It was textbook poisoning the well - like, logic 101 stuff. The fact that she has a PhD in economics has no bearing on the substance of her argument. The substance is what matters and should be addressed.
It’s a thin, brown bad-smelling bovine sourced liquid.
She’s trying to apply investment strategies to a health concern.
I’d be happy to discuss the article after you actually read it. It’s a waste of time if you don’t have any interest in honest discussion.
Dunno if these have been posted. I don’t think so. They are both promising stories about the availability of testing going forward:
Or, a pretty good, but paywalled article about the same topic as Abbott’s news release
Thanks, this is good stuff. I’ve read about most of the studies in here. The ME/CFS stuff sounds horrible. Hopefully some of the studies being run will bear fruitful results and we get a better understanding of what’s going on with the “long haulers.”
This is not remotely close to what “poisoning the well” means.
You are correct to point out that it’s not poisoning the well to make relevant criticism of the source, such as lack of expertise in a relevant field. But if you read the article it clearly cites data from the CDC and other expert sources on the technical epidemiological aspects, the author is not claiming any epidemiological expertise herself. The substance of the article is a comparison between public perceptions of risk (supported by data from a survey) to the epidemiological facts (citing the CDC etc.). That comparison doesn’t require expertise in epidemiology.
I think @Trom is correct, if you disagree with the article, you need to address the substance of the article - the validity of the data or the merits of the reasoning.
You are correct to point out that it’s not poisoning the well to make relevant criticism of the source, such as lack of expertise in a relevant field. But if you read the article it clearly cites data from the CDC and other expert sources on the technical epidemiological aspects, the author is not claiming any epidemiological expertise herself. The substance of the article is a comparison between public perceptions of risk (supported by data from a survey) to the epidemiological facts (citing the CDC etc.). That comparison doesn’t require expertise in epidemiology.
I think @Trom is correct, if you disagree with the article, you need to address the substance of the article - the validity of the data or the merits of the reasoning.
I agree. The article is simply a summary of polling data from a survey conducted by Gallup. I can see having reservations about the fact that an investment company sponsored the survey, or methodological issues about the wording of the questions (e.g., asking people to estimate what percentage of total deaths are among people in a particular age group is potentially confusing, since people can easily misinterpret it as “what are the odds of dying for an individual within this age group”), but claiming that the author is just basing it on her own opinion is silly.
The data seem to show that people have massive misconceptions about which age groups are at risk.
I have no idea what this is supposed to mean. Who are “they” and what is the alleged conspiracy theory here?
It seems to me that there may be significant implications for policy in realizing how badly people misunderstand who’s at risk. An obvious example would be a young person who knows of nobody in their hundreds of young friends who has got sick, and concludes incorrectly that it has all been exaggerated, and the risk to their elderly relatives is low. At the very least we should be doing a better job of educating people. And to the extent that we do start to relax social distancing measures, should we be doing much more to help at-risk groups to isolate themselves until there’s a vaccine?
The article posits that every age group’s fear of serious health effects is greater than its share of deaths (not serious health consequences), except 65+ where it’s under by 2.4%. It’s apples and oranges, the survey was done July 2 - 14 in the middle of a spike.
It compares fear ratio during a spike vs death share on July 22.
It’s apples and oranges and a lot of wool over the eyes. It belongs in the “LIBERATE MICHIGAN” pile.
That’s a valid criticism of any claim about absolute level of risk, and the author is upfront about this problem with the data. But it doesn’t invalidate the evidence that people’s perceptions about the relative risk for people in different age groups seems to be wildly wrong. Epidemiological data for “serious health consequences” may be slightly less skewed by age than risk of death, but still surely not remotely in accord with public perceptions.
And again, if people overestimate the relative risk of serious symptoms among younger people, but then see that in a community of young people nobody is sick, they may incorrectly conclude that the virus is not circulating among those people.
I don’t see where 100% of a cohort of people having concern about serious health effects of Covid is a problem regardless of what that cohort’s death share is.
Except as it relates to refraining from commerce.
You don’t see, and yet you’ve ignored the fact that I’ve pointed out to you (twice) why it’s a problem.
People mistakenly think that infection leads to serious disease in a significant proportion of young people. You really don’t see how the absence of serious disease in a group of young people might lead people to infer incorrectly that infection is not spreading among them? And to infer incorrectly that the prevalence or seriousness of the virus is exaggerated, and they don’t need to do all this silly stuff like wearing masks?
Exaggerating risk can be as dangerous as minimizing it.
Since one’s functional chance of death is 0 (not die) or 1 (die), caution would suggest evaluating one’s risks as important even if disproportionate.
The data presented in the article quoted does not in fact show this. She’s comparing “the share of people who are very worried or somewhat worried of suffering serious health consequences should they contract COVID-19” with mortality data, as though dying is the only possible serious health consequence. I do not see in the article how the respondents defined (or were asked to define) “serious health consequence”; how would you define it, and are you certain that all of the respondents would view it the same way?
For example, is being sick enough to miss work for a week or two, even if you are never hospitalized, a “serious health consequence”? Maybe, especially for people who rely on the paycheck. Now, what percentage of people in what age ranges who come down with COVID-19 are sick enough to miss work for awhile? Sonal Desai doesn’t provide that data. Do you have it?
The University of Arizona has been testing waste water from the dorms and other buildings, and they identified two asymptomatic people with Covid in a dorm, even though weekly testing was happening. & hadn’t caught it yet. That, I have to say, is both clever and good.
I wrote to my state governor a month or two ago urging him to set up testing of wastewater in all the towns with sewage facilities. I wonder if the state is doing anything like that. He never wrote back.
I agree that conflating death and “serious health consequences” is iffy, but the survey data in the article also shows that people get it really, really wrong when they are asked to estimate the percentage of deaths that have taken place among different age groups. No ambiguity in this question; they were asked only about death. And people didn’t even get it close to right. They guessed, on average, that eight percent of deaths were among people under 25; the actual figure is 0.2 percent.
And I do think that has consequences. Yes, there is nothing wrong with individuals being more cautious about COVID-19 than they “need” to be, as long as they are not deciding to avoid medical care because they’re afraid of contracting it in the doctor’s office. But pressure from the public directly influences decisions about policy, and you can’t make good decisions about policy with inaccurate information. (The converse is not true; it is very possible to make bad decisions with accurate information. But if you don’t start with information that more or less reflects the facts, you’re screwed.)
Would that be complicated to execute? The reason this worked so well for UA is that it’s a mostly-closed system, with only 20 nodes to test, and enforced testing already existing at each node.
A town of say 25,000, that also has commercial structures…I don’t know. Not arguing, just trying to picture it.
About a third of the residents in my town are on septic, so that’s another thing.
I understand what you’re saying about a potential “boy who cried wolf” problem. I’m going after the presentation because they’re not really comparing people’s perceptions of risk probability vs risk actuality and I think they’re trying to slip a fast one past people.
It’s all in this paragraph:
This misperception translates directly into a degree of fear for one’s health that for most people vastly exceeds the actual risk: we find that the share of people who are very worried or somewhat worried of suffering serious health consequences should they contract COVID-19 is almost identical across all age brackets between 25 and 64 years old, and it’s not far below the share for people 65 and older.
The first part of the sentence states people’s fear is greater than the actual risk.
The second part of the sentence says “SHOULD they contract COVID-19”
They are asking people “are you worried about what will happen IF YOU CONTRACT COVID-19”, not “what do you think your risk of getting it is?”
Let’s say the risk of “serious health consequences” for Group A is known (it probably is). Should the percentage of people who say they’re worried about what would happen if they catch it match the actual probability? No, you can’t meaningfully compare those numbers. What would your reaction be if only 0.1% of Group A (or any group really) said they were worried about what would happen if they got it?
Should they have asked, “if you get it, what do you think the chances are that it will be bad?” THAT would be a basis for comparison to actual. You’d have to plot it as a dot chart though.
And just to underline where they’re coming from:
This misinformation has a very concrete adverse impact. Our study results show that those who overstate deaths among young people are more cautious about making purchases, more reluctant to travel, and favor keeping businesses and schools shut.