If you have a specific reason to believe that the model resulted in an incorrect conclusion, feel free to share it, instead of casting aspersions with cryptic nothings.
Also Neil's other predictions have been completely wrong on the Swine Flu and Bird flu. Why this "expert in his field" is still listened to is a mystery to me.
If you're talking about that first graph on the page, I think that it is not very helpful. Comparing total number of deaths can be misleading, especially for small countries like Sweden. If my state had a Coronavirus death rate as high as Sweden's 15,000 more people would be dead. Still not "millions", but it wouldn't be an ideal outcome.
Sweden is pitched as as some kind of example of handling the pandemic correctly, when their numbers[1] don't look good at all. From their numbers[2] 44% of people diagnosed ends up dead, implying they are way under tested or they have ridiculously deadly strain (I think it is the former). Because of that the most reliable indicator from them is number of deaths.
Now compare number of deaths with countries that reacted quickly, for example: South Korea, Taiwan, Australia, New Zealand, Norway and others.
It looked very wonky. I cannot judge if the code does not actually produce something worthwhile, but it certainly doesn't pass any smell tests. In no profession would work looking as sloppy as that be trusted. And for the critical decision it was used for I would expect something more robust.
Also Neil's other predictions have been completely wrong on the Swine Flu and Bird flu. Why this "expert in his field" is still listened to is a mystery to me.