An infection rate that is much higher than we knew is not all good news.

While I agree that all the various data points need to be added to considered to add to the total body of knowledge, we also need to be cautious of the small sample studies and how error rates/false pos/neg results can magnify errors when extrapolating out to populations. Confirmation bias has run rampant in analyses as right wing groups have attached to anything that comes close to confirming that mortality rates for Covid-19 might look similar to seasonal flu. Here are a few things that I think are important to mention.

1. The many articles expressing the ‘good news’ that the infection more widespread than we thought, and therefore the death RATE is lower seem to be forgetting what this does to our estimation of the r0. This would suggest that our understanding of how infectious the spread is grossly underestimated. The total mortality rate of the population is a function of the death rate of infections AND the spread (r0) — so a lower death rate per infection does not necessarily add up to fewer deaths if spread can carry to more of the total population.
2. We have not yet confirmed whether the antibodies give us immunity, or if we can be reinfected. This is a very big and problematic unknown.
3. Despite so many studies trying to work their way down to a flu-like death rate (0.1%), the biggest laboratory we’ve got is producing real life numbers that are hard to refute, because regardless of the ‘official’ infectious characteristics of the virus — it has actually killed 23,000 people in New York City which has a population of 8.77 million people. So far, that is 0.27% of the total pop — so even if we took the absurd assumption that 100% of New Yorkers were infected it would already be 2x more deadly than seasonal flu. If the recent antibody test was right that indicated a 20ish% infection rate, in NYC that would put the infection fatality rate at over 1% and counting — which is 10x the flu. If we compound that with an r0 much worse than we previously understood and 80% of the population still uninfected, then we still end up with a terrible death toll in aggregate even if the rate per infection is lower.
4. For a deep critique of Santa Clara study, this is worth a read https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/