3 ms·

There was also an absurd amount of selection bias in their population. They recruited people for a COVID-19 antibody screening, and there were emails encouragin

There was also an absurd amount of selection bias in their population. They recruited people for a COVID-19 antibody screening, and there were emails encouraging people who suspected they had recovered from the disease to get screened. If the researchers knew about the email, it's actionable research misconduct. If they didn't know (a coauthor's wife sent the email), then it's just very very bad work.

briandear 7y ago
However what about the USC and the NYC studies? Are they wrong too?
- ekidd 7y ago
  The NYC studies actually look halfway decent. The big problem with serological tests is that even good ones may have, say, a 2% false positive rate. So if you test a population where nobody is infected, the test will say that 2% have been infected. To get good numbers, you need a population where lots of people have been infected. That will allow true positives to swamp the false positives, which is what happened in the NYC study that claimed 21% of people had already been infected. Even if it's really only 19%, that doesn't change much. You also need a good random sampling procedure. IIRC, the NYC study tested people shopping for essentials at mid-day. This underrepresents essential workers, people who are really good at self-isolation, and people who are currently sick. But still, it's not too bad. The New York City numbers suggest that very roughly 1% of people infected with the virus will die, depending on how you count probable but unconfirmed COVID deaths reported by NYC. This could be off by a factor of two in either direction, depending on how good the random sampling was, and the characteristics of a given population.
  - MengerSponge 7y ago
    Nicely put. With a case fatality of ~1%, we need orders of magnitude reduction, not factors of 2. If anyone wants to quibble over a factor of 2 you've missed the point. Now my nightly rant: I did this kind of false positive calculation in high school statistics, and I hated it. Still do. I hate that we're dealing with this BS. I hate that stupid people put us in this position, and that smart people aren't smart enough to not be absolute knobs.
- creato 7y ago
  Why are you citing the NYC study as reinforcement of the other two? It is unlikely that all 3 are correct, because they imply significantly different outcomes of an infection.

briandear 7y ago

However what about the USC and the NYC studies? Are they wrong too?

ekidd 7y ago
The NYC studies actually look halfway decent. The big problem with serological tests is that even good ones may have, say, a 2% false positive rate. So if you test a population where nobody is infected, the test will say that 2% have been infected. To get good numbers, you need a population where lots of people have been infected. That will allow true positives to swamp the false positives, which is what happened in the NYC study that claimed 21% of people had already been infected. Even if it's really only 19%, that doesn't change much. You also need a good random sampling procedure. IIRC, the NYC study tested people shopping for essentials at mid-day. This underrepresents essential workers, people who are really good at self-isolation, and people who are currently sick. But still, it's not too bad. The New York City numbers suggest that very roughly 1% of people infected with the virus will die, depending on how you count probable but unconfirmed COVID deaths reported by NYC. This could be off by a factor of two in either direction, depending on how good the random sampling was, and the characteristics of a given population.
- MengerSponge 7y ago
  Nicely put. With a case fatality of ~1%, we need orders of magnitude reduction, not factors of 2. If anyone wants to quibble over a factor of 2 you've missed the point. Now my nightly rant: I did this kind of false positive calculation in high school statistics, and I hated it. Still do. I hate that we're dealing with this BS. I hate that stupid people put us in this position, and that smart people aren't smart enough to not be absolute knobs.
creato 7y ago
Why are you citing the NYC study as reinforcement of the other two? It is unlikely that all 3 are correct, because they imply significantly different outcomes of an infection.