Post #921: North Dakota: Is this what herd immunity looks like?

Posted on December 17, 2020

The news media don’t pay much attention to places that aren’t having trouble.  But in the case of North Dakota, I think it’s pretty important to keep your eye on them even as their situation brightens.

I started out by joking about North Dakota and herd immunity  (Post #889, Post #890).  Then, at some point, that wasn’t a joke any longer (Post #900, Post #901).  So in this post, I’m not even going to try to be amusing, because this is going to be a hard thing for many people to accept.

When looking at the situation in North Dakota, I think it’s important to try to separate out your value judgments from your analysis of the facts.  As a value judgement, I think that letting many people die because you’re too stubborn to wear masks and want to return to a more relaxed lifestyle is a piss-poor way to respond to a deadly pandemic.   As well as being an inefficient way to deal with it.

But purely as a matter of fact, I can’t deny that it should work. Even if they stumbled into it by denying and ignoring all the best public health advice.  Even if nobody planned to have it play out this way.  Purely as matter of fact, if enough people get infected, your population ought to get to herd immunity.  Minus the ones that died on the way. 

And ignoring the unnecessary risk imposed on hospital staffs and first responders, the permanent organ damage for some survivors, the substantial burden on the public purse for paying for those unnecessary hospitalizations, and so on.   It’s a strategy, but don’t expect me to say it’s a good strategy.

So I’ll just go ahead and say it.  I think this is the best best explanation of what’s happening now in North Dakota.  I’m guessing they’re closing in on herd immunity, and that the pandemic there is winding down of its own accord.

Extreme change in one month.

Let me start by highlighting how extreme the North Dakota experience is.  In the span of one month, they went from having the highest rate of new COVID-19 cases/ 100,000/ day, to having the lowest rate in the entire mid-section of the U.S.

(For every graph below, ignore the little spike on the right.  That’s due to a change in their data reporting, as documented in Post #912.

Source: Calculated from NY Times Github coronavirus data repository data.

As you can see above, the seven-day moving average of new cases for North Dakota is the lowest in the Midwest.

And, in fact, it’s the lowest in the entire middle of the country (Midwest, South Central, and Mountain regions).  The black line below represents the current ND rate.

Only nine U.S. states currently have a new case rate below that of North Dakota.  Those are all Atlantic coast or Pacific states.

Not plausibly the result of policy changes.

I want to emphasize the timing of this, because North Dakota did, in fact, put in an extremely weak mask mandate.  But:

  • They did that only after new cases had peaked.
  • Cases were falling well before any impact of that mask mandate should have worked itself into the data.
  • South Dakota is following the same pattern, and South Dakota has no mask mandate.

The ND mask mandate went into effect on 11/14/2020.  It takes (by my estimate) about 12 days for any policy change to begin appearing in the data.  (That’s the median total lag between being infected, showing symptoms, seeking medical help, getting tested, and having the test results appear in the data.)  Others suggest lags of up to three weeks.

In either case, we would not have seen results from the policy change prior to the end of November.  And yet, cases peaked in mid-November and were steeply declining by the end of November.

Other states in the area are following the same pattern with no notable changes in policy.  Most notable, South Dakota is on roughly the same trajectory as North Dakota (just not quite as extreme).  And the South Dakota governor famously refused to impose any sort of mandate.

Plausibly the result of nearing herd immunity.

As I noted in earlier posts, this is not rocket science.  You guess how many people have already been infected with COVID-19 in some population.  And you compare that to a guess as to how many need to be infected to achieve herd immunity.  And the only hard number in the whole calculation is the fraction of the population that has actually been diagnosed with COVID-19.

As of yesterday, about 12% of the population of North Dakota has been formally diagnosed with COVID-19.   As of data reported through 12/16/2020, they’ve had 88,686 diagnosed cases.  That’s out of a population of about 760,000 (per the US Census Bureau).  Or (88,686/760,000 = ~) 12%.

But there will be a lot of people who’ve had it, and didn’t get diagnosed.  That fraction certainly has to vary from place to place.  And the data by which you might estimate that fraction is fairly sketchy.  But putting that aside, CDC staff have recently doubled-down on an estimate that the total number of infected persons is about eight times the number of diagnosed persons.  (If you want the reference, read my earlier posts cited above.)

And a common guess for the herd immunity level for COVID-19 is 70%.  If 70% of the population has had it, and so is presumed immune, then the pandemic will die off for want of diseases carriers.

So, slapping those three numbers together with all the accuracy and care that they deserve, I get:

12% x 8 = 96% > 70%.

I cannot be sure they’ve achieved “herd immunity”.  But as that 12% continues to rise, the odds that they have achieved herd immunity continue to increase.

Heck, I’m not even sure how “herd immunity” is supposed to play out.  But just pondering the arithmetic a bit, I’m guessing that the higher they rise, the harder they’ll fall.  Meaning that the highest peak rates of total fraction of population infected ought to lead to steepest declines in new infections.  And that you’ll need a steeply rising infection rate to achieve that peak (else herd immunity starts to slow you down.)

And so just eyeballing and spitballing here (ew!), the whole broad arch of the Midwest, shown above, kind of makes sense, if herd immunity is putting the brakes on the pandemic in those states.  Places that skyrocketed up hit that magic herd immunity percentage quickly, and then fell rapidly.  Places that increased at a slower rate should show a shallower but much longer peak, as the effects of herd immunity slowly dampened the rate of spread of disease.

And if that’s right, what we’ll see in the next few weeks is that the states at the top of this list are going to fall to the bottom of states ranked by daily new cases.  I.e., those arch shapes should continue, and the ones with the sharp peaks are going to be the ones with the steepest drops as well.

We can only wait and see.  And a trend is a trend until it ceased to be a trend.  But if herd immunity is now the dominant factor controlling trends in the Midwest, I bet that North Dakota has one of the lowest rates of new infections per capita by New Year’s Day.  I’ll put that marker down, and check back in a couple of weeks to see how that turned out.