First, I’d like to provide a brief history of my correspondence with my good friend, pastor Doug Wilson. By which I mean, I used the contact form on his website to send him one email, and he actually read it and posted it on his site. Here it is, in full:
Way back long ago, at the beginning of corona-mania, a guy named Aaron Ginn posted a statistical analysis of available COVID data, and said, basically, that we had no reason to freak out about it.
Of course, immediately after that, everybody freaked out, his post was pulled down by Medium, and he was attacked by “experts,” including a guy named Carl Bergstrom, who posted a detailed takedown of Ginn’s analysis on Twitter.
You’ll probably remember all this because I think you posted a reference to ZeroHedge’s reposting of the whole donnybrook here.
Anyhoo, I bring this up because I was thinking, now that we have the experience of hindsight, wouldn’t it be interesting to review who was more right, the amateur or the “expert”? (Sorry, but I’ve gotten to where I can’t write the word “expert” any more without the sarcasm quotes.)
I don’t want this story to be forgotten, because I want everybody to remember that there were voices from the beginning saying “don’t freak out,” and those voices were silenced and ridiculed. And they were right.
Thanks.
Jason
And here is his reply, also in full:
Jason, yes, that would be worth resurrecting.
So hey, me and my buddy Doug are right there on the same page! Since Pastor Wilson and I are so interested, let’s take a look at that story from way back at the dawn of lockdown-mania.
In March of 2020, former Mitt Romney campaign staffer Aaron Ginn posted an article on Medium titled “Evidence Over Hysteria” (and could we use more articles like that?). Ginn admitted he wasn’t a virology expert,
Our focus here isn’t treatments but numbers. You don’t need a special degree to understand what the data says and doesn’t say. Numbers are universal.
But he said a lot of commonsensical things like:
The total number of cases isn’t illustrative of what we should do now. This is a single vanity data point with no context; it isn’t information or knowledge. To know how to respond, we need more numbers to tell a story and to paint the full picture. As a metaphor, the daily revenue of a business doesn’t tell you a whole lot about profitability, capital structure, or overhead. The same goes for the total number of cases. The data isn’t actionable. We need to look at ratios and percentages to tell us what to do next — conversion rate, growth rate, and severity.
And:
As the US continues to expand testing, the case fatality rate will decline over the next few weeks. There is little doubt that serious and fatal cases of COVID-19 are being properly recorded. What is unclear is the total size of mild cases. WHO originally estimated a case fatality rate of 4% at the beginning of the outbreak but revised estimates downward 2.3% — 3% for all age groups. CDC estimates 0.5% — 3%, however stresses that closer to 1% is more probable. … A paper released on March 19th analyzed a wider data set from China and lowered the fatality rate to 1.4%. This won’t be clear for the US until we see the broader population that is positive but with mild cases. With little doubt, the fatality rate and severity rate will decline as more people are tested and more mild cases are counted.
Almost immediately, Medium pulled the article down, because it was way too sensible and level-headed for the time, and that made a bunch of people really mad, including a biology professor named Carl Bergstrom, who took it upon himself to deliver a lengthy Twitter rebuttal to Ginn’s article.
It’s hard for me to sum up Bergstrom’s rebuttal thread, but suffice it to say that he really, really didn’t like Ginn’s examples or analogies, and he made every effort to point out that he was the expert and Ginn was not. And though Bergstrom may not have been pro-hysteria, it’s pretty clear he was anti-anti-hysteria.
So, here we are eight or so months down the road, and we’ve had some time for these two opposing arguments to play out. And I wonder, who was more right, the anti-hysteria amateur, or the anti-anti-hysteria academic?
My Request
I’ve taken some statistics classes, but I gave up doing math for Lent several years ago and never really went back. If there’s anybody out there who likes reading charts and graphs and likes pondering the validity of statistical models, I’d really like to hear your opinion of how Ginn’s analysis holds up. And I’d like to hear your opinion on the validity of Bergstrom’s counter-points.
Of course, seeing that it’s been literally days since I’ve seen a pile of dead bodies in the street, I have my own opinions about who was more right about the contagiousness and lethality of the virus.