completely reasonable advice.  And we may yet see that spike in the next few days.  But if we don’t see it, that’s news, and that needs to be widely reported.

Post #912: COVID-19 trends: No clear Thanksgiving effect yet; ND data anomaly

Yesterday, North Dakota decided to add persons with a positive antigen test to their counts of new positive COVID-19 cases.  Previously, they did what every other state does, and counted PCR tests only.   (See diagnostic test on this FDA webpage for the difference between antigen tests and the standard PCR tests.)

The backlog of those individuals added thousands of new cases to their totals, yesterday, and generated an apparent spike in cases.  For anyone looking for the effect of Thanksgiving travel in the data, that certainly caught the eye.

But if you look net those cases out of the data, to make the current data consistent with the historical data, ND continues on its prior downward trend.  That’s the red line segment added to the ND data line above.

That’s all by way of getting to my main point.  So far, while the trends are in general not good (outside of the states that had high peak rates last month), the trends are no different today than they were a week ago.  Today is exactly 14 days after Thanksgiving.  And, to may eye at least, so far, there’s no evidence of a widespread Thanksgiving-driven increase in the number of new cases. Continue reading Post #912: COVID-19 trends: No clear Thanksgiving effect yet; ND data anomaly

Post #911: COVID trends to 12/7/2020, Hawaii is the only bright spot.

This is just an update of my state-level graphs, showing the seven-day moving average of daily new COVID cases, based on the NY Times Github data repository.  The sharp squiggle near the end of many lines is an artifact of data reporting from the Thanksgiving holiday.

True new cases generated by all the socializing and travel at Thanksgiving should only start arriving in the data this week, at the earliest.  So all the existing upward trend you see to this point, in so many states, is all prior to the impact that Thanksgiving may have on new COVID-19 cases.

The Midwest states that had such extreme peaks two weeks ago generally continue to see declining (albeit high) new case counts.  Or maybe stable (but high) new case counts.

Pretty much everywhere else, other than Hawaii, the trend is toward higher case counts.  Outside of the Midwest/Mountain states, only Rhode Island has exceeded 100 new cases/100,000 population/day.  But many states are headed for that level, and (e.g.) Alaska looks like it will exceed that level in a few days.

California has broken away from the other West Coast states.  Without proof, I’d suggest that an exceptionally dry November in most of California may have contributed to that (Post #894).  With their Santa Ana winds, and zero rainfall, Los Angeles had numerous days where the outdoor relative humidity was in the single digits.  So California isn’t cold, but it’s surely got dry indoor air.  (By contrast, e.g., Both Seattle (WA) and Portland (OR) had significant precipitation, and outdoor relative humidities were typically in the 80%s.  So the Southern California climate was vastly different from the OR and WA climate in November 2020.)  Weather data were summarized from Weather Undergound historical weather data.

National and regional data follow.

 

Post #909: Thanksgiving data artifact. I think. Now confirmed.

Edit:  One more day of data confirms that this was just a data reporting artifact.   True Thanksgiving-generated cases, if any, should begin showing up in the data next week.

Original post follows

Based on data reported through 12/3/2020, many (but not all) states are showing large upticks in the seven-day moving average of new cases per day.  As shown above, circled in red.

After looking at the details, I think that’s probably an artifact of Thanksgiving data reporting.  That is, I don’t think this is the start of a rapid increase in cases due to Thanksgiving-related travel.  Initially, I thought that all of that would have “washed through” the data reporting systems by Tuesday at the latest.  But here’s why I’ve changed my mind: Continue reading Post #909: Thanksgiving data artifact. I think. Now confirmed.

Post #908: Hebrews 11:1

Post #906 was about things that can harm us even though we can’t see them.   Seemingly clean household air is, in fact, full of particulate matter, much of it not visible to the naked eye.  But even if you didn’t believe that, it’s relatively simple to prove it.  Just run a box fan with a high-end air filter on the back, and note the buildup on the air filter.  Seemingly out of nowhere.

For most people, dealing with things that you can’t directly perceive boils down to matter of belief.  Your average Joe really doesn’t have much grasp of scientific method, or Koch’s postulates, or clinical trials.  Or science in general, for that matter.

And so, ultimately, for most people, taking proper COVID-19 sanitation measures is a matter of belief.  You have to believe that COVID-19 is transmitted by invisible particles passing through the air.  And your faith has to be strong enough that you’ll take the right actions to prevent that.

So when the Governor of Oklahoma decided to have a day of fasting and prayer, instead of a mask mandate, this struck many people as odd.  And I have to count myself among them.  (Despite Post #567).   Apparently the governor has faith that the invisible hand of God will help his people.  And so he called on the citizens of Oklahoma to pray for those who’ve already caught COVID-19.

But at the same time, his faith in the germ theory of disease is not strong enough for him to require people to wear masks, to avoid catching COVID-19 in the first place. Continue reading Post #908: Hebrews 11:1

Post #907: Social distancing rule + quarantine rule = insanity.

Source:  Japan Ministry of Health.

I’m not confused because I’m stupid.  I’m confused because I’m paying attention to what they’re actually saying.

Let’s see if you can find the inconsistency in current CDC advice.

The social distancing rule:  The CDC continues to focus on “social distancing” as the primary defense against spread of COVID-19.  That means staying at least 6′ apart.  The theory there is that people who cough or sneeze emit “droplets” containing infectious material.  And if you stay at least that far away, you are unlikely to be hit by somebody’s droplets.

AND

The quarantine rule:  If you’ve been exposed to COVID-19, you need to quarantine yourself for 14 days.  (Or fewer — see below).  You need to do this whether or not you have any symptoms at all.  Because asymptomatic or pre-symptomatic individuals can spread COVID-19 quite effectively.  And you could be spreading disease without knowing it.

Does it seem like I have that right, more or less?  The CDC added masks to that social distancing rule, but only after the fact. Only as kind of an oddly-worded add-on recommendation.  And the CDC has recently added some grudging mention of aerosols (tiny drops that can float on the air) in addition to droplet transmission.

By and large, I think the paragraphs above capture what the CDC has told the American public.  Maintain social distancing to avoid the droplets produced when people cough or sneeze.  And quarantine yourself for 14 days if exposed, even if you have no symptoms.  And wear a mask, too.

Now let me get down to the insanity part, by putting those two rules together.  You must maintain social distancing, because when people cough or sneeze, they emit droplets that can travel up to 6′ and transmit infection.  And if you’ve been exposed, you must quarantine even if you have no symptoms and are not coughing or sneezing, because you might transmit infection.

This mish-mosh of internally-inconsistent guidance is an historical artifact.  It’s the result of the way the CDC policies have evolved over time.  In particular, it’s the result of the CDC being unwilling to admit that aerosol transmission matters.  (Aerosols being tiny particles, smaller than “droplets”, that can float on the air well beyond the standard six-foot social distancing barrier.)  And only making grudging and piecemeal changes to its guidance, that kind-of, sort-of, recognized the importance of aerosol transmission.

You can see the apex of that process in Post #822, when the CDC issued and then immediately revoked guidance with clear discussion of aerosols. You can review the long, winding road to get to that guidance, in Post #820. The CDC did eventually produce guidance so larded with weasel-wording on this key issue as to be more-or-less unusable.  You can see that discussion in Post #850.

They key problem here is that if aerosol transmission matters, then social distancing is not an adequate way to prevent spread of COVID-19.  For the simple reason that aerosols routinely spread beyond six feet.  And so, for the CDC to go all-in on aerosol transmission is for them to admit that they offered really fundamentally bad advice to the American public.  And so, they can’t really admit it.  And we end up with the current internally-inconsistent and piecemeal advice from the CDC.

This has a couple of immediate impacts on health care policy.

First, many U.S. states continue to base their own recommendations on the original CDC “social distancing is the main line of defense” message.  And so the effect of the mixed and unclear CDC guidance has been to promulgate state mask mandates that make mask wearing an alternative to social distancing, only if social distancing cannot be maintained. 

Iowa, for example, passed a mask mandated in the middle of November (Post #893).  It requires individuals to wear masks, indoors, in a public place, only if they are unable to maintain 6′ social distancing, and are unable to maintain it for more than 15 minutes.  So in Iowa, you’re required to wear a mask only where social distancing fails for an extended period of time. 

And so, if aerosol transmission matters, and social distancing alone is an inadequate public health measure, the upshot of all of this confusion from CDC is the creation of state-level rules that sanction dangerous behavior.  That Iowa mask mandate tells the people of Iowa that not wearing a mask is good sanitary practice, as long as you aren’t within six feet of an individual for more than 15 minutes.

So Iowa, following the main CDC message, has now told its citizens that it’s perfectly fine to (e.g.) meet somebody for a cup of coffee and have a 10-mintue face-to-face chat.  With no masks.  Because masks are only an needed if you’re going to spend 15 minutes or more in that situation.

Second, more recently, the CDC seems to have finally woken up to the fact that people who don’t feel ill aren’t doing the recommended 14 days of quarantine when exposed to COVID-19.  So they’ve decided to shorten the quarantine period for those with no symptoms.  The theory being, I guess, that the increased compliance with a shorter quarantine more than offsets the handful of individuals who will still be infectious at the end of that shorter quarantine period.

The entire change is aimed at asymptomatic individuals.  If you’re coughing or sneezing, or have any other symptoms, the new rules do not apply.  But if you’ve been exposed to COVID-19 and have no symptoms, you only have to quarantine for ten days (without testing) or seven days (if you get a negative COVID-19 test).   You can read the actual CDC recommendation here.

If the CDC ever gets to wondering why people who didn’t feel sick didn’t stick to a 14-day quarantine, I think it should start by looking at its own advice and messaging.  They start out by pressing that sneezing-coughing-droplets-distancing message.  Then they turn right around and try to tell people that, well, we were just kidding about that whole sneezing and coughing thing.  That doesn’t really matter, after all.  Just do your 14 days regardless.

And, unsurprisingly, a lot of people seem to be ignoring that second message.  So now the CDC is trying to patch that up a bit, by recommending a shorter quarantine for asymptomatic individuals.

But what they really need to do is rethink this from square one.  In light of what we now know, if you could rewrite the CDC guidance from scratch, what should it say?  At the minimum, if you want asymptomatic individuals to take this seriously, you’d start by dropping the whole sneezing-coughing-droplets party line.  Go straight to droplet or aerosol transmission.  Note that social distancing alone is inadequate.

And replace the current patched-together guidance with a single, unified, easy-to-grasp message.  Something akin to what the Japanese have been telling their population from Day 1, shown at the top of this posting.  Compare that, to whatever the current CDC guidance is, and you’ll see that our guidance just does not measure up.

Post #906: The schmutz does not lie.

What you’re looking at above is the end result of using a type of Corsi Box, as described in Post #854.  That’s a fancy term for a cheap box fan with an HVAC air filter (or filters) attached.

Hence the circle of schmutz, on the air filter above, mirroring the circular blade of the box fan.

That filter has been running in the simple setup pictured below for a few months now.  That’s a Filtrete ™ filter literally sitting behind a cheap 20″ box fan, held in place by the slight suction created by the fan on its lowest setting.

At the very least, I can now guarantee that this setup won’t burn out the fan motor.  Not in any short period of time.  Based on the dates on the photos, I’m just about at the three-month anniversary for this filter.

An actual Corsi box is constructed using cheaper (but higher resistance) high-MERV-rated filters.  Corsi recommended using five, literally set up as a box, with the fan as the sixth side of the box.  Instead, I did the obvious thing and used a single high-end 3M Filtrete ™ filter.  It gives good filtration of aerosol-sized particles and has low resistance to air flow, but is fairly expensive.

(You can find discussion of all the common filtration standards in Post #593, which walks through all MERV, MPR, N95, HEPA, and other common filtration standards for air filters, masks, and other air filtration devices.)

 

 

And as you can see, this is about as minimal-effort as it gets.  Unwrap the filter, sit it behind the fan, and turn the fan on low.  It works even though the filter is actually sitting backwards on the fan (because I didn’t feel like tearing off the yellow filter timer on the back of the filter).

The idea of using cheap box fans and filters keeps popping up as a way to make indoor spaces safer.  As outlined in Post #810.  There’s no way to know if this will ever catch on, in part because nobody is going to test this, in any realistic way, as a way to prevent indoor spread of COVID-19.  So even if you use setups like this, as suggested in Post #810, you can’t legally advertise that it reduces COVID-19 risk, because there’s no direct proof that it does.

Separately, based on what has gone on in (say) South Dakota, a lot of important people still can’t quite get their mind around the idea that things they can’t see can harm them.  The idea that seemingly clean-looking air might be filled with tiny little particles that can hurt you.  I guess that’s a bit of a stretch even for those of us who accept the germ theory of disease.

And if you don’t grasp that simple fact, then the idea of filtering the air that you breathe makes no sense.  But what is a mask, if not a crude and portable version of the filter above.  In my case, the mask is literally made out of the same material used in that air filter pictured above (Post #780, Post #807).

So a lot of people don’t quite seem to get it.  But the schmutz does not lie.   Even though I can’t see it, and the air looks perfectly clean, all of that came out of the air in my home.  In any urban area, air that looks completely harmless is laden with particulates.  It’s really no big stretch to go from aerosol particulates from diesel vehicles to aerosol emissions from people.

So, for those people who can’t seem to believe in physical things that they can’t see, it might be worth stopping to ponder just where all that schmutz came from.  On that high-end air filter pictured above.  Some of it is common household dust.  Some of it is PM2.5, aerosolized air pollution around 2.5 microns in size.  And some of it, for this filter, will be as small as the smallest aerosol particles that carry coronavirus.