I really want to share his optimism too, and he does make some good points about the social/psychological reactions many people are having, but even with my basic foundation in epidemiology, there is so much wrong with his information and and data selection that it reads more like hope than analysis. A lot of his snapshots were accurate information weeks ago, but have been greatly superseded, he compares incomparable data, and he generally operates under the presumption that a lack of data on risk implies lower risk, which is fundamentally the opposite of what most epidemiological risk assessment guidelines indicate, especially when additional data establishes a pattern of higher risk or at least doesn't reinforce a lack of risk. This is especially highlighted in his views on infection rates among children, where he uses information from February 5 (!) to suggest that children not only suffer less clinical illness, but also have significantly lower infection rates (and are thus less a source of infection and spread). While he acknowledges some risk, his data is way behind what we know now.
A good example of a bad example is his treatment of the bell curve on Italian cases. He cites this:
Attachment 50358
To use some meme lingo, "This comment has not aged well", because moving ahead to today, we have:
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His data sets are constructed according to different criteria, the time scales are different, and (crucially) the data on his bell curve example is about 2 weeks old. Subsequent events did not bear out the bell curve status at all, even allowing for indirect comparables.
I think the author was sincere, and from a behavioural standpoint he makes some good points about how people need to consider all angles and not panic, but his epidemiological presentation and conclusions are founded on some highly erroneous methods and information.