Coyote Blog

1.  Here is the iron law of medical -- in fact all scientific -- studies in the modern world: most do not replicate.  This has always been true of studies that supposedly find some link between doing [thing we enjoy] and cancer.  This of course does not stop the media from running with initial study results based on 37 study participants as "fact."  The same is true for studies of new drugs and treatments.  Most don't pan out or are not nearly as efficacious as early studies might indicate.  We have seen that over and over during COVID.
2. The Feds insist that a drug that is know to be perfectly safe in humans still must be carefully tested in random controlled studies before it can be used for a new application.  Fine, I think they are overly cautious in application of this, but let's run with this standard for a moment.  Why, then, are NPI that have known astronomical human costs (eg lockdowns, business closures, and mask mandates) allowable without any sort of study -- allowable in fact when the existing science on their efficacy is at best ambivalent?

Update:  In case you wonder why they don't replicate

Five years or so ago I remember it was a popular social media poll question in this country to ask where one would live if they could not live in the US.  I remember that Australia and New Zealand were often near the top of the lists.  Which leads me to ask today -- would anyone, after watching the extraordinarily totalitarian response of these two countries to COVID, answer the same way today?  I certainly would not.  The country of Crocodile Dundee has morphed before our eyes into the country of some weird fascist version of piglet in the 100 acre wood.

I have wondered for a while what Australia was thinking of -- long-term -- with its COVID zero policy.  Let's say they were successful in their country eliminating COVID cases.  Now what?  They would soon be a nation of non-immunes in a world that has largely come out the other side of the pandemic.  This is particularly true now that we have a better sense that existing vaccines are more of a before-the-fact treatment to reduce the severity of the disease than they are absolute immunity to catching the thing, at least in some mild way that triggers an overly-sensitive test.

Were the Australians going to permanently wall themselves off from the rest of the Earth?  Refuse to participate in the world economy?  Because the one thing that is absolutely certain is that reservoirs of the disease would still exist -- heck, there are still small whooping cough outbreaks in the US, and a couple hundreds polio cases around the world each year.  Perhaps they were hoping the disease would morph into something less deadly, as most viruses do (most all parasites will mutate over time to spread more easily but be less likely to kill their hosts).   If this is the case, it is sure strange given that the people most in favor of extreme government interventions are the exact same people who seem unable to recognize the Delta variant as being less rather than more deadly.

Well, the sort of good news is that the Australian government has announced that it is willing to release the citizenry from its hostage status once 80% are vaccinated.  I personally was vaccinated very early on (so early that I may soon not be counted as vaccinated) and would urge most adults without any unusual medical conditions get one as well.  It is not going to stop you from testing positive at some point, but it very likely will keep you off a ventilator if you do get COVID.   If you are in Australia, I certainly would recommend it as a small price to be released from captivity.

It should not be surprising that any roundup I do of problems with COVID response would include a chapter on metrics -- I am a very strong believer that metrics and incentives live at the very heart of most private and public organizational failures.  I already dealt with incentives in part I, though I will come back to them a bit in this piece.

For the metrics, I want to focus narrowly on the selection and quality of COVID-related tracking metrics.   Perhaps I will cover this in a later chapter, but I will not cover that absolutely awful performance of the media in reporting COVID data and COVID-related science.   Suffice it to say that the media has once again shown itself absolutely incapable of reading a scientific study and assessing the quality of the methodology, or parsing the true results of the study vs those ascribed to the study in the press release.  Inherent problems in the data, such as the time delay for death reporting, have been made an order of magnitude worse by the media's inability (unwillingness?) to explain shortcomings in the data.  Is it really so hard to explain how deaths reported yesterday in such and such state did not actually all occur yesterday and in fact represent data updates sometimes weeks old?  This simple bit of clarity has been a bridge too far for most of the media.

Poor Data Quality

For the last 18 months, we have had to work with absolutely awful data on COVID.  I am willing to believe that in March 2020 we had excuses for not knowing what we were doing.  But now?  Some examples:

• We are testing for COVID using PCR tests that are far too sensitive.  These tests use a series of cycles to concentrate the virus being searched for.  Many tests are being conducted as high as 40 cycles, which pretty much everyone agrees is way too sensitive and is likely to give false positives.  Given the importance of this cycle number, it is astounding that in 18 months I have never seen -- not once -- a media article that has a statistic on positive COVID tests along with the cycle number at which these tests were conducted.
• Hospitalization data is skewed by the fact that hospitals have strong financial incentives to report patients as COVID patients.   This means a dude in a car wreck who tests positive for COVID once brought in might be listed as a COVID patient, despite the fact that this person fits no definition any of us have for what should count as a COVID hospitalization.  Retrospective studies have consistently shown huge overcounts of COVID patients, confusing "patients with COVID" with the more important "patients who were hospitalized because of COVID."
• Most retrospective audits have found that COVID death data suffers from the same over-reporting as hospitalization, as a person testing positive for COVID but dying of a stroke might still be listed as a COVID death
• I have no idea what is going on in many states with COVID death reporting delays.  We still see COVID deaths being added to counts for dates months in the past.  Why the long long delay?  Is there some sort of reclassification going on, and if so why? If not, given that we literally have spent trillions of dollars on COVID response, why can't we fix these data issues?

Following the Wrong Metric

The metric we should really care about is deaths (or given the fact that COVID deaths skew so old, perhaps total life-years lost to COVID).  After all, if we are to be honest, it is the prospect of death and not getting really sick that has certain elements of our population nearly catatonic in fear.  The problem is that even without the death reporting problems outlined above, deaths are way too much of a lagging indicator to be useful in spotting early trends.

Unfortunately, though, because the vast vast majority of positive tests for COVID are for folks who will never display anything but mild symptoms (and due to the testing issues discussed above), this is not a very good metric either.  But there is another problem -- all positive tests are not created equal.  A positive test of a health 20-year-old is pretty much the occasion for a big yawn.  A positive test for an 86-year-old with heart problems and diabetes is a cause of immense concern.  But the metrics do not differentiate.  We just see case counts on the news.  And note the ratio between these two extremes has not been stable -- early on a lot of the cases were in older folks, while today most of the positive tests are in young and healthy people.  Add to this the fact that we now have positive tests in the vaccinated, who are highly unlikely to die of the disease, and I would argue that 1000 positive tests in August 2021 are FAR less worrisome than 1000 positive tests in March 2020.  But again we treat them the same.

So Coyote, is this just academic?  I don't think so.  Personally I think we have seen several decisions of late that are impossible to justify based on science.  For example:

• Oregon governor orders that even the vaccinated must mask outdoors
• Many, Many school districts are demanding that kids as young as 3 must mask in school

Neither of these are supported by any science, and to the extent that the former discourages people from getting out of crowded cities and into the outdoors, and the latter discourages children from getting educated, they likely have net negative consequences.  So why?

I would argue the problem is that we have gotten stuck on cases (from overly sensitive tests) being the key metric.  Kids going back to school will almost certainly increase case counts, but for a disease that is less threatening to them than the ordinary flu, so what?  We are stuck on a stupid metric that no longer reflects actual risk and we have politicians mindlessly (see part 1 on incentives) managing to that metric.

So what metric would be better?

First, a good metric needs to really measure what we care about.  At some level, if we really think about it, we shouldn't really give a sh*t about case counts -- we care about people who die or have serious health complications from the disease.

Second, a good metric needs to be easy to calculate and reach the same figure no matter who does the calculation

Third, a good metric needs to be timely.  It is not helpful to have a collision indicator in the cockpit that only lights up 30 seconds after the plane hits the mountain.

Through the middle part of last year, I tended to look at hospitalization data.  It had its flaws (discussed above) but it struck me as the best balance between being timely (more timely than deaths) and indicating true risk (vs just cases).

I can envision a better metric: risk adjusted cases.  This could be as simple or as complicated as one likes, but I would favor a simple version that did not look at too many metrics -- maybe just 5 or 6 age bands and maybe vaccination status.  How it would work in its simplest form is that each case in the summary statistics would be weighted with a factor based on that person's risk of death.  For a simple version with age bands, this means that a case in the 80+ band might have a multiplier of 10 or greater while a case in the 0-18 age band might have a multiplier of 0.1 or smaller.  This would have been impossible to do last March but certainly by the time of the winter peak last year it would have been very doable.  We could easily do this today and back calculate the 2020 data for comparability.  I think age adjustment would be enough, I wouldn't get more fancy than that because we tend to have the age in the case data but not a lot else.  Perhaps we could add a factor for vaccination status as we measure that too.

This approach give us a much clearer idea of how much we should be worried about rising case counts and would be a better leading indicator of potential stress on health care systems 1-2 weeks out.

I understand that Afghanistan is falling into what is sure to be a heart-breaking mess as the Taliban quickly rolls up the country in a way that is quite reminiscent of South Vietnam falling to the North in the 1970s.   The rapid collapse of the Afghani government after the exit of most American troops will be used by many as evidence that we shouldn't have left, or that we left too soon.  In my mind, it's the opposite.

We have had 20 years to try to build a sustainable non-Taliban regime in Afghanistan and have clearly totally failed.  Again, we have failed to do so in a way that is surprisingly similar to our failures in South Vietnam (though at least without sustained bombing of population centers).  Holding on in Afghanistan has taken on the aspect of holding down a dead-man's switch on a bomb.  We seem unable to defuse it, but as long as we are willing to sit there, the bomb doesn't go off.  In this context, it should surprise no one that the bomb went off when we got up and left.

The silver lining is that given time and space to find their own way without a million foreign troops on their soil, the Vietnamese have steadily improved their country and the lot of their people.  Vietnam sits above Russia, Greece, and South Africa (and probably California) in the recent economic freedom rankings.

This does not mean that the Afghan people are not going to suffer over the next years and decades.  They will.  I feel for them.  But its clear to me at least the the US occupation is a dead end.  If liberty and prosperity ever come to the Afghani people, it will have to come through a different path.

Update:  Well, maybe not exactly this way.  I wrote this referring to the collapse of the Afghan government we had selected and propped up.  Clearly the ridiculous mistakes made on our exit that left Americans and our vulnerable friends without a clear path or plan for exit were not inevitable.

Part one of this series was on government incentives.  Part two of this series was originally going to be "managing to the wrong metrics," and we will still get to that topic in part 3.  But as I wrote that piece, it occurred to me that perhaps an even larger issue is not just working from the wrong data, but working from no data at all.

While it would be easy to attribute the "feelz before facts" bias to things like post-modernist thought, in actuality it is older than civilization.    I am pretty sure that panicked, emotional stories about Native American attacks on 19th century settlers grossly exceeded actual such events had we had good statistics (just as panicked, emotional stores of barbarian attacks on 4th century Roman settlers probably similarly exceeded actual cases).

More recently, the global warming debate has been home to many good examples of this effect.  Rising global temperatures are fairly easy to show on a chart, and while the compilation of these statistics is fraught with problems, it is generally unassailable that the data trends up.  Where things really go downhill is in the supposed knock-on effects of rising global temperatures (eg hurricanes, tornadoes, droughts, floods, etc).

The media coverage of these issues is absolutely dominated with feelz over facts -- a good example being hurricanes.  Media coverage of every hurricane is full of panicked articles that this particular hurricane is a demonstration of climate change.  Beyond being a great example of how the media often tries to claim a trend from a single data point, the amazing part is that long data sets of hurricane frequency and, even better, total cyclonic energy in such storms, are readily available...  and NEVER published.  This data consistently shows no upward long-term trend in hurricane activity or strength, but such data is deprecated in comparison to fear of the individual hurricanes themselves.

We have seen this exact same kind of thing, with fear and anecdote trumping actual data, from the very beginning of COVID.  For example:

• One single panicked tweet or interview of some random hospital nurse** will create a stampede of stories that hospitals are all full and that if you get sick you will likely get turned away and die.  What these stories never include is either a) real data on hospital bed occupancy in the area being reported on or b) any background how hospitals can and routinely do flex ICU bed capacity or c) any background on how this happens even in many flu seasons and is not a unique COVID marker (eg here, here, here, here).
• Some person will claim so weird long-COVID reaction without any statistics or background on how a) many respiratory diseases have odd longer-lasting effects or b) at what rates these occur or c) how most of these are eventually debunked a few months later (remember the whole young athlete heart thing?).
• A story will feature a person dying at 30 to try to scare people that this is not just killing old people without a) any context of pre-existing conditions in that person or b) without any data on the microscopic overall fatality rate for this age group and how unusual this case actually is.

My wife tends to be susceptible to this panic stuff because a) she actually still trusts the media and b) she tends to be one of those people who will always jump to the worst case scenario.   It is just incredibly frustrating to watch the media push her buttons and make her fearful when no rational basis exists to be scared.  And the hard part is that for rational people to bat this stuff down, it is like playing whack-a-mole.  At some point it just becomes tedious and exhausting to keep responding every day to a new batch of fact-free BS (irritatingly wrapped into a self-righteous mantle of "following the science.")

I remember a Teaching Company lecture course on German propaganda in the 1930's.  The professor Thomas Childers (I would recommend any of his courses) compared the messaging to a wheel.  They would try a message, and for those that this message did not work for they would turn the wheel a bit and get a new message.  And they would do this constantly until no opponent could reasonably knock them all down.

** Postscript.  This sort of gets back to the first post in this series on incentives, but one might wonder why some front-line healthcare worker would go to the media with dramatic stories that are untrue.  Various political sites that are skeptical of the stores have assumed these folks are political in some way with a political mission, but that does not have to be true.  Let me tell a story.

Back in the early 1990's I was on a jury in Dallas.  This was at the tail end of the incredible child molestation and day care panic, where Janet Reno and others using her "Miami Method" put scores of people in jail based on absurd, literally unbelievable stories generated by young children at the urging of prosecutors.    Our jury's case was a dad accused by the babysitter of molestation of his daughter.

The facts were absurd.  The molestation event supposedly occurred in a quasi-public place;  there was no physical or other evidence;  the "victim" recanted earlier stories told to aggressive prosecutors and testified for her dad;  no one actually witnessed anything.  We returned a not guilty verdict in barely an hour.

We can guess the prosecutors were motivated both by sincere belief that they were doing God's work as well as desire to emulate other prosecutors who had jump-started their career by recently making headline-grabbing molestation prosecutions (Janet Reno actually having jumped all the way to US AG, as an example).  But why the heck did the baby-sitter start all this?  It turns out that this was actually pretty clear from cross-examination by a very good defense lawyer.  She had seen another baby-sitter get on the Oprah TV show for accusing a father of molestation, and she wanted the same chance to meet Oprah and get her 15 minutes of fame.  Seriously, the whole family's life was shattered for years because she wanted to be on Oprah.  Never over-estimate anyone's motives, I guess.

When I argue with folks about the irrationality of certain COVID NPI mandates, eg masks and lockdowns, their ultimate argument when their backs are up against the wall is this:  the government and/or the "experts" would not have mandated these interventions if they did not make sense.  The purpose of this and several following posts is to explain exactly why  they might, or more particularly, why certain government mandates might make sense for government officials even when they make sense for no one else.

Briefly, the case against masks

There are people I talk to that assume that the entire history of science consists of a march towards more and more certainly that public masking is essential to stopping respiratory disease spread and that the only people who oppose this NPI are doing so because Donald Trump or the Baptist Church told us to oppose them.  But there are actually really good reasons to be skeptical of masks as a mandated NPI for this respiratory disease:

• The body of public health research prior to 2020, on balance, held that public masking (and large scale lockdowns, btw) were not effective and generally not recommended (at least once the outbreak is past a very small group).  A good roundup of the studies is here.
• People usually respond to this by saying, well, you wouldn't want your surgeon to operate on you without a mask.  Of course, this use case comparison is absurd, since standing next to someone in line at Walmart for 60 seconds is not really anything like hovering over someone's open incision for 3 hours.   But it turns out that the scientific support for masks even in surgery to reduce post-op infection is surprisingly equivocal.
• The weave of your mask looks to a COVID virus approximately what a chain link fence looks like to a mosquito.  It is not stopping the virus itself.  And this is even before discussing the total lack of sealing against the face I see on pretty much every mask.  And the fact that many people are reusing the same mask for days.
• The argument is thus made that the mask is stopping saliva droplets.  But we have known pretty much since last March that droplets don't spread the disease.  Droplets end up on the floor, not floating around for hours.  The disease is spread best by aerosols, and masks are only marginally effective at blocking these aerosols
• Everything I have said above is EXACTLY what the CDC has said for years.  Here is their info-graphic, still up on their web site.  (Here is a copy I have archived in case they ever take it down: understanddifferenceinfographic-508 )
• A case can be made that masks can make spread worse.  Imagine being on a plane for 4 hours and you have COVID.  Before you ever even get on the plane, you mask is saturated with COVID virus and moisture.  You then spend the entire flight blowing COVID-laden aerosols out through the mask like bubbles from a bubble wand.

Incentives of Government Agencies

But within weeks of the start of the pandemic in 2020, government agencies like the CDC threw out all this history and decided to mandate masks.  Masks were mandated for people outdoors, even when we knew from the start that transmission risks outdoors were nil.   Officials are still mandating masks for children, who have lower death rates from COVID than the flu and despite a lot of clear research about the importance of facial expressions in childhood development and socialization.  Officials are even starting to mandate masks for the vaccinated who, if they are not effectively immune from the disease, are nearly perfectly immune to hospitalization and death from the disease.  So why?

One needs to remember that the officials of government agencies like the CDC are not active scientists, they are government bureaucrats.  They may have had a degree in science at one time and still receive some scientific journals, but so do I.  Dr. Fauci has seen about the same number of patients over the last 40 years as Dr. Biden.  These are government officials that think like government officials and have the incentives of government officials.

I will take the CDC as an example but the following could apply to any related agency.  Remember that the CDC has been around for decades, consuming billions of dollars of years of tax money.  And as far as the average American is concerned, the CDC has never done much (at least visibly) as we never have had any sort of public health emergency when the CDC had to roll into action.

If you think this unfair, consider that the CDC itself has recognized this problem.  For years they have been trying to expand their mandate to things like gun control and racism, trying to argue that these constitute public health emergencies and thus require their active participation.  The CDC has for years been actively looking for a publicly-visible role (as opposed to research coordination and planning and preparation and such) that would increase their recognition, prestige, and budget.

So that is the backdrop.  And boom - finally! - there is a public health emergency where they can roll into action.  They see this new and potentially scary respiratory virus, they check their plans on the shelf, and those plans basically say -- there is nothing much to be done, at least in the near term.  Ugh!  How are we going to justify our existence?  Tellingly, by the way, these agencies and folks like Fauci did follow a lot of the prior science in the opening weeks -- for example they discouraged mask wearing.  Later Fauci justified his flip flop by claiming he meant the statement as a way to protect mask supply for health care workers, but I actually think that was a lie.  His initial statements on masks were correct, but government agencies decided they did not like the signal of impotence this was sending.

There was actually plenty these agencies should have been doing, but none of those things looked like immediate things to make the public feel safer.  Agencies should have been:

1. Trying to catalog COVID behavior and characteristics
2. Developing tests
3. Identifying and testing treatment protocols
4. Slashing regulations vis a vis tests and other treatments so they could be approved faster
5. Developing a vaccine

If we score these things, #1 was sort of done though with a lot of exaggerated messaging (ie they communicated a lot of stuff that was mostly BS, like long covid or heart risk to young athletes).  #2 the CDC and FDA totally screwed up.  #3 barely happened, with promising treatments politicized and ignored.  #4 totally did not happen, no one even tried.  #5 went fabulously, but was an executive project met with mostly skepticism from agencies like the CDC.

Instead, the CDC and other agencies decided they had to do something that seemed like it was immediately affecting safety, so it reversed both years of research and several weeks of their own messaging and came down hard for masks and lockdowns.   And, given the nature of government incentives, they had to stick with it right up to today, because an admission today that these NPI aren't needed risks having all their activity in 2020 questioned.

Incentives for Government Officials

Pretty much all of the above also applies to the incentives of government officials.  Our elected officials of both parties, but particularly the Democrats, have been working to have the average American think of them as super-dad.  Got a problem?  Don't spend too much time trying to solve it yourself because its the government's job to do so.  Against this background, the option to do nothing, at least nothing with immediate and dramatic apparent potency, did not exist.  We have to do "something."

It might have been possible for some officials to resist this temptation of action for action's sake, except for a second incentive.  Once one prominent official requires masks and lockdowns, the media began creating pressure on all other government officials.  New York has locked down, why haven't you?  Does New York care more than you?  We had a cascade, where each official who adopted these NPI added to the pressure on all the others to do so.  Further, as this NPI became the standard government intervention, the media began to blame deaths in states with fewer interventions on that state's leaders.  Florida had far fewer COVID deaths, particularly given their age demographics, than New York but for the media the NY leaders were angels and the Florida ones were butchers.  For a brief time terrible rushed "studies" were created to prove that these interventions were working, generally by the dishonest tactic of cherry-picking a state with NPI mandates that was not in its seasonal disease peak and comparing it to another state without NPI mandates that was in the heart of its seasonal peak.  (We are, by the way, starting to see a similar cascade around the most recent delta-driven mandates -- just today a random Arizona county with no uptick in COVID hospitalizations just required indoor masking for the vaccinated).

And then the whole thing got polarized around party affiliation and any last vestige of scientific thinking got thrown to the curb.   Take Chloroquine as a possible treatment protocol.  Personally, I have not seen much evidence in its favor but early last year we did not know yet one way or another and there were some reasons to think it might be promising.  And then Donald Trump mentioned it.  After that we had the spectacle of the Michigan Governor banning this treatment absolutely without evidence solely because Trump had touted it on pretty limited evidence.  What a freaking mess.  In addition to giving us all a really beautiful view of the hypocrisy of politicians, it also added another great lie to the standard list.  To "The check is in the mail" and "I will respect you in the morning" is now added "We are following the science."

Incentives for the Public

I won't dwell on this too long, but one thing COVID has made clear to me is that a LOT of people are looking for the world to provide them with drama and meaning.  The degree to which many folks (mostly all well-off white professionals and their families) seem to have enthusiastically embraced COVID restrictions and been reluctant to give them up has just been an amazing eye-opener for me.

Incentives for Businesses

Many businesses have been caught up in the politicized virtue-signaling, making a big deal of their support for or opposition to various NPI.  But even without this political element, businesses were always going to be conservative and mandate a lot of this stuff if for no reason than to avoid liability.  If politicians are worried about blame from the media for deaths if they did not mandate every intervention their neighbors required, just think what a corporation worries about.  Any tort lawyer worth their salt can get a jury to blame a customer or employee death, without evidence, on a company that somehow did not follow the CDC advice of the microsecond.

Next Episode

In our next episode, I will discuss the role of poor selection of metrics for crazy government interventions.  Spoiler alert -- focusing on cases via positive readings on an overly sensitive test has led to a LOT of the most recent wave of stupidity.