This isn’t helped by the facty - and a lot of people won’t like me saying this but here we go - the fact that the wave of flu deaths is exaggerated. The number you see thrown around, about how 30,000 or 50,000 or 75,000 people die from flu in the USA every year (or whatever - the number varies from claim to claim) just aren’t true. They are broad estimates, having no relation whatsoever to the official causes of death of people who died. They heavily rely on conflating flu with other causes of death, especially pneumonia, which can be caused by flu but can be caused by many other things. It just is not true. Flu is dangerous but the wild figures being put out there are dishonest, by at least an order of magnitude
COVID-19 can quite easily surpass the numbers flu REALLY kills, and the risk exists it’ll surpass the fantasy numbers too.
OP: here’s a detailed article on that issue. No short bullet points in the article, but you might prepare some from the article and then post your bullet points and a link to the article.
I would stay away from any political comments if you’re hoping to change people’s thoughts on the issue. Keep it clinical.
For most of them IMO misreacting more than overreacting.
But yes you are on point about having some appreciation for the “costs” - which include very real health harms - and balancing it against possible or theoretical benefits.
To my mind job one was to get the information that we need to make actual intelligent decisions. I can think of no reason why by now there have not been good studies sampling the population at large in Hubei for antibody levels in order to determine basic critical bits of information such as what the true infection rate in different age and gender demographics was, and of those how many were completely asymptomatic, how many mildly symptomatic, etc… It seems that those who are asymptomatic or extremely minimally symptomatic and then recover are of less contagion risk than those who at least become more moderately sick. Confirming that is key.
It is only with that information that experts can actually do more than wild assed guess about what sort of social distancing measures are most effective, where returns diminish, how possible containment was, and come up intelligent estimates of benefits to balance against possible costs. Without it we have no real idea what the shape of the curve might be with and without different social distancing measures.
Aggressive testing, including of contact tracing, and isolation of those positive, might have been able to hold off its widely spreading in the first days of its identification in America. It seems likely to me that that opportunity is now past.
So we are at a point in which we are trying to alter the shape of the curve, hopefully avoiding a peak (of it plus influenza) that exceeds health systems capacities, but doing so fairly blind, with no idea as to true infection mortality rates for each demographic, or how contagious people at different ages with different presentations are. No real idea of what the curve would look like in our demographics in any of the circumstances.
And in the face of that lack there is knee jerk application of near random and somewhat extreme bits from the pandemic flu toolkit, even though one the few things we already know is that this does not follow the same patterns. School closings, preventing gatherings in which people are NOT on top of each other, broad social isolation as the norm for who knows how long, taking those of lowish risk for serious morbidity and mortality but high risk of spreading it about when they get it and throwing them into the communities with those of high risk, instead of containing them on campuses, and much else, are to me misreactions.
Given that we are now past containment the issue is mitigation. We know that the highest numbers of deaths occur in specific populations. To my mind the ideal would be have aggressive surveillance testing across the country and as rates started to rise in certain areas implement aggressive protective measures for that population during the period of moderate to high COVID-19 in their communities. As practically as possible isolate them during the storm (wearing effective mask protection whenever visited or out) and when they come out, as rates drop back down on the other side, if this really is so contagious and 30 to 50% have been infected and are now, most of them, recovered, then they are in an environment with much reduced risk of exposure. The actual amount under the curve is reduced.
If we are to aim to alter the shape of the curve do not forget that the actual curve that matters is COVID-19 PLUS influenza demands. Be very cognizant of the risk that an attempt to flatten may end up resulting in just delaying the peak to coincide with next season’s influenza demands. The less catastrophic would be to aim to backfill into a time period that we can reasonably expect influenza rates to be low. Which would imply that we want whatever it will unavoidably be to occur during weeks 16 to 42 (see the seasonal flu numbers over the years here), IOW mid April to mid October, if we knew enough to know how to do that, not to slow it to a degree that were still fairly maximal numbers of those susceptible in October and November as flu is likely to erupt.
FWIW much of what is being done in the name of mitigation is NOT what is currently advised by the CDC. School closures (grade, HS, and college) are, for example, only advised when there is “substantial” community transmission (“Large scale community transmission, healthcare staffing significantly impacted, multiple cases within communal settings like healthcare facilities, schools, mass gatherings etc.”, and then mostly because of the expectation of too much staff or student body out sick.
Risk balancing, for release of a poorly tested pharmaceutical, requires knowing how many people have COVID-19 antibodies divided by how many people die of the disease. If something on the order of 2+ percent, a terrible risk is justified.
Knowing the results of that division requires first developing an antibody test, and then testing a random sample of a population in a society where death certificate causes of death can be trusted. Before the end of 2020, we probably will have some reasonable approximation of that number.
My guess is that, when good evidence is available, I’ll think abbreviated testing a big mistake.
I’ve read this and the follow ups. Not that I disagree with the assessment, and although it could be a damned if you do damned if you don’t situation, you are committing the same fallacy. As you said, we don’t know many of the answers, but by framing it this way, you are making it a praised if you do, praised if you don’t situation.
If nothing much would have happened anyways, you cannot baldly claim that the overreaction without question caused the not amounting to much.
One of the main CDC spokespersons said that the reason why COVID-19 may be underreported is that many people believed that they just had a bad cold and never sought treatment. Well, if that is so widespread, then it leads me to believe that this is not Dr. Tripps and that I won’t be dreaming of Randall Flagg or Mother Abigail very soon.
And as Manda Jo said, we are paying a rather extreme price both economically and personally for something that for most people is very mild. And not to be an asshole, but does this whole thing boil down to giving a few 87 year olds a chance to survive this until the flu or something else minor kills them next year?
I’m not trying to be so cold-hearted, but is this the bottom line here?
Everyone, please don’t conflate my views with this. I am not saying all these things aren’t worth the cost, nor do I think the lives of old people are of low worth. Some of my favorite people are old.
UltraVires, it’s worse for those over 60, but it kills other people, too. It especially kills them (us, maybe, me or you or someone you love) if we are stuck in a hospital hallway in an overwhelmed medical system.
Honestly, having read everything, it appears we just don’t know what we should be doing. We don’t have the information we need to make the right choice. It seems appropriate to me to err on the side of caution, just because it could be so very bad. Recognizing things have a high cost isn’t arguing that they are inappropriate.
I look forward to reading the books about this, and hope they will make sense.
It is estimated that 20-somethings who have been infected by COVID-19 have a 0.2% risk of dying (assuming they have access to adequate healthcare).
This doesn’t seem like a big risk when we’re talking about low numbers.
But let’s say 30% of Americans ages 20-39 get infected by the end of the year. That’s a little over 12 million people. 0.2% of that number is 24,000.
*That’s just 20-somethings. *
And of course, that 0.2% is based on statistics from China, where people were literally welded into their homes for a month to keep this thing contained. China built extra hospitals and mobilized an army of doctors and nurses so that people of all ages would be treated. Needless to say, we aren’t doing this here.
Much more deadly than the seasonal flu, but nowhere near your numbers. And if we have a bunch of people who never even go to the hospital because they think they just have a bad cold, then those numbers are vastly overstated.
France and Spain have closed all businesses except grocery stores and pharmacies. What more would/could they do if this was the actual Black Death of the 1300s, or Captain Tripps from The Stand?
I’m not saying that we are overreacting. I don’t know enough to say that. But it would seem to a layperson that we are.
Of course there’s a lot we don’t know. We do know that we aren’t testing at the same rate that SK is, though. We don’t have the kind of healthcare system that SK has (SK has four times the number of hospital beds the US has, per capita). So we shouldn’t use SK’s outcomes to inform us of our risk. We seem to be following more of the path of Italy, which chose to take a wait-and-see approach until shit got too real. Since we don’t have the political will to do what SK has done with testing and we can clearly see that Italy’s approach has been disastorous, then it makes perfect sense to be as proactive as we can without literally welding people into their homes. Our strategy my not end up being a good one either, but what is the alternative? No one is saying what we’re doing is the best way.
So I guess I don’t know what point you’re trying to make.
I guess the short, short version of my point is that we are taking an awfully goddamn drastic approach to something that we don’t know very much about. Panicking people and trashing the economy and people’s lives: marriages canceled, vacations canceled, sports cancelled, high school seniors no prom or graduation ceremonies, unemployment, businesses going to close, lost opportunities, social distancing, and the like. All for “we don’t know.”
ETA: And from being around town, bars, strip clubs and tattoo parlors are still running as usual, but not schools.
But we do know what’s happening in Italy. We’d be fools to not use what’s happening in Italy (and now Spain) to motivate us to take an awfully goddamn drastic approach.
Because bars, strip clubs, and tattoo parlors are run by people who won’t be held accountable if a public health disaster happens.
An analysis that looked at the decisions by the lens of economics is very hard to do with the information we have UltraVires, but it would include what is called “Quality Adjusted Life Years” (QALY). QALY’s monetary value is not applied consistently but seems to generally range between $50 to 150K at full health value. So yes economic analysis values a healthy 30something with 50 years of presumed life ahead as worth much more than an 81 year old with significant disability. In 2008-2009 the H1N1 pandemic had a significant impact on QALY because it impacted younger people more commonly than the old and infirm.
The analysis would have to know how many QALYs are likely to be preserved at what net cost.
I’m gathering that most have accepted the concept that the goal now is “flattening the curve” and understand that the concept assumes the same number of total cases in each age cohort but in one case more occurring in a circumstance in which the system is over its capacity threshold, and in another the threshold is never breached. So applying the economic analysis lens would have to be able to estimate how many more of which age groups (and thereby how many QAYs) would die as a result of the threshold being breeched that could be avoided by investing in these costs today? And then add in the other economic costs (lost productivity, so on) and/or (cold this) savings of those lost lives.
Anyone doing such a modeling exercise could use a variety of hypothetical assumptions, of different fractions getting infected in each demographic and different true mortality rate, and different impacts of avoiding the threshold being breeched, and even different odds of the investment having that avoiding breeching capacity payoff to different degrees.
Doing such might offend some people, making decisions on its basis likely third rail, but it would still be an interesting and important analysis.