I'm with you on how depressing it is, my biggest take away from this entire thing so far is that people's ability to link cause and effect is much lower than I had previously estimated.
I'm now very mildly asthmatic and had pneumonia and bronchitis often as a child. I know what not breathing, and chronicly not having a strong respiratory system can be like and most people don't. I think that really factors into why people aren't taking it as seriously, going out whatever.
Contrast that with the fact I basically haven't left my Brooklyn apartment in 8 or 9 weeks even though my asthma and breathing issues largely subsided years ago and I would be considered less than mildly asthmatic now, I imagine other people with my profile are acting similarly.
I think it totally makes sense why you would feel that way.
I do want to mention that we know that somewhere between 25-50% of COVID-19 cases appear to be entirely asymptomatic (as opposed to pre-symptomatic). So almost half of people who get it won't even realize it, of those with symptoms, only a small fraction will go on to experience the serious respiratory issues that characterize COVID-19.
So it makes sense that you know first-hand how horrible breathing problems are. But I just wanted to be clear that, it's actually not irrational for someone to not want to stay inside for months to avoid a disease that in their specific case would almost certainly be mild. It just goes into what a person's priors are.
For sure and to be completely clear, I don't want to stay inside, I just think it's the most responsible move.
Like you said though it comes down to priors, and I'll add risk tolerance, and some pro-social behavior (I won't risk my neighbor even if it might be fine for me). I work in startups and have a few failed companies under my belt my risk tolerance in business is very high but not with health, you read that as 25-50% of cases are asymptomatic and an even smaller percent develop the very horrible symptoms, I read that as there is a 75%-50% chance I'd be symptomatic and a non 0 chance I'd be seriously ill with symptoms I'm already averse to through experience with them even though I'm otherwise young and healthy.
Edit: I'll add in, besides the above my biggest motivator for staying inside is that even if I was fine, to me its untenable to potentially spread it to someone who has a higher chance of not being fine through no fault of their own.
> we know that somewhere between 25-50% of COVID-19 cases appear to be entirely asymptomatic (as opposed to pre-symptomatic).
Which is not a big number at all, at least, not big enough to suggest that infecting more people is a solution. Considering that the chances to have symptoms and die rise exponentially with age, the estimated 25-50% are young and lucky ones. Still, it is known that even kids (unlucky, i.e. not in great proportion) do die:
By the way, from the older investigations about how people self-report their respiratory illnesses, it is already known that some significant percentage would not report anything and when asked claim not to have any symptoms even when they demonstrably do have them.
Even now, in the middle of coronavirus pandemics, there are people who "become used" to less oxygen in their blood, and behave as "not ill" even as their body becomes permanently damaged by the low concentration of the oxygen destroying their tissues.
So "asymptomatic" in the sense "the patient or the person filling up the questionnaire didn't feel being ill" is totally different from "the doctors didn't find any symptoms."
Have you seen any attempts to actually put cause and effect together for stay-at-home orders and number of deaths? The only attempt I've seen to quantify it found no statistical connection between the two, but high connection between population density and deaths.
Just a quick search on scholar shows me at least 5 studies into the impacts for a more rigorous analysis.
Plus anecdotally I'm in NYC and since the stay at home order reached full strength the 3 day rolling average of infections has been decreasing. I can only see that being attributed to two things -- mask wearing and stay at home. Mask wearing came later in our lockdown so I'm going to say stay at home has been effective especially with what I've seen the infection number for COVID, I believe that's the R0 (Rt?) number, was something like 2.5 to much higher.
>I can only see that being attributed to two things
Two more things: 1) introducing (or the halting thereof) infections to at risk populations (the whole NY nursing/retirement home fiasco, or the Italy hospitals being points of transmission, or dorm style living in Wuhan) and 2) approaching ~50% of herd immunity.
1) When did NY state stop putting exposed/infected patients into those facilities? That's going to have a outsized result in the stats, given the segment vulnerability. Same for Italy hospitals being overwhelmed without PPE.
2) Not saying it's what is at play (yet) here, but infections will naturally decrease as a greater percentage of the population gains immunity. It's what has to happen as the population approaches herd immunity. (So about 30% if herd immunity is 60%, which is plausible, given the recent estimates of 20+% of the NYC population with antibody presence.)
It's why exponential growth (for resource limited kinetics) ends up being an S curve and not a runaway exponential curve. The inflection point might not be at exactly 50% for a number of reasons, but it's good for a rough starting point.
Additionally, it will be difficult to distinguish if the stay-at-home orders are effective due to the entire population participating, or if it's tied to specific population segments. Meaning the percent of the population active vs stay-at-home isn't independent of transmission numbers. The active sub-population might be closer to herd immunity than the stay-at-home crowd.
This gets more complicated as you take into account the risk levels of particular patients.
There's potentially a lot more going on. We need some scientific causation, not just correlation.
That's two, I think the second one is better though as it uses more recent data and from more states and they raise a point that I think speaks to why the studies are not more prevalent and that is that many stay at home orders went into effect middle to end of March so the effects would only really be seen at the end of April.
I imagine you'll see more of these popping up in the coming weeks.
I said that there was a measurable connection between them. Any epidemiologist will acknowledge this.
The point is that it could be seen and measured in this case. But when they attempted to find a connection between shutting down early or late (in the USA), no effect was found. The point being, the shocked horror that people already "forgot" the lessons learned last month is silly if that lesson wasn't learned and wasn't even true. The claim could do with some actual evidence.
And I'm not even saying it's not true. I'm just saying this is the only attempt I've seen to actually analyze it, and it came up the opposite way. Can you point me to anything that shows the claim is true?
