The data in the article tell us that most of those 446 deaths in which C19 played a part would have happened in the next few years anyway.
So we would expect fewer people to die in Bergamo next year, because they died this year instead. And then fewer than normal expected the year after, and so on, although it gets increasingly noisy with time.
We’re measuring the impact of COVID in deaths, by and large. A more useful unit for some purposes is quality-adjusted-life-years (QALYs).
For people who die, the QALY impact of C19 would have been how many years of full health the person had left, if they had not died after catching the virus.
But similarly, for people who don’t die shortly after contracting it, C19 can still have a QALY impact, and we’re not reporting or even measuring that much. Patients often have reduced lunch function even after “recovering”; there will be patients in whom C19 triggers post viral fatigue, which can last years; in the worst cases patients will be stuck with ME/CFS or similar for the rest of their lives.
Very little about the philosophy, economics, politics or science of dealing with C19 is simple. Although clearly some things are: if I don’t go near people with the virus, I won’t catch it; if we flatten the curve, fewer patients will die; the old and the infirm are more at risk. But those few simple parts don’t necessarily make the whole simple.
So overall deaths per capita will probably still be much higher than before for the next 5 to 10 years. Maybe longer.
If the virus causes one year's worth of extra deaths, these will not be spread out over the whole year, so seeing 350 of them in a month of the epidemic would also not seem out of place, it corresponds to an epidemic whose peak is a few months long. So this data doesn't seem inconsistent with the linked article's estimates.
Of course if you are running a morgue, then 448 instead of 98 is the relevant figure, and is likely to be very difficult to handle. And if you are running a hospital, even worse.
So it doesn't disprove the hypothesis that the average person who gets it has a 1 % chance of dying.