Post #909: Thanksgiving data artifact. I think.

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.

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 breath 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.

Post #905: Virginia nears the bottom of the pack

This is how I see the U.S.A today.  Starting from the bottom of the legend, the bright red states all had a high rate of new COVID-19 cases and a very sharp peak rate that occurred in late November.  Moving to the other end, almost all the East Coast and West Coast states have similar low upward trends in new cases.

What I find so interesting is how nicely geographically clustered this looks.

  • Everything in north-central part of the country peaked late last month.
  • That’s ringed with non-coastal states that have a high current trend.
  • Wheras almost all the coastal states (except Rhode Island) have low upward trends (currently under 40 new cases/100,000/day.) or moderate upward trends (40 to 60 new cases/100,00.day).

Details follow.

Continue reading Post #905: Virginia nears the bottom of the pack

Post #904: Dryer air arrives in Virginia

Source:  National weather service (forecast.weather.gov), downloaded 12/2/2020.

I’ve been tracking the relative humidity in my house for roughly the past month.  November had relatively few days with truly dry outdoor air.  Air that was both cold, and had low relative humidity.

Unsurprisingly, I’ve had to run my indoor humidifier infrequently, so far this year.

Today, and looking forward to the forecast for the next two weeks, that appears to be changing.

As shown above, today is cool and dry.  That 31% outdoor relative humidity (at 47F) would result in a roughly 15% indoor relative humidity at 68F, absent any other inputs of water vapor into the indoor air.  Today my humidifier is running constantly but my indoor humidity is slowly dropping anyway.

For the next two weeks, it looks like a typical day will be 45F with 55% outdoor relative humidity.  Absent any other inputs, those conditions will translate to an indoor relative humidity of 25% at 68F.  That’s a long enough period that houses and other indoor locations should be fairly well dried out by the end of it.  Absent a humidifier, indoor air in this region will be quite dry by mid-December.

If you wonder why I’m tracking this, refer to Post #894.  I heard from a few readers who purchased humidifiers after reading that.  If you have one, but haven’t unboxed it and set it up, now would be a good time to do that, I think.

Post #903: Population weighted trends

Why do you keep hearing that the US third wave of COVID-19 is getting worse, when most of the states appear to have peaked?  Like so:

The answer is that the US totals reflect the US population.  And the (mostly) upper-Midwest and Mountain states that have peaked are all low-population states.   There was a lot of COVID-19 activity there, but there aren’t a lot of people.

By contrast, over one-third of the US population lives in just five states (CA, TX, FL, NY, TX, PA).  And in those states, you are still seeing a broadly-based and slow ramp-up of COVID-19 activity.  I would say that they show almost weirdly similar paths, given how different those five states are from one another.

In fact, we have to broaden the view to the top ten states (encompassing more than half the US population) before we pick up even one of those Midwest states where there appears to be a clear peak in COVID-19 activity.  In the graph below,  the top line is Illinois.

And so the third wave of COVID in the US has this odd multi-part nature.

First, there were crazily high growth rates for daily new COVID cases in a cluster of Midwest/Mountain states.  That’s the peak of the mountain on the first graph above. All the states where the growth rate at some point exceeded 100 new cases/100,000 population/day.

Those high rates of growth seems to have “burnt out” for the time being. Most of those states appear to have peaked just prior to Thanksgiving.  Why those peaks were so nearly synchronous is something of a mystery, and probably always will be.  But, for at least one state — North Dakota — enough people got infected during that period that they have plausibly reached COVID-19 herd immunity, or close to it (see Post #901).

But where the bulk of US residents live, we’ve seen nothing quite so dramatic.  Instead, as winter slowly settles in, the COVID-19 new infection rates have slowly risen.

What’s I find particularly odd is that “winter” means different things, weather-wise, in those different states (CA, TX, FL, NY, TX, PA).  And yet, the lines on the graph look almost identical.

NY, PA, and TX all have what I would call a “traditional east coast” winter climate.  If you were to look up today’s forecast for Dallas and for Philadelphia, you would be hard-pressed to tell which was which without the labels.

Florida spans everything from more-or-less that climate (in central Florida) to a subtropical climate in South Florida.  And yet, the entire state shows high rates of COVID-19 activity.

California, or at least Southern California, is hot and dry right now, having recorded zero precipitation for November, and frequently recording outdoor relative humidity below 20% (due in part to Santa Ana winds).

And yet, we’re seeing more-or-less the same slow rise in new cases in all five states.  I guess that’s just another seemingly random aspect of this pandemic.

Post #902: The US third wave. Oddly orderly.

Source, here and below:  NY Times Github data repository.

The graph above is the US pandemic since April 1, by state.  As you can see from the height of the peak, the rapid growth in the upper Midwest and Mountain states was unprecedented.  But at this point, it looks like almost all of those high-growth-rate states have peaked.  And, weirdly enough, almost all of them at the same time.

Maybe that’s some artifact of Thanksgiving, but offhand, I don’t quite see how.  The states at the very top of the graph began to peak (in hindsight) one to two weeks before Thanksgiving.

For sure, this isn’t a consequence of recent actions by some of those state governments.  As discussed in my just-prior post, any consequences of (e.g.) mask mandates in IA or ND will begin to show up only toward the end of November.

Below is the tail-end of the same graph, starting 10/1/2020.

By eye, the lines for the various states sort themselves into three orderly groups.

  • Everything above the 100 new cases/100,000/day line shows a sharply-defined peak.
  • Everything from 60 to 100 new cases/100,000/day appears to show a broad, shallow peak, roughly coincident with the sharp peaks in the high-growth states.
  • Almost everything below 60 new cases/100,000/day does not year appear to have peaked.

Most of the lines 100 and above are for upper Midwest and Mountain states.  Most of the lines 60 and below are for East Coast and Southern states.  And the lines in the middle are a bit of a mixed bag.

I have no real idea what might be causing this.  Or whether I’m just reading too much into the graph.  I’m just noting how orderly and geographically clustered the third wave appears to be.  And that, for now at least, in the areas with the highest recent growth rates, the third wave appears to be peaking.

Here are the numbers, sorted in descending order of new cases/100,000/day, showing how far past peak each state is, and by how much.  E.g., South Dakota still has the highest rate of new cases/100,000/day, but the peak rate occurred 15 days earlier, and right now they are one-third (33%) below that peak rate.

States where the peak occurred recently, and where the difference from the peak is small, are states there the rates are probably still climbing.

 

Post #901: Maybe ND really has achieved herd immunity.

Source:  NY Times Github data repository, data reported through 11/27/2020.

This is one of those seemingly simple 2+2=4 analyses.   In this case, it’s literally 8*10 > 70.

The arithmetic isn’t rocket science.  Anybody can do that.  My only value-added here has been in keeping an eye on the situation, and realizing why that arithmetic might matter.

Right now, 10% of the population of North Dakota has been formally diagnosed with COVID-19.   As of data reported through 11/27/2020, they’ve had 77,242 known cases.  That’s out of a population of about 760,000 (per the US Census Bureau).  Or (77,242/760,000 = ~) 10%.

A 10/25/2020 publication by CDC staff says that, best estimate, on average, 8 people have had COVID-19 for every one that has been diagnosed. 

IF CDC staff are right, and IF that US average applies to the US Midwest, then North Dakota has probably achieved COVID-19 herd immunity.  Or is close to it.  And much of the US Midwest has or will be following suit in the near future.

Obviously, that’s two big ifs.  But anybody can follow the math.  That’s 8*10% = 80%, and that’s higher than the 70% conventionally thought to be required to achieve herd immunity to COVID-19.

Oh, and note the peaks on all the curves at the top of the graph above.

Discussion follows.  This brings together several points that I’ve brought up over the past two months or so. Continue reading Post #901: Maybe ND really has achieved herd immunity.

Post #900: Peak of the third wave: Is “dynamic herd immunity” capping the rate of spread of COVID-19?

Source:  Data from NY Times Github data repository.  Data reported through 11/23/2020.

An odd thing has been happening, even as the news is dominated by the worsening of the third wave of the pandemic nationally.  That third wave of US COVID-19 appears to be cresting in the states that led it.  And the strange part is that simultaneous crest across several states has nothing to do with any actions recently taken (or not taken) by state governments to contain the virus. 

The mere fact that some hard-hit states appear to have peaked, in terms of new COVID-19 cases per day, is not the odd part of this.  Here’s what’s odd.

First, note that several states peaked at just about the same time.  Within, say, a week of one another.  Two states peaking in the same week could be a coincidence.  But six or seven states?  Spanning more than 1000 miles?  All of them with extremely high rates of new COVID-19 cases per day?  It’s hard not to think that there’s something that ties that together.

Second, note that this peak occurred despite some states taking action and others not. Famously, for example, the governor of South Dakota refuses to institute a mask mandate or take other protective measures.

Third, note that these peaks occurred well before we could plausibly expect to see any results of any state actions, in any case.  For example, ND and IA mask mandates were passed 11/14/2020 (Post #890) and 11/17/2020 (Post #893), respectively.  Any reduction in infections that result from those changes could not possibly appear in the data prior to the end of November.

That’s due the “pipeline” of cases that are already infected, at any point in time, but haven’t yet appeared in the numbers.  It takes, on average, in most areas, about 12 days for any change in infection rates to appear in the data.  (That’s about five days from infection to onset of symptoms, and then another 7 on average for seeking medical attention, getting tested, and having the test results appear in the data).

Meanwhile, three other states in that vicinity have high case rates and continue with a relatively steep upward trajectory.  But all are well below the peak demonstrated by ND.

Finally, I need to supplement the above with one chart of states that got covered up in the tangle of lines above, and then the remainder of that block of states.

Note that, in particular, MN appears to have peaked in the last week.

And when I put that all on one map, it looks like this.  The block of green-ish states are those that a) had high rates of new cases and b) all appear to have peaked in the past, oh, week or so.  The red-ish states are those, in the same area, with high rates of new COVID-19 cases, but where trends continue upward, with no evident peak or leveling-off of new cases per day.

All pandemics are local.  And by that I mean that you’re going to be reading news articles about individual cities, within those states, that are running out of hospital beds.  And will continue to do so for some weeks.  But in terms of total cases within the states, for some reason, almost all of the states with extreme new-case loads decided to do a 180 in the past couple of weeks.  All in the same geographic area.  All at the same time.


Speculation on what might cause this.

First, let me be clear, I have no firm idea on what is causing this.  I just noticed the oddity, that’s all.

1:  Maybe it’s the weather, and so this break is temporary.  I note that this area had a heat wave just about weeks before these states started peaking.  That should have temporarily raised indoor relatively humidity, and if humidity is key to transmission (Post #894), should have slowed transmission.  And so, maybe this isn’t a peak, but it’s just a temporary break in the trend, due to that past weather event.

The problem there is that the heat wave affected all of those states.  Here’s Bismark, ND and Cheyenne, WY.  Pretty much the same weather pattern across both areas.  If it were solely an artifact of weather, we’d see a break in the trend for Wyoming.  Which we do not.

2: Maybe people wise up before their state government does.  The high incidence of COVID-19 in these states was public knowledge.  Maybe there’s some common threshold of hard-headedness that people can get past, with enough news coverage of how dire the situation is becoming.  And so, these peaks are an artifact of enough people waking up to the situation and changing their behavior, in each state, to break the back of the upward trend.

But the sharp reversals of trend, and the tight synchronization, don’t really seem to fit with that.  At least, not to my eye.  This has the look of something far more mechanical or automatic, and less the look of (e.g.) the will of the people shifting in favor of mask use.

3:  Maybe this is how herd immunity works in this situation:  It generates a natural cap on the rate of spread, for a given set of underlying conditions.  We keep hearing that we need 70% of the population to be immune before we achieve “herd immunity”.  That’s the point where the pandemic dies out for lack of enough “infectable” people to maintain the chains of disease transmission.  But maybe herd-immunity-type effects also limit continued rapid spread.

Herd immunity is not going to be a smooth process.  It’s not as if you’re going to run right up to the herd immunity level, and then have the pandemic stop all at once.  Instead, as a smaller and smaller portion of the population is at risk of infection, presumably the rate of transmission would slow.

At this point, best guess, somewhere around a quarter to a third of the entire population of North Dakota has already been infected with COVID-19.  (See Post #889 for details.)  That’s the roughly 8 percent that had been formally diagnosed, as of mid-November.  Times some unknown multiplier to account for cases that were never diagnosed (asymptomatic individuals and individuals with symptoms mild enough that they did not seek treatment or diagnosis.)

I’m not familiar enough with the techniques used to model epidemics to say for sure, but I’d bet that having a third of your population immune to the disease is enough to put a crimp in the rates of spread.  It might not stop it, but it might plausibly prevent the highest possible rates of spread from occurring.  Except for the fact that COVID-19 spreads largely via clusters, you’d be tempted to say, well, at this point, a third of the chains of infection that used to continue are now being truncated by running into an immune individual.

The point here is that that maybe the basic arithmetic of this pandemic makes the rate of spread somewhat self-limiting. Once it reaches some high rate of new cases per day, for long enough, the rate has to go down due to the rapid build-up of surviving immune individuals.

Notably, the case mortality rate for COVID-19 is now quite low (e.g., about 1% in the Commonwealth of Virginia).  That makes the situation for COVID-19 materially different from that of the 1918 Spanish Flu. With this low mortality, if  COVID-19 tears through a population rapidly, then it rapidly builds up a large population of immune individuals. And that large population, while not enough to stop the pandemic from continuing to spread, may be enough to cap the rate of spread.  The very fastest rates are no longer feasible, because enough chains of transmission are being truncated.

If so, that’s very good news for my “reefer test” ( Post #888).  That means that the rates won’t continue to climb until you finally run out of potential victims.  Instead, for a given set of circumstances, you’ll see the rates all peak around the same point.  And the commonality of that peak occurs because you’ve built up enough survivors to “clog up the works” just enough to cap the rate of spread.

As a footnote, I’ll bring back an earlier version of the diagram above.  Oddly, note that the two peak summertime states both peaked at just about the same daily rate of new cases.  Despite being in completely different climates and locations.  That was for the air-conditioning-led summer outbreak.  And now, with what I’d call the heating-led winter outbreak, we’re kind of seeing the same thing.  Just at a different level of new cases per day.

(But that may just be reading too much into the data.  There was a spectrum of peaks in the summer outbreak.  Obviously, the ones at the top are all going to be near the top.)

4:  Does “herd immunity” really require 70% of the entire population to be immune.  Maybe you run out of risk-takers well before 70% are infected.

How about people like me, who are basically minimizing exposure already, scrupulous about mask use, and wearing an aerosol-filtering fitted mask when shopping (Post #780, Post #807).  Does herd immunity require 70% of people in my situation to be infected before the pandemic stops on its own?  Or, by dint of isolating myself, am I more-or-less irrelevant to the herd immunity calculation?

Let me put it this way:  A vaccine provides (we hope) 90% protection against being infected.  We count (90% of) the vaccinated population as part of that 70% in the herd immunity calculation.

But suppose that a good mask and careful behavior results in 80% protection against being infected.  What’s the difference, exactly, between that, and being vaccinated?  (In terms of the herd immunity concept.)  The vaccinated individual is assumed to be (more-or-less) permanently removed from the pool of persons who can be infected.  The mask-and-behavior person remains at risk of infection, regardless.  So there’s clearly a long-run difference — the virus can slowly “pick off” persons from the mask-and-behavior pool, but not from the vaccine pool.  But in terms of breaking the chains of transmission, in the short run, I’d say that those two routes to stopping spread of the virus are roughly equivalent.  One terminates 90% of the chains, the other terminates 80% of the chains.  So to speak.

And so maybe, at some point, the population of risk takers that is responsible for high rates of spread gets thinned down somewhat.  Not by mortality, but by becoming infected and so becoming immune.  And so, even if just a third of ND residents are immune, maybe that’s a lot closer to 70% of the risk takers.

If so, the rapid spread attributable to failure to take precautions might be self-limiting well before 70% of the entire population is immune.  Maybe, to prevent the most rapid spread, all you need is 70% of the risk-taking population.  And that might be a much smaller fraction than 70% of the entire population.


Best guess:  “dynamic herd immunity”.

These synchronized and rapid reversals of the upward state trends, for the states with high growth rates, suggest a mechanistic explanation, rather than a behavioral one.

For sure, it’s not a result of government action.  That’s been piecemeal, and in key states (ND, IA) occurred far too recently to account for the turnaround.

The weather is something that would affect a broad area.  But the same heat wave that plausibly might have resulted in the peak in (say) SD also affected states where a peak has not yet occurred, such as WY.

Having the populations of these states all “wise up” at the same time seems improbable, given how close the timing is.

My bet is that the rapid growth is self-limiting.  The virus leaves so many immune survivors behind, in such as short period of time, that it chokes off that very rapid growth.  So it’s not herd immunity (that disappearance of the virus) but instead a natural limit on the rapid spread.  Rapid spread can only go on for just so long before it (in effect) chokes on its own impact on the population.

Let me call this “dynamic herd immunity”.  That’s the idea that a high rate of spread can go on for just so long before it has to slow down.  And that it will slow down well before 70% of the population has been infected.

How long that high growth may continue, and how rapid that growth can be, will of course depend on underlying conditions.  In these mask-averse states with dry and cold winters, that can proceed much faster than it might in states with good mask use and milder climate.

Seeing all these states, all peaking around the same time, around the same growth rate, suggests that there’s something about the mechanics of epidemics at work here.  My best guess is “dynamic herd immunity”.  A high rate of new case growth chokes itself off, at some point.  The virus will still be spreading, but at a slower rate.  And if so, that’s very good news from the standpoint of running out of hospital beds.  Maybe the lower apparent severity of the average case (Post #897), and “dynamic herd immunity”, mean that we won’t have to fail the reefer test after all.  We’ll manage to get through this, despite ourselves.