I couldn't find any detailed write up about their selection methods for participants, only the basics of where they found them. Without that, it is very hard to determine whether or not there's some flavor of selection bias: If it is voluntary, and they do not screen out people who report having had cold/flu symptoms, then they run the risk of attracting a disproportionate number of people who volunteer because they're curious if their prior symptoms were actually coronavirus. That would make it far from a random sample. The fact that they sampled only people actually leaving their house is also a form of selection bias: these are the people more likely to be exposed and may represent a disproportionately high infection rate as well.
So I await further information.
That said, even if it's overall 0.6%, that is still 6x higher than flu, and higher than H1N1 which had a CFR around 0.1 for areas with adequate health care. (much higher when there was not adequate care, but that is not dissimilar to Covid.)
So no matter what, no one should be walking away from this study saying "See it's no big deal! Just the Flu/Cold etc!"
Flu is generally well under 0.1% of those infected on average. If you’re comparing them you want to either include or exclude asymptotic people from both populations. “Symptomatic Illnesses” https://www.cdc.gov/flu/about/burden/index.html
As to NYC deaths, many people currently infected will die in the future. You can make various estimates to account for this but a reasonable first approximation is to double current deaths based on NYC’s infection curve vs South Korea’s.
Flu rates are based on all known knowledge, population testing, etc. We don't have that for covid-19. If you want a good apple-to-apples comparison of lethality of another pandemic, you need to find CFR numbers that were available during the pandemic. That is what I provided in my post. Here is the source I got them from [0] which gives the CFR at the 10-week mark for H1N1, somewhat similar to where we are now. Here's the relevant quote:
>"The overall case fatality rate as of 16 July 2009 (10 weeks after the first international alert) with pandemic H1N1 influenza varied from 0.1% to 5.1% depending on the country."
There are near instant tests for flue in most every urgent care center I've been to (easier and faster than getting a dr appt.)
Whenever I have gone or brought my kids when sick, they perform the test to rule out any potential need for antibiotics. When I asked, they said it's systematically reported to the the CDC as part of their flu surveillance system, whether positive or negative. That surveillance network is significantly more robust than a survey.
0.6% this is the estimated ifr. comparing it to the cfr of flu is not right, which is about ten times less than the flu ifr - or about 60 times less than this figure. your conclusion is upheld, but even moreso
According to the CDC, the estimated prevalence of symptomatic flu last year was 45 million illnesses and 61,000 deaths.
For NY, assuming it’s evenly distributed, that would translate into 13.8% of 20 million = 2.8m symptomatic flu cases and 3,753 deaths.
COVID appears to be significantly more prevalent (roughly twice as prevalent in just 3 months as flu gets all year despite incredible efforts), and roughly 2-3x as fatal.
I think you need to rethink essentially all of your assumptions/math. COVID is not more prevalent than the flu and certainly more than slightly more fatal.
20% infection rates already puts SARS-CoV-2 at higher prevalence than the flu. And we're barely a couple months into the time period of significant spread.
Why would you think that SARS-CoV-2 would not be more prevalent than the flu? The fact that we have no natural immunity, combined with how virulent it is, indicates the endpoint infection rate will be significantly higher than an average flu season.
"In the U.S., for example, in recent years about 8.3% of the total population get sick from flu each season, a CDC study found; including people who carry the flu virus but show no symptoms, that estimate ranges to up to 20%."
The endpoint percentage of fatalities is a multiple of the infection rate times the fatality rate. Both numbers are equally important.
We've been hearing the "10% hospitalization" and low-single digit CFR numbers for months. At 20% prevalence, the NYC actually had 1.7 million cases, 36,723 hospitalizations, for a hospitalization rate of ~2.1%.
According to the CDC web site, those numbers are 35.5M flu cases and 34,200 deaths (https://www.cdc.gov/flu/about/burden/2018-2019.html), giving an IFR of more like 0.1%. Which would put COVID-19 at more like 5-6x more fatal than the flu. Combine that with the virtually complete lack of natural and vaccinated resistance compared to the flu, and it's clear that the potential fatality totals for COVID-19, absent drastic action, would be much, much higher than for the seasonal flu.
I agree 100% it will be significantly more prevalent, due to the nature of the virus combined with the total lack of natural or vaccinated immunity.
However, it's not clear at all what our "drastic action" is achieving, aside from 20 million unemployed and trillions of dollars spent trying to hold everything together. 20% prevalence doesn't exactly speak volumes towards the efficacy of social distancing.
That 45 million in your first link is Symptomatic Illnesses which represent ~2/3 of total cases as Approximately 33% of people with influenza are asymptomatic. https://en.wikipedia.org/wiki/Influenza So, total infections would be closer to 67.5 million.
But, it’s important to keep things in context, another year lists 9.3 million symptomatic infections and 12,000 deaths. The average year is well below peak years.
"... it's not clear at all what our "drastic action" is achieving..."
It's no coincidence that the city that shows a much higher prevalence also experienced a much more acute infection, straining their medical infrastructure. That isn't evidence that social distancing doesn't work, it's evidence that the infection was already well on its way before social distancing was implemented there. NYC was the canary in the coal mine that triggered social distancing across the US, and as a result the experience in NYC has not been repeated elsewhere. Aside from the results, which should speak for themselves, the epidemiological connection between R0 and the prevailing rate of social interaction is clear, which is why it's accounted for in the models.
I actually agree with everything you said, but I still haven’t found the basis for the tremendously costly actions taken.
As we can see, NYC did not particularly flatten their curve, and they did not see excess deaths due to lack of available care. They already hit the endpoint prevalence that you would see with the flu in a very bad year.
It’s not clear how much further SARS-CoV-2 would go naturally — the S curve doesn’t ever go to 100%. But more importantly, without a vaccine, which we won’t see for 12-18 months, we are going to find out exactly how high the S curve goes.
We have a small degree of control over exactly when that happens by burning extremely large amounts of money. So, when do you want it to happen? Now, while flu is at its nadir, or after spending $10 trillion dollars perhaps we can see the final surge during the peak of the next flu season?
The fact is that there isn’t actually a known treatment for COVID, and even with treating the symptoms (invasive ventilation) 80% of people in the ICU will die. This isn’t a disease for which “flattening the curve” makes particular sense. That would require there actually be an effective treatment.
NYC did not particularly flatten their curve, and they did not see excess deaths due to lack of available care.
I'm pretty sure all the family members of the people who died would regard their loved ones as "excess deaths". Your technocratic language ascribes no value to the lives lost, in which case of course the actions seem excessive. For people who don't value the lives of others, it would be hard to understand all the fuss.
This isn’t a disease for which “flattening the curve” makes particular sense. That would require there actually be an effective treatment.
This is a self-contradictory statement. The whole point of flattening the curve is to buy time to develop exactly those effective treatments. It is also possible to flatten the curve to an extent that there are fewer deaths under it, and based on the continual downward revision of the IHME model fatality estimates, that appears to be exactly what is happening.
So the most charitable interpretation of my comment is to convince yourself I’m a sociopath?
Excess deaths is a term of art to describe a number of deaths over a baseline. It can be used in general, or specifically, as I was using it, to describe the repercussions of an overloaded health care system. Here, for example, is a Sky News story from today using the term in its headline. [1]
I think you owe me an apology, but I won’t hold my breathe.
“Flattening the curve” is absolutely not intended to buy time to develop a cure or vaccine. The timeline over which the economic devastation of flattening the curve can be sustained is measured in weeks not 12-18 months.
The purpose of flattening the curve is to be sure there are the necessary number of hospital beds and ICU beds to provide effective treatment. If effective treatment can not be provided it leads to “excess deaths”.
Bad projections based on a 10% hospitalization rate and based on assumptions that ICU ventilators wouldn’t kill 80% of patients, have led to disastrously bad public policy which is causing untold suffering throughout the country. This suffering, which many people seem to be blind to, is notably self-imposed rather than natural, and through logical and reasonable interpretation of factual data we can stop this suffering.
This is very much unlike the suffering caused by people who are dying from COVID, for which unfortunately we have no effective cure or treatment, and for which it is not reasonable to assume we will develop one in the timeline of this current pandemic.
This is the key takeaway from “flattening the curve”. It cannot and will not decrease the total number of people who are ultimately exposed at this stage of the pandemic. Once the health system capacity is high enough to handle the number of cases coming in with effective care, continuing social distancing causes extraordinary damage without any benefit.
Since effective care at this point has proven to be both simple and extremely scalable (non-invasive ventilation, antibiotics, and frequent repositioning) the resource curves for effective care are extremely larger than projected, back when they were based on availability of ventilators.
Simply put, the data has changed, and it’s time to update the policy. It’s extremely incompassionate to do otherwise.
However you choose to define the term "excess deaths", the fact remains that there are tens of thousands of people alive today who would be dead if we all took your advice and ignored the notion of social distancing. Does that make you a sociopath? No, it simply makes you wrong, policy-wise, if you value human life. Unless you really are a sociopath, and advocate the policy precisely because you don't value those lives. I can either give you the benefit of the doubt morally, or intellectually. Which do you prefer?
You are correct that social distancing and flattening the curve protects the health care system from overloading. That doesn't mean that it is the only purpose, or effect. If we took a poll among health care policymakers about the benefits of flattening the curve, I'd be happy to bet any amount you'd like to wager that "buying time to develop effective treatments or a vaccine" would be on their list.
This is the key takeaway from “flattening the curve”. It cannot and will not decrease the total number of people who are ultimately exposed at this stage of the pandemic.
This is just mathematically untrue. There is clearly a point where the curve is so flattened that the number of deaths under it is less than a baseline "no action" scenario. If we could somehow get everyone in the US to truly isolate for three weeks, the virus would die out entirely. So clearly there is a spectrum of actions and their corresponding outcomes. The number of infected (and dead) is not a fixed number with only the duration of the outbreak changing.
If your premise were simply that the current measures are unsustainable, I couldn't agree more. Fortunately, those measures have bought us the time to take more focused, informed action based on the latest data. In a crisis this fast-moving, every day is time to update the policy.
Those are the people who constitute the denominator for the CFR. It's a completely different metric. You would never try to impute population exposure from such cases. This study is trying to to impute population exposure. There isn't any comparison between the two in terms of which has more/less selection bias, they are completely different things.
That's because all of the statistical reporting is whacked up across the globe. The only thing that can reasonably be measured now is CFR. Without extensive, reliable serological testing with high specificity, IFR can only be guessed at.
That said, even if it's overall 0.6%, that is still 6x higher than flu, and higher than H1N1 which had a CFR around 0.1 for areas with adequate health care. (much higher when there was not adequate care, but that is not dissimilar to Covid.)
So no matter what, no one should be walking away from this study saying "See it's no big deal! Just the Flu/Cold etc!"