The US FDA (U.S. Food and Drug Administration)’s current advice on what to do about covid-19 still pretty bad.
Hand-washing and food safety seem to just be wrong, as far as we can tell covid-19 is almost entirely transmitted in the air, not on hands or food; hand-washing is a good thing to do but it won’t help against covid-19 and talking about it displaces talk about things that actually do help.
6 feet of distance is completely irrelevant inside, but superfluous outside. Inside, distance doesn’t matter—time does. Outside is so much safer than inside that you don’t need to think about distance, you need to think about spending less time inside [in a space shared with other people] and more time outside.
Cloth face coverings are suboptimal compared to N95 or P100 masks and you shouldn’t wear a cloth face covering unless you are in a dire situation where N-95 or P100 isn’t available. Of course it’s better than not wearing a mask, but that is a very low standard.
Donating blood is just irrelevant right now, we need to eliminate the virus. Yes, it’s nice to help people, but talking about blood donation crowds out information that will help to eliminate the virus.
Reporting fake tests is not exactly the most important thing that ordinary people need to be thinking about. Sure, if you happen to come across this info, report it. But this is a distraction that displaces talk about what actually works.
Essentially every item on the FDA graphic is wrong.
In fact the CDC is still saying not to use N95 masks, in order to prevent supply shortages. This is incredibly stupid—we are a whole year into covid-19, there is no excuse for supply shortages, and if people are told not to wear them then there will never be an incentive to make more of them.
I like the idea of this existing as a top-level post somewhere.
6 feet of distance is completely irrelevant inside, but superfluous outside.
That seems to be a bold claim. Do you have a link to a page that goes into more detail on the evidence for it?
Here in Germany Bavaria decided as a first step to make N95 masks required when using public transport and shopping and it’s possible that more German states will adopt this policy as time goes on.
One weird trick for estimating the expectation of Lognormally distributed random variables:
If you have a variable X that you think is somewhere between 1 and 100 and is Lognormally distributed, you can model it as being a random variable with distribution ~ Lognormal(1,1) - that is, the logarithm has a distribution ~ Normal(1,1).
What is the expectation of X?
Naively, you might say that since the expectation of log(X) is 1, the expectation of X is 10^1, or 10. That makes sense, 10 is at the midpoint of 1 and 100 on a log scale.
This is wrong though. The chances of larger values dominate the expectation or average of X.
But how can you estimate that correction? It turns out that the rule you need is 10^(1 + 1.15*1^2) ≈ 141.
In general, if X ~ Lognormal(a, b) where we are working to base 10 rather than base e, this is the rule you need:
E(X) = 10^(a + 1.15*b^2)
The 1.15 is actually ln(10)/2.
For a product of several independent lognormals, you can just multiply these together, which means adding in the exponent. If you have 2 or 3 things which are all lognormal, the variance-associated corrections can easily add up to quite a lot.
Remember: add 1.15 times the sum of squares of log-variances!