All models are wrong, but some are completely wrong

I kind of disagree with this point. The models we see are mostly statistical models. Anybody with a statistics background (mathematician, physicist, chemist, biologist, engineer, computer scientist, epidemiologist) can have enough of an understanding to make valid points.

Discarding opinions based on somebody's background is an argumentative fallacy in and of itself. You should of course check if somebody is trustworthy, but epidemiologists should be scrutinized under this aspect like everybody else.

What actually happens is this:

1. Journalists have a story they want to write. They probably already decided what the message is going to be, but let's be generous and assume they didn't.

2. They consult a rolodex of, almost exclusively, government funded academics. This is true even if the story they're writing is about activity or science that takes place only in the private sector and for which the academics in question have no actual experience. They may consult two or three grant funded academics if they want their story to seem especially robust. If they give the private sector a chance to reply at all (often not) they will cite one or two sentences of a brief phone call in which the person being talked to doesn't know what they're trying to defend themselves against and is probably just confused. It's not a real interview with an actual in-house expert.

3. This story is then published as "Experts say, ..." even if what the chosen experts say flatly contradicts common sense or things that can be checked with 10 minutes and a search engine.

4. Readers comment below the line, pointing out the flaws in the story. If a specific company is involved, they may do a blog post explaining their side of the story which the journalists will either completely ignore, or if they think they can get away with it, selectively quote one or two sentences in a misleading way.

Industrial scientists/engineers are sometimes assumed to be inherently evil and untrustworthy. But the whole idea that journalists are untrusted because they very rarely quote people in industry is a saw of the left; it's not true, which is why the examples given always seem so curiously weird and out of date. Tobacco industry? when was the last time you even read a newspaper article about them? Oil corporations? Those firms that have spent the last 15 years rebranding themselves as energy companies because they now make solar panels too?

There's a lot of really good analysis of the trouble journalism has got itself in for, and a significant part of the blame is laid at the feet of journalists uncritically reporting anything academics say as the Whole Truth and Nothing But The Truth, when in fact they routinely contradict each other, make up statistics, report obvious common sense as "findings", are hugely over-confident in their own predictive abilities, mis-use statistics and so on.

A good book to read on the topic is "Wrong" by David Freedman:

https://www.goodreads.com/book/show/8134625-wrong

He's a former journalist and so has direct experience of this problem. He cites many examples where expert testimony caused misleading or wrong stories to be published, but IIRC none of them involved corporate scientists. Mostly academics like nutritionists, psychologists and so on.

Which model? Your article mostly dwells on the Oxford model in the FT which is as mainstream as it gets. The Daily Mail article is about a prediction by an Imperial academic.

There doesn't appear to be any "mainstream" in epidemiology. This kind of false-consensus argument is one I've seen before and frankly it undermines people's respect in both academic and journalism. How exactly is the "mainstream" established, in your mind? And don't talk about vague, easily manipulated non-metrics like reputation. Mainstream models should come from a single thing: success. Your insistence on rigid academic segmentation is the very thing that makes academia brittle and riven with non-replicable papers.

You know which kind of modellers I respect the most? Actuaries. They have skin in the game. They don't try to predict pandemics or sell insurance products against them, implying they think pandemics can't be modelled. So far based on what I've read about the history of epidemiology, I can't disagree with them.

Which is fine. It'd be far better if people weren't trying to model COVID-19 at all. It's clearly far beyond our societies capabilities today. We can't even get useful data let alone feed it into a simulation of society.