My understanding is that most evidence points to order of magnitude more lethal even when the hospitals aren't overflown.
Regarding "testing negative then positive" the experts already expected that there were no real reinfections.
If those mortality estimates were based on the number of positive test cases, then they're very likely overblown. Recent seralogical studies indicate that the number of positive test results are likely a small fraction of the total number of cases, and likely the most severe subset at that. None of this is to say that it's less lethal than influenza, only that the situation is developing rapidly and any given mortality estimate may well be outdated.
But it seems plausible if the CFR is <0.1% as there are both asymptomatic cases of the flu and people don't always go to the doctor even if they have symptoms. It seems like caring about IFR was rare before this pandemic and the lockdown
They don't mention IFR anywhere as far as I can see
No: the antibody tests were done with the expectation that the total number of the infected would be much higher. The tests have such false positive rates that with the results actually observed the tests in most of the cases say nothing -- in most of the locations the numbers would be similar even if nobody would be a real positive. And there where the results are above these "noise" thresholds we also have a big numbers of deaths which do confirm my claim of order of magnitude deadlier than flu.
Even observing the pure death statistics we can see that, even in spite of all the measures actively taken throughout the world. Without them it's obvious it would have been again the difference of some orders of magnitude:
https://www.euromomo.eu/graphs-and-maps/
See also here:
https://www.ft.com/coronavirus-latest
the "Death rates have climbed far above historical averages" graph.
Saying that it would've been a magnitude higher without any of the measures is pure speculation.
Covid19 figures in the UK are 26,000 [hospital] deaths for 165,000 confirmed infections. Even if we assume the entire population is infected ... that makes it a minimum of 10x as deadly as flu. We're at a slowly falling ~5000 deaths per day; when care-home and other Covid deaths get added ...
I think perhaps you're down-playing it a little too much.
Early studies treated the Case Fatality Rate as the Infection Fatality Rate, by virtue of the fact that the only people getting tested were people with symptoms. Random testing in Germany has indicated that ~20% of the population was infected or has been infected, and the corresponding death rate yielded an IFR of 0.37%.
Measuring IFR is inherently speculative, unless 100% of the population is administered a test with no risk of false negative or positives. In order to compare the IFR of COVID-19 to the seasonal flu, we'd need to use the same estimation techniques. I've only found a few experts that have done comparisons of IFR rates of the flu and of COVID-19. The most reputable source on this reported an estimated IFR for the flu of 0.04%, but also an estimated IFR for COVID-19 of 0.2-0.3% [2]. This is "many times deadlier" if by "many" you mean 5 to 8 times deadlier. This is nowhere near the multiple orders of magnitude deadlier that was reported initially (IFR rates of 2-3% and above).
1. https://www.cdc.gov/flu/about/burden/index.html
2. https://www.bloomberg.com/opinion/articles/2020-04-24/is-cor...
Initially you were implying that the IFR of the flu was 0.1% and comparing it to an IFR of 0.4%, this is what I disagreed with strongly
The bloomberg link you're giving is showing that the vast amount of randomly sampled serological studies are showing IFR of 0.5%-1%. And importantly, looking at how the random sampling has been done for each case and ranking by quality, >0.5% results rank at the top (he studies with the biggest sampling problems show the lowest IFR)
0.2-0.3% is by far in the bottom range of estimates
I think the data shows a pretty clear single order of magnitude difference between the IFR of the flu and novel corona. But I agree that >1% IFR is extremely unlikely
Plenty of the >0.5% results have serious sampling problems of themselves. The Dutch study sampled people who were donating blood. The subset of the population that donates blood is could easily have different behavior than the general population: like being more health-conscious and thus less likely to be infected, which would inflate the infected fatality rate.
And when we compare against the flu, we also have to consider that there are different methods of estimating the infected fatality rate. More conservative estimates on infections of the seasonal flu yield higher IFR values. The epidemiologist being cited here is providing relative estimates of 0.04% and 0.2-0.3%. We could go with more conservative estimates on the infected rate for COVID-19, but we'd have to be similarly conservative when measuring the IFR of the flu.
I'm not sure the blood sampling would skew the direction you think it does, healthy individual could just as well mean that they're more likely to have had it since they're less likely to sit at home and stick to a quarantine. But you are right, it definitely counts as a sampling issue and I'll concede that ranking by quality is a lot less clear cut, I should not have been so confident
Actually, the "risk" of false positives or false negatives is dependent on prevalence, 100% is not always required. If you have a test where 5 of 100 cases are false (i.e. 95% times is not wrong), and nobody of these tested is actually infected, you could incorrectly believe that 5% of population is infected even when nobody is, meaning such a conclusion would be completely false.
But if the population is actually already e.g. 50% infected, the same test can "lie" only 5%, giving you 47% or 53% but still being "mostly true" (from the engineering point of view).
So it is important to ignore the test reports as long as they are close to their false positive rate, which they were in a lot of antibody tests done up to now.
Also "false positives" and "false negatives" can lead to wrong handling of the cases, but that's another topic.