I’m going to lay my cards on the table here:
At this point I no longer think there’s a good argument that this hasn’t been a massive, very harmful overreaction. I think anybody who still thinks that is being fooled by the media or else isn’t paying attention.
If you look at the data WITHOUT the underlying assumption that the media has been reporting things honestly – and you should never assume that – it’s glaringly obvious that nothing we’ve done makes sense. Worldwide, the numbers don’t make sense. In the country, the numbers don’t make sense. Not even close.
There was a point where a shutdown for a couple of weeks to a month in order to monitor things was a good idea; we did that, and it was clear things weren’t particularly bad. So naturally the shutdown was extended and the media breathlessly reports every incoming statistic 24/7.
I bring this up because I see that Dr. Feser supports the lockdown. Dr. Feser is charitable, his writing is clear and logical, and he’s respectful of his opposition. He is also totally and completely wrong, not even close to correct. His linking to really, really bad articles is especially bizarre.
The issue with “revising their opinions” is that the decisions they are making are based on models they are using. The problem is that the models they are using have been totally off. Not only are they totally off, at no point at any of this have they been even close to right.
Consider: If “revising their opinions”, repeatedly, because they have been repeatedly wrong, is no reason to not trust the epidemiologists, is there literally any reason at all to NOT trust the epidemiologists? “Never once being close to right” is apparently not a reason to mistrust them. Soooooo…auto-trust in experts I guess?
This is precisely the same logic used to justify global warming. Sure, the climate scientists’ predictions have been wrong, in fact, not even close to right, but that’s no reason not to trust them!
This is the absurdly bad article I was referring to by the way.
I will give Dr. Feser some credit. At least he acknowledges the actual point here, as most people seem to miss it.
This is threefold:
- The best case scenario – best case, if with perfect compliance and a total lockdown, which we didn’t get – was said to be 100,000 dead, by Fauci. And it was this model that gave us this number that was used to justify locking down the country.
- Every model that has been used to justify extreme measures, every single one, has overshot. And overshot badly. Because we never needed extreme measures to prevent a second Spanish flu. We were never getting that. We were never close.
- People are ignoring the historical perspective. I know I keep bringing up the 1967 flu, but: The 1967 flu. Corona isn’t a particularly interesting cold bug. It hit nursing homes and hospitals unusually hard. In a couple of hotspots around the country you should probably wear gloves and use takeout. Wash your damn hands.Now even the skeptics are grudgingly admitting we’re going to end up around 60,000 dead. To reach the percentages of the 1967 flu – I believe the extent was school was closed for a month or two – we’d need around 300,000 dead.
Nobody remembers that pandemic. Why? Because it wasn’t that big a deal. Wanna bet that people who lived back then would have wanted to react like we are now? I’ll put my money on “No, because that’s insane”.
Given all of this I don’t see any way anybody giving an honest appraisal of the situation can see all of this as anything but a massive and incredibly harmful interaction.
Maybe if we open lockdowns “early” the death count will hit 100,000. So what? Who cares? That’s unfortunately high, but it happens. It isn’t end of the world high. And this economic collapse is in all likelihood going to affect millions, and for years.
And the article gives us gems like this:
If we are going to have 60,000 deaths with people not leaving their homes for more than a month, the number of deaths obviously would have been higher—much higher—if everyone had gone about business as usual. We didn’t lock down the country to try to prevent 60,000 deaths; we locked down the country to limit deaths to 60,000 (or whatever the ultimate toll is) from what would have been a number multiples larger.
Multiples? How many multiples? How do you know that? What models are you using to get that number?
Because the models we’ve been using haven’t been right yet. That’s the whole point! We were never on the path to be “multiples” higher than 60,000. And some basic thinking would prove it: You would need to believe the U.S. alone would quadruple the world death count in a month just to reach 100,000 deaths. Does that sound remotely plausible? Of course not! How much more absurd is millions?
But the experts said so. And the climate scientists said that if we didn’t have that recycling program the pyramids would be underwater.
So chalk this up as maybe the first time I’ve ever disagreed with the good doctor about anything. But I appreciate his respect for the other side of the argument.
Malcolm the Cynic 
Compare to the 2016 elections. Almost all of the experts were completely, laughably, wrong. Almost none of them changed careers because of this.
And we see the same sort of excuses which don’t agree with the actual models. For example, the 538 models have been defended on the basis that there were big swings in public opinion shortly before the election, and as such the earlier predictions would have been accurate if the election had been held earlier. But 538 kept separate predictions for what would happen on November 8 versus what would happen “if the election was held today.” So the models were supposed to incorporate the possibility for opinion shifts and the like.
Like Brian Niemeier before him, I am bsffled somebody as intelligent and sane as Dr. Feser cannot see the issue with “Even though at no point have they been even in the ballpark of right, we need to trust the epidemiologists anyway”.
The only conclusion to draw from that is that there is literally nothing the epidemiologists could do short of proven conspiracy that should lead us to distrust them. An obviously ludicrous conclusion.
The thing is, there is a way to handle having a lack of information at the start: you simply run the model over all plausible scenarios. For example, if the disease’s contagiousness is so unknown that you aren’t sure if each infected person will infect 1 other person, or 50 other people, run models for each possibility. Then your projection will end up being something like: “In two months we think that there will be somewhere between one thousand and 300 million people infected”, but if the properties of the virus are really that unknown it would be dishonest to say anything more precise. And the prediction would still be useful information because it would stress that the virus is too new to be sure what will come of it.
But if anyone were to publish a prediction like that they would be laughed out of town and never trusted again. Instead people want extremely precise numbers. But they don’t really care if they numbers are accurate.
There is one of Bishop Sheen’s talks where he mentions a soap that is said to kill 99.9% of germs. He points out that you trust the brand because of that .9%. You don’t know how they calculated that number, and you probably don’t know the exact mechanics behind how the soap works, but that extra .9% percent makes you think that the calculation must be trustworthy.