The 100% efficacy for a middle filter layer that's had a saltwater + surfactant sprayed onto it sounds really good; but I wonder how tight the filter material has to be, for that level of efficacy. I also wonder how much air resistance the salt coat adds.
A HEPA filter + carbon would be less restrictive if the carbon part were salted than if the HEPA filter itself were salted, but that might not deactivate all of the virus.
If virus exposure mid-illness worsens your symptoms, doesn't that mean being indoors is harmful? it would be far healthier to spend as much time outdoors as possible? Perhaps on a net hammock if you have to lie down, so your face isn't lying on a cloth full of the virus you're exhaling? Surely this effect would be so large that clinical studies would have noticed by now, people recovering much faster when they're not in a hospital room, or in a room at all.
On a gears-level, it seems like illness severity would be heavily dose-dependent until the virus replication rate has outpaced the amount you could reasonably inhale.
If so, if you have a specific event that you're concerned may have exposed you, it might be worthwhile to sleep outside for a few nights, weather permitting.
How many dimensions is inference space? How many duck-sized horses do we need, to have a 2/3 chance of taking those steps? And are they being modeled as duck-sized monkeys with typewriters, or are they closer to a proper mini-Einstein, who is likely to go the correct direction?
I live in a hot region, and have a car parked outside. I've been putting non-heat-sensitive packages in there for a day, since interior temperatures should be going above 130F / 55C, and easily killing any viruses.
Disinfection guidelines are 70C for 30 minutes. I've read elsewhere that 27C deactivates the virus, but never seen that claim attached to logs per hour. Has anybody seen quantitative data on covid survival rates in human-survivable temperatures at various humidities?
edit: found some stuff for the last SARS: if you go to 100F / 48C *and* 95+% humidity, you will kill 2 log10 in 24 hours. If you lose humidity *or* temperature, you’re back to the baseline of 1 to 0 logs in 24h.
Is the described process different from Dempster-Shafer ?
For the object-level question, Wei Dai linked to this study showing benzalkonium chloride (and a few related chemicals) ineffective against enveloped human coronavirus (although this was one of the common cold variants).
This is good, but I'd add a caveat: it works best in a situation where "normal" is obviously not catastrophic. The airplane example is central to this category. However lift works, air travel is the safest method of getting from one continent to another ever devised by humanity. If you take DMT and finally become aware of the machine elves supporting the weight of each wing, you should congratulate them on their diligence and work ethic.
The second example, morality under MWI, veers closer to the edge of "normal is obviously not catastrophic." MWI says you're causally disconnected from other branches. If your good and bad actions had morally equivalent effects, you would not anticipate different observations than you would under "normality."
As lincolnquirk pointed out, Covid and other long tail events are diametrically opposed to the "normal is obviously not catastrophic" category. Instead of the object-level belief being changed by a discussion on aerodynamic theory, it's being changed by the plane suddenly falling out of the sky, in a way that's incompatible with our previous model.
So, I'd tweak your adage: "promise yourself to keep steering the plane mostly as normal while you think about lift, as long as you're in the reference class of events where steering the plane mostly as normal is the correct action."
Sure, but the landlords' rent/mortgage and grocery bills are being suspended too. If the landlord is a business with multiple employees, those employees' rent/mortgage and grocery bills are also suspended. It's option (1) all the way down.
Data from periods of forced conscription would correct for that bias, but would introduce the new bias of a 4-F control group. Is there a fancy statistical trick to combine the data and eliminate both biases?