The problem is not the system of government. The problem is the weakness of many of the key characters in the system.

A pretty good update which mirrors many of the issues I have been concerned about regarding Covid-19.  Principally that we have misplaced confidence in the scientific process at the beginning of a novel infection.  There is nothing wrong with the scientific process, but it needs reliable data and enough time and cases to be able to identify patterns and causal mechanisms.  

At the beginning of Covid-19 we have had to make assumptions about the degree to which Covid-19 might mimic which attributes of earlier pandemics.  But there are so many assumptions about so many variables with such variance in variable weighting that forecasts were themselves dramatically variant.

Again the the problem is not in the scientific process or even in the models.  The problem is that we have accorded end-state insight at the very beginning.  In other words, the scientific process will eventually get us there and we will have some confidence in our knowledge and forecasting.  But that confidence comes at the end-stage of the process, not at the beginning when all is novel, unclear, and uncertain. 

We study something long enough and eventually we begin to understand in days, weeks, months, years, or decades.  In practice we need to be especially humble at the beginning because we only have hypotheses which are at best being tested in shallow, expedited, and unrigorous ways.  

Just because the actions look like science does not mean we are yet reaching robust or reliable conclusions or accurate forecasts.  The scientific method is always at risk of being highjacked by special interests or mono-focused enthusiasts or grifters.

And that is what has happened so far.  We have had far more confidence on display by various institutional players or interests than the science can actually support.  We still do not have a good comprehension of exactly what is happening and our input data is widely acknowledged to be deeply flawed.  We are still at the very beginning of the scientific journey even though the political and advocacy process is treating it as end-stage.

This article touches on that epistemic precariousness.  From Covid Spread Can’t Only Be Explained by Who’s Being ‘Bad’ by Faye Flam.  Flam puts the issue in terms of moralizing where I would focus on misplaced epistemic arrogance, but in several ways the two approaches overlap.  

There are some weird things going on in the coronavirus data. It’s curious that cases dropped so fast, and have stayed pretty low, in the spring hot zones — New York, New Jersey and Connecticut. And why did cases remain so low in Idaho and Hawaii until recently?

The mainstream narrative is that it’s all about good behavior when cases go down — mask wearing and giving up our social lives for the greater good. And conversely, bad behavior must be what makes them go up. We talk about certain regions having the virus “under control,” as if falling cases are purely a matter of will-power. A sort of moral reasoning is filling in for evidence.

But why, then, have cases plummeted in Sweden, where mask wearing is a rarity?

This is the time to use scientific methods to understand what’s happening. The pandemic has gone on long enough to reveal patterns in the way it spreads. If it’s all about behavior, that’s a testable hypothesis. If, as a few speculate, dramatic drops in some places have something to do with growing immunity in the population, we can also turn that into a testable hypothesis.

“The issue with data is one can manipulate it to show anything you want if you have an agenda,” says YouYang Gu, an independent data scientist. Cherry picking is easy — prediction is much harder, and Gu is getting some attention for the fact that models he’s been creating since April actually forecast what’s happened with the spread of the disease in the U.S.

He recently took to Twitter to urge public health officials to apply scientific thinking. He pointed to data on Louisiana, where cases were rising earlier in the summer and seemed to level off after various counties issued mask mandates.

But breaking the data down by county, he says, revealed a different story. Mask mandates varied in their timing, but places that implemented them late saw no more cases or deaths than those that did so early. “I don’t think there’s currently enough evidence to support the fact that recent policy interventions (mask mandates, bar closures) were the main drivers behind the recent decrease in cases,” he wrote.

That’s not to say that individual behavior doesn’t matter a lot — and the cancellation of big gatherings and other potential super-spreading events is more important than ever — but there may be more factors than we know driving the bigger picture.

A few scientists are examining the possibility that previously hard-hit areas are now being affected by a buildup of immunity, even if it flies in the face of the widespread understanding that the disease has to run through at least 60% of the population to achieve so-called herd immunity. (So far, antibody tests show only some 10-20% of the U.S. population has had the disease.)

The term herd immunity is a little vague in this context. It was created to characterize the impact of immunization. It refers to the percentage of the population that must get immunized in order for a pathogen to die out — a quantity that depends on the nature of the virus, the efficacy of the vaccine and the behavior of the hosts. If natural immunity is starting to help in some places, that would suggest herd immunity is a reasonable and worthy goal of an immunization program.

But scientists have little experience applying herd immunity to a natural infection, and what understanding they have is changing. Scientists have started to investigate the possibility that there’s another critical factor here — heterogeneity in the way humans interact, and in our inherent, biological susceptibility to this disease.

Read the whole thing.

At this point, our institutional leaders, through arrogance and over-confidence at the beginning, have pretty much squandered the trust reposed in them by their positions.  You cannot be so obviously wrong for so long and with such great consequence without being rejected.  People are not per se rejecting the scientific process or reverting to populism or primitive belief.

They are simply and accurately observing that the emperors in power, whether political power of epistemic power, have no clothes.  That the naked emperors have been enriching themselves in money or status while exempting themselves from consequences.  Consequences for failure which most citizens could not avoid.  

Until we have leaders willing to lead, we cannot make good progress.  Leaders willing to tell the truth when the truth is unpalatable (we still don'd know what is going on).   Leaders who counsel patience over the Kabuki theater of being seen to "do something."  Leaders who have the courage of their convictions and the courage to accept the consequences of those convictions.  Till then, we will not have much recovery from the damage done to our body politic.