Coronavirus

Coronavirus Has Infected 2.8 Percent of Hoosiers, Says New Study

The infection-fatality rate for COVID-19 in Indiana is 0.58 percent, nearly six times worse than seasonal flu.

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Between April 25 and May 1, more than 4,600 Indiana residents were tested for viral infections and antibodies for the coronavirus that causes COVID-19 by a team of researchers associated with Indiana University. The participants in the study included more than 3,600 randomly selected people along with 900 volunteers recruited from the African American and Hispanic communities to more accurately represent state demographics.

A news release from the university reports that through random-sample testing the researchers found that during the last week of April, 1.7 percent of participants tested positive for the virus and 1.1 percent tested positive for antibodies. These percentages mean that about 78 participants were currently infected and 51 had developed antibodies against the virus.

Combined figures brought, according to the researchers, the estimated population prevalence of the virus in the state to 2.8 percent, or approximately 186,000 Hoosiers who were actively or previously infected as of May 1. Since 1,067 residents had cumulatively died of the disease by May 1, the researchers calculated the "infection-fatality rate for the novel coronavirus in Indiana to be 0.58 percent, making it nearly six times more deadly than the seasonal flu."

The infection-fatality rate is the percentage of all of the people who become infected by the virus (including those whose cases are asymptomatic or mild and therefore go undetected by medical surveillance) who die of the disease. This is distinct from the case-fatality rate, which reports the percentage of diagnosed cases who die of the disease. The current U.S. case-fatality rate is just shy of 6 percent.

At that time confirmed cases in Indiana numbered about 17,000, which suggests that only about one out of every 11 true infections had been identified through testing symptomatic or high-risk people. The researchers also found that about 45 percent of people who tested positive for active viral infection reported no symptoms at all.

Interestingly, an earlier controversial study by researchers associated with Stanford University and the University of Southern California using only antibody tests sought to estimate how many residents of Santa Clara County (Silicon Valley) California had already been infected by the virus in early April. The researchers conducted a similar study in Los Angeles County. Based on their population screening antibody tests, the researchers estimated that 2.49 to 4.16 percent of the residents of Santa Clara County and 2.8 to 5.6 percent of the residents of Los Angeles County had already been infected in early to mid-April.

Based on these estimates, the California researchers concluded that would mean that by early April between 48,000 and 81,000 people had been infected in Santa Clara County, which is 50 to 85-fold more than the number of confirmed cases at that time. The results of the Los Angeles County study imply that approximately 221,000 to 442,000 adults in the county already had the infection. That estimate is 28 to 55 times higher than confirmed cases at that time in that jurisdiction. Based on these calculations the infection-fatality rates in these studies—somewhere between 0.12 and 0.2 percent in Santa Clara County and between 0.1 percent and 0.3 percent in Los Angeles County—are significantly lower than that reported by the Indiana research team.

In response to the criticisms of their first report, the Santa Clara study researchers re-crunched their data, changing their early April infection prevalence to between 25,000 to 91,000 with a central estimate of 54,000. In other words, the California researchers are still suggesting that undetected coronavirus infections are still 25- to 91-fold greater than confirmed diagnoses. This would concomitantly mean that their infection-fatality rate is also quite low.

Another April study testing some 1,800 randomly selected residents for coronavirus antibodies in Miami-Dade County calculated that about 165,000 residents were infected by the virus. That was more than 16 times the number of confirmed cases at that time. Based on the current Miami-Dade death toll, those results suggested an infection-fatality rate of about 0.2 percent. These results are clearly in line with those reported by the two California studies.

On the other hand, a New York State antibody test study in late April involving 3,000 participants suggests that the rate of mild and symptomless coronavirus infections is only about 10 to elevenfold greater than the number of confirmed cases in those jurisdictions. The New York study calculated that about 2.7 million New Yorkers have been infected, which in turn implies a statewide infection fatality rate (IFR) of around 0.6 percent. These results obviously are more in accord with the findings of the Indiana research team. Assuming the New York blood test data and the Indiana infection and blood test data are reasonably accurate, these studies would suggest that the California studies are overestimating undetected infection rates three to eightfold.

The researchers behind these studies should be applauded for undertaking these complicated studies during the chaos of the unfolding pandemic. So while it is frustrating, it is therefore not surprising that researchers have not yet nailed down just how deadly COVID-19 is. It is, however, sad that the disparate preliminary results of these studies are being selectively used by today's culture war factions to confirm their already existing biases.

Caveat: Other than the Santa Clara study and its update, none of these studies have been published either as preprints or in peer-reviewed journals and so have not been subject to deeper scrutiny by other researchers. 

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  1. The researchers behind these studies should be applauded for undertaking these complicated studies during the chaos of the unfolding pandemic. So while it is frustrating, it is therefore not surprising that researchers have not yet nailed down just how deadly COVID-19 is. It is, however, sad that the disparate preliminary results of these studies are being selectively used by today’s culture war factions to confirm their already existing biases.

    It’s going to take years to wrap our heads around this. We don’t have years, we don’t have months, what’s about to come is already in the pipe. We need to get over it and get back to work yesterday.

    1. No, no, no! Ron Bailey insists everyone in the country must be tested then tracked, otherwise they should be forcibly kept home with their businesses shuttered.
      Otherwise at least 300,000+ Americans are going to die

      1. Link?

        It doesn’t seem out of the realm of possibility that 300,000 Americans might die from this. Still not worth the damage done by the response and the loss of civil liberties.

        1. Link?

          Back when Bailey used to jump into his articles to defend his fragile ego, he would always throw out absurd “just for instance” estimates of 270K – 300K Americans dying from COVID-19 without every bothering to set out a timeline in which this was going to happen. I kept challenging him to take a bet that we would never come close, and then Bailey started calling me a troll.

          1. A. You are a troll half the time.

            B. Bailey has never pretended that any of these estimates are anything but estimates. You trying to corner him into calling these reliable conclusions is one of the marks of a troll.

            1. A. I troll idiots.

              B. Bailey through out random estimates based on numbers he pulled out of his ass any time he was called out for panic mongering.

              Bailey’s response?

              “I’m not panic mongering. I’m just being an honest reporter of facts. And my estimate is that 300,000 people can easily die. I’m not panic mongering.”

            2. Estimates by definition have to approximate reality. If your auto mechanic or roofer comes back with a bill that’s 30 percent higher than the estimate, you tell him to fuck off and eat the difference. Estimates of mortality that are orders of magnitude higher than reality aren’t good-faith estimates. They’re shameless fearmongering.

              1. Even if you’re feeling inclined to assume good faith, the most charitable way to characterize such wildly inaccurate projections is “wild-ass guesses.”

            3. Bailey fell for the 200k “leaked estimate” story.

              https://reason.com/2020/05/04/trump-administration-projects-200000-american-covid-19-deaths-by-june-1/

              He also constantly goes into comments and assumes worst infection rates of 20% of the population to reach his 400k numbers. Follow on link as an example.

          2. Yes, he did that, but that’s a far cry from insisting that everyone must be tested and traced or forced to stay home.
            Criticism is a lot less trollish if you address what he says rather than putting words into his mouth.
            If he did say anything like what Nards is accusing him of, I would like to know.

              1. That is a report on someone else’s proposal for testing and tracking.
                The strongest statement I see in there is that it “could work”. Not exactly an endorsement of the plan. Though he didn’t condemn it as I would have.

                1. Cry more Zeb.

                2. He shouldn’t even say that in my view.

                  Any type of tracking is froth with all kinds potential problems.

            1. Bailey was pushing testing hard. Look up his articles. Many commenters challenged him on the assertions.

              “Why would testing make a difference, if the virus is already widespread?”

              And Bailey never had a sensible answer. He kept vacillating between “everyone has it, therefore the fatality rate is going to be unthinkable” unless we test and isolate everyone in the country to “nobody has it, therefore the case fatality rate among those that do have is unthinkable” unless we test and isolate everyone in the country that has it.

              To complicate matters, he would just drop out random estimates when commenters insisted the virus is not all that deadly to make it seem like the virus was super deadly.

              I get that the situation is fluid but Bailey really hung his hat on the doomsday scenario hard, unless … somehow … testing.

          3. 200 to 300K isn’t absurd. The 2 million or 1 million numbers thrown out by the “experts” were always absurd.

            If the fatality rate is 0.6% (lots of evidence for that so far), and 20% of the people catch it (far more realistic than 60% or 100%), 300M x 0.2 x 0.006 = 360,000 dead. A 15% infection rate gives 270,000 dead.

            Still not worth destroying the economy, particularly since most of the dead weren’t working anyway (83% of those hospitalized in New York weren’t working.)

            1. “Not absurd” is not a standard we should rely upon. I happen to think being off by an order of magnitude is fairly absurd, especially when you don’t bother to take **any** actual epidemiological variables into account or provide a timeline for when these deaths are going to accumulate.

              Anybody can multiply. Straight mathematics is never going to provide the answer here because you have simplified the equation to such a degree that is, for all intents and purposes, worthless.

              1. We’re at 56,977 deaths as of today (and that includes within the count all the “probable” or “presumed” cases without laboratory testing). Deaths confirmed by laboratory results are likely to be significantly less.

                Bailey was pushing for 300K (timeline unknown) by using the straight math you supplied.

                So, either reality isn’t real or the math is wrong. Usually, it’s the math.

                As for absurdity, if you hired a contractor to renovate your house and he gave you an estimate of $56,000.00 or less, and then billed you for $300,000 when the work was completed, you would justifiably lose your shit. Not absurd? I suppose that’s a matter of perspective but it’s really, really, really fucking off.

        2. Oh shit now you did it Zeb is crying.

          1. Apparent even linking to past stories of reason’s stances (yes, editorial chooses of what stories to push is a form of stance) is too much.

            1. Poor guy he’s so fragile.

      2. For a guy who loves to brag about how he’s going to live forever while all is lesser beings are rotting away in our graves, Bailey sure seems to be an easily frightened little Nancy boy.

        1. I would think that the one would follow from the other. At least until immortality is achieved. If you plan on living forever, you have a lot to lose if you die.

    2. ” It is, however, sad that the disparate preliminary results of these studies are being selectively used by today’s culture war factions to confirm their already existing biases.”

      Oh fuck you and your high horse.

      The disparate preliminary results may also be due to disparate forms of testing. Frankly we do not even know the accuracy of the tests involved.

      Yeah, I supposed that makes me biased against questionable, if not outright worthless information.

      1. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-informs-public-about-possible-accuracy-concerns-abbott-id-now-point

        ” Specifically, the test may return false negative results.”

        No test is perfect. Exactly how imperfect is the question. Too imperfect and any results are worthless.

    3. Yes – we need to get back to work, especially the healthy people under age 50. This article left out something I think is important to know: the average age of the people who have died from and with COVID-19. Seems to me we should be taking a two pronged approach. 1 – stop younger healthy people from self-isolating – they need to get back to work, play, etc. and achieve herd immunity. 2 – be extra careful with those that have compromised immune systems, which mostly means older people. Throughout the world, the majority of deaths from COVID-19 have been older people.

  2. But at least we can be certain that Ron Bailey is a fraud

    1. Yes, your documentation and cites are excellent.

      1. On no you eat your own shit but think people care about your critiques.

  3. The researchers behind these studies should be applauded for undertaking these complicated studies during the chaos of the unfolding pandemic. So while it is frustrating, it is therefore not surprising that researchers have not yet nailed down just how deadly COVID-19 is.

    Serious question: Have researchers, undertaking complicated studies during the long period of calm preceding the unfolding pandemic, nailed down just how deadly, say, the common cold is?

    1. Nope. And I’m glad they didn’t.

      Researchers stay off of, and out of, my body.

      Thank you!
      Eliza

  4. If this was a random sample of residents, why did the researchers need to get volunteers from minority communities to accurately reflect state demographics? It seems there was something amiss with the random sampling, which calls into question the entire study.

    1. That’s an excellent question. If random, it ought to be representative. If not representative, how can it be random?

      1. Random within a carefully, pre-selected population based upon hard, social justice metrics.

        1. I would also question how broadly they pulled for their random sampling and what variables were used to extrapolate the data. If we are going to compare the study to the broader data set then it seems necessary to consider the population density of each person’s home town and how much each one has been isolating. Extrapolating the data from a mix of suburban and rural test subjects will not accurately depict the situation within cities and it would be easy to get poor results without splitting the data sets before calculating for the state as a whole. I think Bailey and other “science lovers” annoy me the most in how they don’t understand the math nor have the capacity to consider some obvious variables

          1. “I think Bailey and other “science lovers” annoy me the most in how they don’t understand the math nor have the capacity to consider some obvious variables.”

            Very few journalists took Calc. II in high school.

    2. 3600 people were random, then an additional 900 were added to match demographics

      1. If the 3600 were truly random, they wouldn’t have had to find 900 more to make them match demographics. There was a flaw in their random selection process.

        1. Nah, just too small of a sample. Random gets more likely to be representative the larger the sample is.

          1. Too small of a sample is a bad sample per se. The whole point of sampling is to have such a representative sample that results can be extrapolated. If 4,600 is a statistically valid sample size, something very bad happened with the allegedly random sample. The results should have been thrown out. Instead, they used those results. And if 4,600 isn’t statistically large enough to begin with, then the researchers don’t know what they’re doing. Regardless of the reason behind the discrepancy, the sample is not representative of the demographics. Therefore, it’s not representative of COVID statistics. This is statistical malpractice.

          2. “Nah, just too small of a sample”

            3600 is plenty for the stated CI.

        2. Indiana is overwhelmingly white. It’s not unreasonable to assume that they asked for volunteers and got predominantly (or even all) white people. Given racial disparities being reported from other areas, they probably thought that matching demographics was important.

          In reality, I would think that they would want to match test subjects to demographics based on urban areas vs rural areas, given that the risks for infection seem to be much higher for high population density areas. Not sure if they did this in the study or not. As Bailey mentions in the footnote, these studies need to be peer reviewed and should be considered somewhat questionable, even if their results are very interesting.

          1. They asked for volunteers *AFTER* they took a random sampling.

            Any selection bias was in their random sampling, only they are too vain to admit it.

            1. Asking for volunteers to be tested for a disease presents its own set of problematic selection biases.

            2. Nonsense. It’s a common issue. Any one with any experience in sampling understands that perfection is the enemy of good. More minorities simply declined to participate, imo.

              1. And that is exactly why this study is not valid. If that many randomly chosen people declined to participate, it’s no longer a valid sample. They adjusted the sample for minorities because not enough minorities agreed to be tested. And that’s an easy characteristic to analyze. But what other populations were under-represented? Healthy people who don’t give a shit, for example? And who might be over-represented? Those who have been around nursing homes, as an example? We don’t know. But if your “random” sample has a significant amount of declined-to-participate, it’s not random.

                1. More nonsense. The study is not completely invalidated due to a handful of non-participation. Again. You’re allowing perfection to be the enemy of good.

                  1. Tibbs said “a significant amount of declined-to-participate,” not “a handful.” You are allowing the shitty to be the enemy of the good.

                    1. This is what happens when people don’t understand an idiom. Give a hand to Woody Boyd over here.

        3. Why are you assuming covid is racist? Race should have no bearing on the sampling. Specific racial sampling may over sample other pertinent statistics like diet and obesity. But everything is racist, so they chose to derandomize the sample.

        4. They ventured out into the communities to get the random samples but only safe communities. To match the demographics they had the minorities come to them on a volunteer basis. It had something to do with losing all their equipment and money venturing into some communities.

        5. And who are those 100 extra study participants to bring the total to 4600?

    3. It was performed by folks at IU, so the veracity was already questionable…

      1. Why do you say that?

    4. I’m guessing there was a lower acceptance rate among the minority communities. You’re randomly selected, but not compelled to participate. my first thought.

      It’s not an unusual problem nor is the solution uncommon. Pretty standard.

      1. Maybe pretty standard, but then it’s not random if a material number of people, truly randomly selected, decline to participate. And that’s a problem with all the COVID studies. I’m not sure any have truly random samples.

        1. There’s no such thing as a truly random sample for something like this, since you cannot compel people to participate. Plus you are limited by location and access. Demographic matching is the best substitute, but yes, it can have some pitfalls. I doubt any are material here.

          1. Exactly. Mr. Tibbs is happy to throw his hands in the air, claim its impossible, and remain in the dark. Others will find a way to work around the problem

    5. “Random sampling” means random solicitation, but volunteer response rates are gonna be different based on how you go about it. This is pretty standard.

  5. Where is the mass die off of grocery store workers?

    http://www.ufcw.org/2020/04/28/workersmemorialday/

    WASHINGTON, D.C. – Today, United Food and Commercial Workers International Union (UFCW), America’s largest food and retail union with 1.3 million members in grocery stores, pharmacies, meatpacking plants, and other essential businesses, released a new update on the growing number of frontline workers who have been exposed, sick, and died from COVID-19.

    According to the UFCW’s internal reports, which were released on Workers Memorial Day, there have been at least 72 worker deaths and 5,322 workers directly impacted among UFCW members. This covers grocery, retail, pharmacy, meatpacking, and other essential industries and those directly impacted include workers who tested positive for COVID-19, missed work due to self-quarantine, are awaiting test results, or have been hospitalized, and/or are symptomatic.

    1. On the off chance it didn’t like the google doc reference

      Where is the mass die off of grocery store workers?

      Whole Foods [87K employees] does not have a current policy in place to inform the community. COO Jason Buechel addressed this issue to team members internally:

      “As a grocer, we are categorized as an essential business by the federal government and will continue to operate our stores to serve our communities. Because of the thorough nature of our daily enhanced cleaning procedures, we are not being advised to close our stores when notified of a confirmed diagnose of COVID-19.[1]”

      For inaccuracies, media inquiries, and other questions/concerns about this list, please contact wholeworkerwfm@gmail.com.

      TOTAL OF CONFIRMED CASES: 314

      TOTAL DEATHS*[2]: 3

      TOTAL STORES AFFECTED: 152 [out of 500+ stores in North America and the UK]

  6. How are we ever going to compare this virus to the “seasonal flu?”
    Based on my experiences with “seasonal flu, ” I doubt that even 50% of cases get reported to a doctor, let alone “the authorities.” Same with ChiComVirus – if you didn’t have symptoms, or had mild symptoms, you probably aren’t in the statistics. Can it be both “more deadly” while also causing fewer symptoms in more instances? This will take years to sort out, so let’s just crash the world economy until Top Men give us their final verdict?

    1. No, you’re mixing up things. Of the people actually tested, 2.8% had the virus. Extend this to the entire state, you get 186,000 infected for the entire state. Divide that by the 1067 in the entire state who allegedly died from the coronavirus. This has nothing to do with cases reported to the authorities or those without symptoms.

      It does matter how many of those 1067 actually died from coronavirus vs just had some of the symptoms and were not actually confirmed as coronavirus.

      1. He’s saying under-reporting is more likely for the seasonal flu, not the COVID numbers. The question is when they compared to seasonal flu death rates do they also account for unreported cases in a similar manner for seasonal flu.

        1. No he isn’t.

          Same with ChiComVirus – if you didn’t have symptoms, or had mild symptoms, you probably aren’t in the statistics.

          By the very definition of this study, they are in the statistics — the 3600 “random” and the 900 volunteers are by God absolutely in the statistics, and the 1067 dead are by God in the statistics.

          1. Except for the whole classifying any cause of death as covid related solely due to testing positive for covid even when the virus didnt contribute to a death. We dont do that for the flu.

  7. I don’t care if it is a hundred times worse than seasonal flu. Point five eight of one percent is an extraordinary low fatality rate. It is orders of magnitude lower than the original 2.5% or even higher that was used to sell the public to the lockdowns.

    Sorry but a virus that kills barely over one half of one percent of those it infects is not deadly enough to justify declaring a public emergency or doing any of the things we are doing. Life needs to return to normal. This virus needs to be allowed to spread so people can develop some immunity to it and it can die out on its own.

    1. If the original projections were 100Kish dead, instead of 1 to 2 million dead, would we (individuals, government) have made the same decisions? Here is the problem; the first model is the worst model, and it is always the worst model we use to make the biggest decisions. Modelers refine them over time and next year may have a pretty good one, and they will say “see how good our models are?”

      Local models, refine over time, and when they start to look close to reality use them to try to estimate NYC’s hospital bed needs for the next week using local data. None of this “we will model the world” bullshit for one size fits all top down centralized authority.

      Neil Ferguson had more power to destroy more lives than Jeff Bezos ever will, no matter how many more billions he gets. Fergie has blood on his hands, and no accountability for it.

      1. Why should Neil Ferguson be accountable? There should be some benefit to being one of the Top. Men.

        1. #guillotine

          It’s a humane method

      2. Neil Ferguson may be a hack, but no one forced politicians to listen to him. This is all on the political class.

        But it’s important to note that this is a global phenomenon, not just one in L.A. county. I have weekly meetings with contacts all over the globe and this subject comes up quite often.

        For instance Malta has been in lockdown and recently started to open back up. Their infection rate skyrocketed so they locked back down. Everyone is scared shitless about presiding over a runaway pandemic. Hard data seems difficult to come by, and interpretation of what we do have is very iffy, in my opinion.

      3. Yes, SIX TIMES GREATER than the flu! Alternative headline: yet another study indicates coronavirus IFR is one fourth of what was initially feared.

        Another important thing is that in addition to being much less deadly, all these results indicate that there is not an evenly distributed continuum from mild symptoms to death. That is, I think a big part of the initial panic was that while a couple-few percent of cases would die, a much larger percentage (even a majority) would require hospitalization or at least medical treatment and possibly survive only with these interventions. This has proved to not be the case. Most people don’t even realize they have it. In some cases, this is extremely severe or deadly, that much is true. But in the vast majority of cases, it’s not a big deal at all.

    2. That “one half of one percent” is misleading as well, given that it is far, far, far below that for anyone under the age of 60.

      Based on Ohio’s case numbers, assuming this same number of unidentified infections, we’re also at just over half of one percent. For cases under the age of 60, the death rate would be 0.06%, or one death for every 1,592 infections (under the age of 40 is 0.01%, or one death for every 7,613 infections).

      1. That “one half of one percent” is misleading as well, given that it is far, far, far below that for anyone under the age of 60.

        Are you implying that if we protected retirement homes instead of leaving them the only unprotected places, COVID would have been less deadly, and so how deadly it is isn’t consistent, it is based on the actions of idiot politicians?

        1. When Florida Man gets it more right than Top Men…

          1. Florida knows who pays the bills.

    3. Please learn what ‘orders of magnitude’ means.

    4. Weren’t you the guy who originally hypothesized “upwards of 50%” fatalities?

  8. How accurate is that “1067” deaths? Too many jurisdictions simply claim anyone with “symptoms” died of the coronavirus without any mention of comorbidities or any actual testing of the dead. From what I have read, I bet the true number of deaths if 1/2 or less.

    1. Not very accurate. A couple of weeks ago it came out that funeral directors in New York were complaining that literally every death certificate they were getting that didn’t involve an accidental death was listing “COVID” as the cause of death. The more COVID deaths you have, the more federal aid the state gets. That perverse incentive is no doubt driving the numbers artificially high. How much I don’t know but the numbers are certainly inflated.

      1. That’s the worst part of all this: we’e probably never going to know what the real numbers are, because the feds gave assholes like Cuomo billions of reasons to claim that everyone in New York State who dies is a coronavirus victim.

        In my opinion, it’s probably the single worst decision Trump has made in his presidency so far. A corrupt leftie will gladly steal every last penny you have to your name if you make it easy for him.

    2. So long story short, the denominator is Science!, but the numerator is just a politically motivated guess?

      1. Whichever way you flip the two, yes.

      2. Precisely.

        For 99% of people (and probably 99.5% of people), the virus does not present any risk of death, and likely not even a risk of serious health complications any different than the sequelae from flu or cold.

        For all of the panic mongering we have seen calling this a “deadly” or “killer” virus, we can safely call bullshit on it all.

        1. In my state, those over 80 are about 3% of the population, but account for 55% of the Covid fatalities.

  9. >>The researchers behind these studies should be applauded for undertaking these complicated studies during the chaos of the unfolding pandemic.

    seems more like a waste of time until it’s over and real numbers exist

    1. Doing that only leaves us with the models that predicts the sky is falling. Those are definitely a waste of time and causing harm. These at least are injecting something other than fantasy football into the mix…

  10. Until we have mass tests we will never know the real numbers and we will be suffering the consequences all over the world and people and companies in need

    Thank you
    https://cacavazamentosspmais.com.br/

  11. Tots fatality rate has been hovering around 0.5% for a while. But it makes too many assumptions based on bad data. Reality and observation says it’s lower and is about the same as the 1957 and 1968 pandemics. Basically we panicked for nothing and suicide and overdose rates will be considerably higher than they would have been. It’s shameful that the Democrats are still using this to get spending increases and as a political hammer. That is not cultural war or bias that is reality.

    1. And stress related health problems too. There is a pretty strong correlation with unemployment. So more strokes and heart attacks too.

  12. We need more compulsory testing, tracing and quarantines at the point of a gun. It’s the only path to freedom!

  13. We are seeing that the “infection rate” among populations seems to vary quite a bit in study by study. This is a good indicator that we don’t have a good model for random sampling.

    Think about it: what is more likely to drive infection- your ethinicity, or the density of housing where you live? Or your propensity to use mass transit?

    But the samples are trying to balance on demographics, not sampling from areas that have more or less density. If this city is one where most of the whites live in an urban down town, then under-sampling them by trying to get minorities will lower your infection rate.

    I’m not saying this study is wrong, per se, just that there is probably a reason why we get such varied results in study after study.

    This is also, btw, why I think the models were so off. They all assumed an R-naught rate that was more or less constant. But we seem to see that the R-naught is much more dependent on the environment than these models are accounting for.

    1. I don’t think any of these studies can be considered accurate to the nth degree. But all of them so far have shown the virus to have a fatality rate well below 1%. Even though none of them individually offer a definitive answer to the question, there have been enough of them that collectively I think it is pretty safe to say that this virus’s fatality rate is somewhere below 1% and certainly not the 2.5% originally feared. If it were that deadly, there would be some study that showed it to be so by now.

      1. There would be a study, or there would be grocery stores shutting down as their working, on-site, essential employees are dropping dead left and right.

      2. Just remember that the virus killed 100% of the people that died from the virus.

        1. Gretzky Theory of Epidemiology

      3. Half right.

        If the death rate were that high, there would be a study showing that the death rate is much higher.

      4. certainly not the 2.5% originally feared.

        Link to that then. From a credible source. You bullshit artists who want to pretend this is just the flu have been lying through your fucking teeth about everything. There may well be some study that was published in early Feb – based on a couple dozen cases from Wuhan in early January that says that. I know there was an early study that calc’d the RO at just under 4 – but even that was quickly revised with more data from the next couple weeks.

        You asswipes who are still stuck on stupid think that everyone else in still stuck in early Feb – when YOU people were denying everything. Well guess what. YOU are the ones who are stuck on stupid pretending this is early February. I haven’t seen a single credible study that EVER went much over 1% — with the big worst-case exception of ‘what happens when the hospitals are full and most of the sick are now outside the ability to access any medical attention’.

        1. https://towardsdatascience.com/why-the-coronavirus-mortality-rate-is-misleading-cc63f571b6a6

          Here is one example of literally thousands of the reported mortality rate being 2.5% or higher earlier this spring. Google is your friend you dishonest fucking retard.

        2. Link to that then. From a credible source

          Here you go, you fucking nasty little retard.

          ylward said that across China, about 80% of cases are mild, about 14% are severe, and about 6% become critically ill. The case fatality rate — the percentage of known infected people who die — is between 2% and 4% in Hubei province, and 0.7% in other parts of China, he said.

          The lower rate outside of Hubei is likely due to the draconian social distancing measures China has put in place to try to slow spread of the virus. Other parts of China have not had the huge explosion of cases seen in Hubei, Aylward said.

          A case fatality rate of between 2% to 4% would be catastrophic, if the virus spreads widely and infects a lot of people.

          https://www.statnews.com/2020/02/25/new-data-from-china-buttress-fears-about-high-coronavirus-fatality-rate-who-expert-says/

          That is from February 25th. The general consensus then was that the virus had a fatality rate of 2 to 4%. There are articles all over the place from that time frame saying that. Just because you are ignorant and dishonest and literally change what you think are the facts to fit your narrative doesn’t mean the rest of us do.

          You asswipes who are still stuck on stupid think that everyone else in still stuck in early Feb – when YOU people were denying everything.

          I never denied shit. I supported the lockdowns. I believed all of this crap. The difference is I am not a mouth breathing moron like you are and I am willing to change my opinion when the known facts change. You sadly are not.

          I haven’t seen a single credible study that EVER went much over 1% — with the big worst-case exception of ‘what happens when the hospitals are full and most of the sick are now outside the ability to access any medical attention’.

          That is because you are either a liar or a fucking imbecile who won’t look. The WHO was claiming 2.5% or higher fatality rate of this stuff clear up until April.

          Why don’t you just shut up. You are incapable of telling the truth or doing anything but lying and spewing bullshit.

          1. That is the CASE fatality rate. Fatality rate / CONFIRMED CASES. The US is currently running a 6% case fatality rate. The only countries that have more than 10,000 cases and less than 2.5% CFR and that aren’t obviously lying are: South Korea, Singapore, Israel. Period.

            Pakistan, Russia, Saudi Arabia, South Africa, Chile and a couple other SAY they have a lower CFR but most likely they are simply lying.

            So a 2.5% CFR is in fact low and you are, at best, trying to conflate apples and oranges in order to advance a political interpretation to lie with data like – eg – those countries that ARE lying.

            No one has ever said that all the infected have been confirmed as cases. Everyone understands that many are asymptomatic. Which is why everyone has been waiting for the serological/antibody testing to confirm the actual fatality rate. But I repeat – SHOW ME A FUCKING CREDIBLE LINK that projects that number as 2.5%. For planet Earth a 2.5% actual fatality rate would project as 100-200 MILLION fatalities – with roughly 5-8 million in the US.

            1. How does it feel to know you lit yourself on fire for nothing bitch?

            2. JFree
              May.14.2020 at 2:34 pm
              “That is the CASE fatality rate…”

              Fuck you with a running, rusty chain saw, you cowardly lefty piece of shit. Stuff your PANIC!! flag up your ass, stick first and sit on it.

        3. JFree
          May.14.2020 at 1:17 pm
          “Link to that then…”

          Fuck you with a running, rusty chain saw, you cowardly lefty piece of shit. Stuff your PANIC!! flag up your ass, stick first and sit on it.

    2. No model that I’m aware of assumes RO is constant. What they assume is what people who look at the models for the purpose of poo-flinging don’t pay attention to. That they can’t predict human behaviors/interactions and stick those into a model. So they have to take the behaviors as they exist at that model’s time/place as a given – and make some of those assumptions explicit if they can.

      And it is then up to people to look at the DIFFERENT models – working under different behaviors that existed – to figure out what elements are specific to that particular model and what elements may be more universal.

      1. models.

      2. No model that I’m aware of assumes RO is constant. What they assume is what people who look at the models for the purpose of poo-flinging don’t pay attention to. That they can’t predict human behaviors/interactions and stick those into a model. So they have to take the behaviors as they exist at that model’s time/place as a given – and make some of those assumptions explicit if they can.

        They can’t predict human behavior. That means they can’t accurately model the spread of the virus. So they are worthless. Moreover, this entire sentence is one giant example of a statement that can’t be falsified. If the model is wrong, you write it off to people’s behaviors. If the model is right, you claim it is right. Either way, no model can ever be shown to be wrong by your logic.

        My God you are a dangerous idiot.

        1. No they are not worthless. They model what they can. What they know they know and what they know they don’t know but must assume. Hopefully they are honest about that – and that they at least try to state what isn’t known to them. But in truth that is always up to those who interpret the model not those who create it.

          It is people like you – on the left too – who take that as some fucking prediction by Nostradamus.

          1. Then why were you making a fool of yourself screeching gloom and doom only to be so fucking wrong bitch?

          2. Not quite certain what you are saying about Nostradamus. Are you saying his predictions were accurate? Because, from what I can tell the models were no better at predicting anything than Nostradamus was.

            1. The valid purpose of a model is a process one not a goal one. To better understand the processes of what is happening and how changes affect outcomes – and incorporate that into improving it.

              Sometimes, as in this case, that is all you freaking have to project possible outcomes because the events are one-time and haven’t happened yet. At best what we have is different models in different places. But the events are happening globally all at once.

              This isn’t a game of ‘who built the best model on day one – now let’s all go home’. And even if it were, it wouldn’t do anyone any good because that assessment can’t possibly happen for a year or two and hence is completely fucking useless to figure out what to do next in the real world. That’s the Nostradamus type thing. Where the model isn’t a model but is an oracle into a fatalistic unalterable future.

              There is a natural tendency to pre-judge this stuff this way. You who view this as ‘just the flu’ have THAT model in your head. Not because that is an accurate model but because it delivers the outcome you prefer. If anyone who knew anything also thought this was ‘just the flu’, then presumably they would have fleshed out that model for this virus – and you might actually have valid arguments on your side. But that ain’t the case. So all you are left with is trying to pick apart all the models that don’t lead to the only thing you want all along – which is the outcome that leads to or rationalizes ‘no need to do anything that we haven’t already been doing for decades’ (apart from blaming China – which isn’t a model thing but certainly fits the politics).

              In truth, I suspect this is just the futile conservative mindset that Hayek talked about when he said he wasn’t a conservative. But when ‘the outcome’ intersects with what even many libertarians might argue is a legitimate function of govt (public health), well then you all throw the mantle of ‘libertarian’ on yourselves to argue that everyone arguing to do anything (or even the mere possibility of the wisdom of doing anything) is just a statist progtard commie. Y’all are useless.

              1. We knew the models were crap before this even started. Oxford statitacians in 2015 demonstrated that epidemiology models had no correlation to reality and always vastly overestimated actual infections and Lethality.
                And I never said it was just the flu but that we were overreacting to something that may not be anymore deadly than the flu.
                Also, tell us again about exponential growth of infections.
                I did ridicule you for your over the top, the world is ending pants shitting. I also ridiculed panicking about anything we had so little information about. And I ridiculed you for comparing us to Italy. And for believing models that, even by February, were demonstrating they were magnitudes of order off. Yet you continued to defend these models well past the point where it became obvious that they were wrong.
                Relying on models which are known (epidemiology models as demonstrated by past pandemics and the Oxford study) as you decision making tool is asinine. Try to gas light all you want, because everyone sees it for what it is.
                And who stated public health is a libertarian acceptable function of government? I know you did and we’re roundly ridiculed for it. But who else?

                1. And I never said it was just the flu but that we were overreacting to something that may not be anymore deadly than the flu.

                  And of course like all the other ‘it’s just the flu folks’, you can’t even admit that the itty bitty six weeks of the first wave has already proven you wrong on that little outcome.

                  If you want to make a case that we are overreacting based on the characteristics of the disease itself, then creating a model is EXACTLY what you do. Course that would require that you plug in something more than class ThisIsJusttheFluLetsDoNothing {
                  public static void main(String[] args) {
                  System.out.println(“This Is Just the Flu! Let’s Do Nothing!”);
                  }
                  }

                  If you want to make a case that we are overreacting because all reaction whatsoever is overreaction, then you certainly don’t need a model of anything. Nor however need anyone pay the slightest attention to anything you think you might have to offer because in fact you offer no more than a dead person or a line of Hello World code.

                  And please spare me that you know anything about epidemiology. Nor do I even believe your ‘medic’ handle anymore. You are spouting politics because that is the tribe you belong to.

              2. I am sorry but you don’t even know the difference between exponential, parabolic or asymptotic. Because outbreaks grow parabolic or asymptotic not exponentially. You always eventually run out of susceptible hosts, ergo it can’t be exponential.
                And you don’t seem to understand how diseases spread, as evidenced by your stupid remark yesterday about the plague and the illness induced deaths of American Indians being evidence that infectious diseases with high mortalities don’t always burn out quickly. Those were a series of localized outbreaks that occurred over an extended period of time. One location became infected. The disease killed a large number and died out quickly, rarely to return for long periods of time. However, when the disease carrying vectors came into contact with a new, susceptible host, in a new location, you would have another outbreak that followed the same pattern. In the case of the plague it traveled at the speed of commerce for the time, because the disease carrying vector, fleas, were not susceptible and they traveled on the merchant trains and shipping.

                1. soldiermedic, I tend to read your posts whenever I come across them on a variety of topics. I have to say, you are one intelligent motherf***er.

                2. To be fair, -X^2 + Y is exponential, it justs means we’re going to see a rapid decrease in the number of nonexistent people that don’t have it.

          3. All model are wrong. Some are useful. – George Box

            Early models built on bad and unknowing assumptions are not useful.

            You’re a fucking idiot.

        2. Not only that but the IHME model and the one the US assumed we would social distance even in the high projections. Jfree is just trying to revise his last 3 months of being wrong.

          1. Maybe he should change his name to “gaalighter”?

          2. Just a few weeks ago when the IHME revised their projected ‘until Aug’ death toll from 80k to 60k, your ilk were jumping up and down saying – see they were wrong. They should be shot. It will actually end up being lower than 60k.

            To your credit (or your sockpuppetry), I can’t see any posts by you on that thread. so maybe you missed it – but a whole ton of the usual suspects didn’t.

            I was the one saying – this is peak optimism about the death toll. Even I however didn’t think it would get back up to 80k for the first wave. Silly me – I still can’t really fathom how utterly incompetent our public health functions are or how fucking little we even give a shit about that. Course I was blasted for saying the models are now going to start going up.

            Roll forward a few weeks. We now have 80k already dead. The IHME is now projecting 140k or so. And you clowns are still pretending you were right all along.

            1. Yes, they lowered it to 60,000 and then raised it to 80,000 and then to 140,000. They still have been incorrect on deaths, hospitalizations, ICU bed usage etc when compared to the actual data. So the question is why you believe they are right now? Especially as reported deaths in the US and now reported new infections are both going down? Oh yeah second wave. We could have 140,000.
              And as for you not believing it wouldn’t get to 80,000 in the first wave, bull fucking shit. Stop gaslighting asshat.

              1. So the question is why you believe they are right now?

                For fuck’s sake. Stop obsessing blindly about the output of a model. It isn’t designed to create the desired widget for you or me. What is important is the inputs and the processes. The inputs are improving over time (as they always do) – and the processes are finally incorporating some of the more obvious things they missed last time (like a plateau not just an up-down phase).

                Oh yeah second wave. We could have 140,000.

                In your dreams. The second wave is gonna hit when sniffles season starts this fall and everyone has moved back inside. Most likely right around the election which is interesting for a non-viral consequence (and I suspect that is why you Trump-bots are really objecting here). And likely we will have tired of the mask stuff by then. Oh- and unlike the easy stuff of first wave – we won’t have three months waiting for the virus to make its way halfway around the world in onesies and twosies from Wuhan. It’s already here now. Just like I said in early February.

                And as for you not believing it wouldn’t get to 80,000 in the first wave, bull fucking shit.

                My specific comment from that thread: It’s probably not going to get back to the 81,000 projected before the first wave really started – but 60,145 is peak optimism. No doubt however that 60,145 will be repeated and repeated to reinforce optimism – until the actual number gets higher than that – in which event there will be a ‘these models all suck’ meme again.

                1. That is from March and you just claimed you were stating it was going to kill 250,000 to 1 million. Admit your faith in the models, which were biased right because of bad assumptions as they always are (which is my point) was misplaced.

                  1. You can’t even fucking read can you. That thread I just linked to is APRIL. Not March. Every fucking word out of your mouth is either a lie or stupid

                    Yes my initial estimate was in early February and I would welcome you finding that and pointing out specific errors. Otherwise – fuck off. You’re just like a Sevo but a different cut-n-paste

                    1. Yes, I misspoke about the month in your citation but you were, as everyone knows, toeing the millions are going to die line. As for saying every line out of my mouth is a lie or stupid who keeps calling it exponential and who completely fucked up trying to state the plague and the infectious diseases deaths in Amerindians was proof that deadly infections don’t die out early? It wasn’t me. You have been wrong from almost the get go. And this is your latest version of gaslighting.

                    2. And, yes I made a simple mistake so I must be wrong about everything. The pure stupidity of that logic is breathtaking. You keep calling it exponential. You keep trying to deny that you defended the initial estimates. You keep trying to defend modeling that was known never to be realistic. Epidemiological modeling has never been accurate because it is way to complex a system to model. It isn’t a question of which model is accurate if none of them have ever been able to even come close to accurately predicting the outcome. Statacians, and a number of epidemiologist, were stating that exact thing back in January. Which is what I was saying back in January and February. Your response was always chicken little the sky is falling, bring out your dead pants shitting and appeals to authority. Your entire schtick the last 48 hours is blatant attempt at memory holing.

                2. This whole thing, including your sky is falling routine in February, was a clusterfuck from the start. Anyone who knows anything about the accuracy of epidemiology modeling was aware of that back on February and we were saying that.

                3. Holy. Fucking. Shit. Are. You. Dumb.

                  The outputs are not improving over time. They are tuning them to recent trends you utter dumbass.

      3. Holy fucking shit. I literally argued with you in an early thread where you fucking claimed foe every new virus eventually 100% of the population got it. You kept claiming it was always exponential until full infection. Go fuck yourself chicken little.

        1. Hell just yesterday he was still claiming it was exponential. He doesn’t seem to know what that word means.

          1. And because he loves revisionism so much here is the quote defending his stance as being correct all along.
            “… exponential growth IN EARLY FEBRUARY when you clowns were dismissing it all because there were only 10 cases or something”

            1. I had an argument last month with a proggie that genuinely believed that not only would infections rise exponentially, indefinitely … but that DEATHS would also increase exponentially …. indefinitely, every two weeks, unless we locked down … in which case we could slow the indefinite, exponential growth to periods of four, instead of two, weeks.

              I told him if that was the case, the entire United States would be wiped out several hundred thousand times over by Christmas.

              He screeched and then never spoke to me again.

              1. 8 weeks ago Gavin Newsome said we’d have 25 million cases in California if we didn’t lock down. We’re just now about to hit 75,000, despite most people regularly going out for groceries, take-out, browsing the aisles at Home Depot or working “essential” jobs.

                If someone had asked him how many cases we were due for in 10-12 weeks he very well may have given us a number that exceeded the state’s population.

            2. Anyone who was saying growth was exponential was either lying or a useful idiot. At worse it would be asymptotic. Mainly because at some point you will always run out of susceptible hosts. Parabolic is generally more likely.

              1. Might want to look up some words in a math textbook.

                “Anyone who was saying growth was exponential was either lying or a useful idiot.”

                Growth rate was exponential at first. Feed the data before lockdowns into a spreadsheet. Best fit is very close to exponential.

                “At worse it would be asymptotic. Mainly because at some point you will always run out of susceptible hosts.”

                I think the word you are looking for is “logistic,” though I’m uncertain given your vague descriptions. A logistic curve is typically a good model for the situation you describe, where growth is roughly exponential at the beginning, the exponentially approaches a maximum (asymptote).

                “Parabolic is generally more likely.”

                See, there you give yourself away. Parabolic growth also assumes unlimited “susceptible hosts” — it just grows more slowly than an exponential curve. But it will also eventually infect everyone in that scenario. So, the one you say is “more likely” actually contradicts your earlier statements.

                1. “Growth rate was exponential at first. Feed the data before lockdowns into a spreadsheet. Best fit is very close to exponential.”

                  No, it wasn’t exponential. For fuck sake. It is multivariate. It is always multivariate since the population is constantly changing. You don’t get to take a small segment slice of data and claim victory because it fits somewhat closely to a curve, then dismiss the rest.

                  We know how these curves look because viruses have always been around. Long term infections always look parabolic. This is because of the changing population metrics.

                  Saying a curve is exponential because a small area of a curve fits exponentially is fucking retarded.

                  1. //Saying a curve is exponential because a small area of a curve fits exponentially is fucking retarded.//

                    Thank you.

                    For some reason, the panic merchants just cannot understand this concept.

                    “See! It was exponential this one week! THEREFORE ….”

                    Mind numbing.

                2. Parabolic has both an upslope and a downslope you can have both positive and negative parabolas one is U shaped up and the other u shaped down. Asymptotic implies there is an upper limit. An asymptote is a line that approaches a curve but never reaches it, i.e. an upper limit. This is common in population biology, chemical reactions with a limiting reagent etc. So, please correct me again. As for it growing exponentially, yes the initial slope may be exponential. But that is not ever going to be a steady state.

                  1. Furthermore, the slope of the asymptote can be positive, negative or flat. Flat or near flat is the most likely worse case scenario.

              2. You’re an idiot. Exponential growth does not require a constant exponent. And in this case, that exponent is variable – roughly a function of the RO of the virus at the particular point in time.

                And anyone who somehow thinks exponential requires growth to mathematical infinity so it can kill people an infinite number of times. Well – that is truly as stupid as fuck.

                Stop pretending you know what you’re talking about. Like you would have understood an initial sigmoidal RO growth lagged by a reverse sigmoidal for antibodies or other changes to RO. Repeated periodically until either 100% exposure or vaccine (whichever comes first) driven by the hosts (human) cycles from inattention to attention to inattention. I’m sure that’s exactly the explanation that convinces you hmm this isn’t just the flu.

                It must have been the word exponential that threw you off and sent you into ‘I’m a stupid fucking Trumpbot’ DeRpland. Cuz it’s not like you were already there was it.

                1. If the exponent is changing based on a dependent reliance on the inputs, it is not exponential you fucking retard. It is a multivariate analysis.

                  https://www.sciencedirect.com/topics/medicine-and-dentistry/multivariate-analysis

                  Saying it is exponential proves you maxed out at intro to calculus at best.

                  1. In HS calculus. In college, topology

                    1. Topology? Then we should start referring to your posts as “genus 50”, because they’re full of holes…

                2. No, exponential means the exponent remains constant. Jesse just stated what you are describing is a multivariate growth.

                3. And when you can’t even understand why you are wrong you always revert to the (in my case inaccurate) charge that the person correcting you must be a Trumpbot.

                4. //Exponential growth does not require a constant exponent.//

                  Summer school much?

            3. By the way…

              I bet if you ran the Ferguson or IHME models for an expanded period both would extrapolate to full population coverage and then some. I guarantee those systems lack basic stability checks in their line progressions.

              1. Thought Ra’s pointed out in a link in the Morning Links a few days ago that Ferguson’s cleaned up code failed the simplest of replicability trials?

                As to exponential v parabolic growth, I thought epidemic case numbers did grow near exponentially, until the population of infected was 1/R0 of the total population. At which point growth failed off. If that is true, is it just a simplifying assumption? (Not like there’s a shortage of those when life science majors have to start doing math.)

                But LOL at estimates of 50% and up of the population getting the bug. Not when we had historical data suggesting only something like 20 percent or less caught the Spanish Flu. OTOH, what is the prevalence of something like chicken pox exposure, and is the difference that people actively try to catch the disease when younger?

                1. That means it isn’t exponential. Certain areas of the curve can be represented as an exponential for very short periods of the graph, but the overall growth is not exponential. There is a dependency of the output on the input. It is a multivariate analysis that can be somewhat controlled by linear algebraic system representation. It is not an exponential curve. It never can be because the population sample has a set limit.

                  Exponential estimation of the curve is such a simplification of reality as to be utterly useless in pandemic modeling.

                  1. //It is not an exponential curve. It never can be because the population sample has a set limit.

                    Exponential estimation of the curve is such a simplification of reality as to be utterly useless in pandemic modeling.//

                    Again, thank you. I’ve tried drawing graphs for people, but still nothing.

          2. He doesn’t understand that it is a multi, but dependent, variable problem where overtime the inputs modify the equation. It is closer to a liberal algebra problem than it is a simple exponential problem. But the idiot read R0 at one point and assumed the equation was static. Not dealing r0 was depending on the current population of infected, not infected, and immune. The population is an output of the system so it changes over time.

    3. Actually, I see the opposite. While the infection rates vary, they track pretty consistently as 10-20x the confirmed rate. That indicates to me that the serological studies are likely valid (specificity concerns still exist, but researchers can usually account for this), and just that different locations have different infection rates… as you would expect.

      “They all assumed an R-naught rate that was more or less constant.”

      Indeed. As recent data has shown, people started staying at home long before they were ordered to. You see this in more recent historical pandemics, too (at least those after germ theory was common), where the actual total infection rate ends up no where near the herd immunity rate produced by R0. But the media and government like to pretend we are all lemmings who will just go about our business as usual in the face of Armageddon unless ordered not to (and naturally they find a few dozen reckless people and present them as representative, which everyone else likes to believe because it makes them feel special and responsible).

  14. Nobody has the virus. Everyone that does have it, dies. Everyone that dies, could have been saved if only we tested for the virus. When we tested, nobody had it. Everyone that had it, died. They could have been saved, however, if we tested ….

    Circular logic is fantastic for keeping the death rate as high as possible, at all costs, by simultaneously believing the virus is super transmittable, but hasn’t been transmitted to anyone, except that it killed everyone to whom it has been transmitted, and will keep killing anyone, and being transmitted, unless we close all business forever.

    The mental gymnastics at play are a wonder to behold.

  15. Unfortunately until the specificity and sensitivity of the antibody/serology tests is well over 98% (on the MINIMUM side – not the marketing bullshit of 100%), we are going to tend to overestimate the exposure and underestimate the IFR. It’s getting closer to real – and I like that Indiana is doing this in phases to follow the same people over time.

    What I’d really like to see though is a more comprehensive breakdown by age and occupation. The epicenter outbreaks to date have been concentrated in nursing/etc homes and institutions. Which would lead one to expect that the survivors there are actually closer to herd immunity (or at least much higher antibody prevalence) than the rest of the population. Course it’s the worst possible population to test for herd immunity – but it’s not like we’ve done any competent public health work and it is what it is.

    Likewise with the under-20’s. They are clearly the missing barking dog demographic from the confirmed case info. Have they been exposed at the same rate as the older? Are they just almost universally asymptomatic (the only conclusion I can think of of top of head if they have been equally exposed) or is there some other impact of the disease that is less ‘requires immediate hospitalization’ but maybe more ‘long-term impact’. Again like above – not sure the info would be actionable because we pretty clearly don’t do public health in this country.

    1. Unfortunately until the specificity and sensitivity of the antibody/serology tests is well over 98% (on the MINIMUM side – not the marketing bullshit of 100%), we are going to tend to overestimate the exposure and underestimate the IFR. It’s getting closer to real – and I like that Indiana is doing this in phases to follow the same people over time.

      Sure we are. But there is a lot of numbers below 98%. Let’s say it is 80%. That would mean it is over estimating the exposures by a quarter. Okay. That would give it a fatality rate of about .07 rather than .058. Still not even close to being deadly enough to justify the response. And these tests while not at 98% are most certainly better than 80%.

      You put this same bullshit talking point out last week. And I explained why it was bullshit then. You just won’t fucking listen. You are just a fucking idiot. You make up your mind about something, cherry pick a few things to support it and then start spewing bullshit. Once in a great while you are right about something by dumb luck. Otherwise, you are dangerous idiot on every subject. It is terrifying how stupid and hard headed you are.

      1. No that is NOT what 80% means. If the ACTUAL ‘infected already’ rate is 2%, then a 98% sensitivity/specificity test will be off by roughly 50% with a ton of false positives and false negatives. An 80% test will produce nothing but false noise – close to 90% inaccurate.

        An 80% test will only be ‘off’ by 20% once/if the entire population is ‘infected already’. It is the big problem with these tests early on.

        1. No one cares what you think bitch.

        2. You can’t calculate that without knowing the rate of both false positives and false negatives. They are not inherently the same as the overall accuracy.

          1. The sensitivity and specificity tell you the rate of false positives and false negatives. What you don’t know is the ACTUAL infection rate in the population that is now being tested. Only what the actual infection rate was in the population where the sensitivty and specificity were determined.

            1. Fuck you with a running, rusty chain saw, you cowardly piece of lefty shit. Stuff your PANIC!! flag up your ass, stick first and sit on it.

            2. And because our years are bad, we should all cost in great in our hovels until three entire nation starves. Then China can simply come in and take over! No shots fired!

    2. Researchers know that and provide a confidence range. The serological tests in several of the studies I’ve looked at (not this one, I can’t find info on it yet) had a specificity of 99.5% or so, which makes the results significant. At least that’s what the researchers claimed.

      Regardless, the results between serological studies as well as broader-population viral testing show much the same everywhere. Infections are 10-20x the “confirmed” rate, and the actual IFR around 0.4% to 0.6%.

  16. Since 1,067 residents had cumulatively died of the disease by May 1, the researchers calculated the “infection-fatality rate for the novel coronavirus in Indiana to be 0.58 percent, making it nearly six times more deadly than the seasonal flu.”

    Um, no. 1,067 people who died tested positive. Doesn’t mean that the virus was the cause of death. If someone dies in a car accident and tests positive, then the CDC requires that it be listed as a virus-related death.

    So the numbers are meaningless bullshit.

    1. People keep saying this, but where on the CDC website is such a requirement listed?

      1. I heard it on a radio interview with the director of my state’s CDC. The question was if the methodology was different between states, and the guy stressed that all states are following federal guidelines. When pressed on what those guidelines actually are he reluctantly admitted that anyone who tests positive and dies will be counted as a virus-related death, regardless of the actual cause of death.

      2. came out of Birx’ mouth on live tv

      3. Part of the problem too is that the CDC isn’t the only agency with a thumb in the pie here. CDC has said, officially, they would count cases even without a positive test for COVID. DHHS, who’s paying the bills, likely won’t pay out without one and may or may not attempt to reconcile with whatever the CDC reports.

      4. I’ve literally posted this nonsense multiple times…. from the CDC.

        “In cases where a definite diagnosis of COVID cannot be made but is suspected or likely (e.g. the circumstances are compelling with a reasonable degree of certainty) it is acceptable to report COVID-19 on a death certificate as ‘probable’ or ‘presumed.'”

      5. By the way, the CDC provides 2 death counts for covid. Confirmed and related. The related number is the one seen in the news. The confirmed was about 30% less last time I checked. Confirmed meant actually tested and died of pneumonia like symptoms.

        1. “Confirmed” deaths, which still include “probable” or “presumed” deaths (that is, no testing), are at approximately 57,000 at the moment.

          https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm

          Even fudging the numbers, they are really struggling to make something catastrophic out of this – that is, something worse than middle of the road flu season. Considering, also, that somewhere near half of all the COVID deaths are due to the virus running through nursing homes, you can see fairly easily that this virus is neither “deadly” nor a “killer.”

          It’s all bullshit.

  17. Coronavirus Has Infected 2.8 Percent of Hoosiers, Says New Study

    That’s what Sheb Wooley died from in the movie.

    1. Look mister there’s two kinds of dumb …

      1. My favorite sports movie.

        1. I have a buddy raised in Iran who asked me for 10 movies from the 80s. Trying to avoid the Hughes stereotypical movies he can figure those out on his own.

          Hoosiers on list.

          1. Which Beverly Hills Cop are you suggesting?

            1. lol also 48 Hours “I’m sorry, Luther that looked very painful.”

          2. So (in the order i remembered them)… Empire Strikes Back, Back to the Future (and maybe II and III), Space Balls, Indiana Jones (Raiders at least), Die Hard, Heathers, Breakfast Club, Ferris Buhler’s Day Off, Dirty Dancing, Princess Bride, Blade Runner, Ghostbusters, Goonies, E.T., Beetlejuice, Short Circuit, The Color Purple, Alien (and Aliens), Terminator, Labyrinth, Clue, Fast Times at Ridgemont High, Karate Kid, Caddy Shack, Top Gun, Say Anything, Who Framed Roger Rabbit, … and probably many more…

            The 80s was a great decade for movies.

            But how does Hoosiers even make the list?

            1. Hoosiers would be on my list. Also, Labyrinth, Back to the Future, Red Dawn, The Muppet Movie, Princess Bride, Time Bandits, Gremlins, Fast Times, The Shining.

              An hour from now, that would be a completely different list.

              1. Dead Poets Society, Into The Night,….

              2. Coming to America
                The Thing

                1. Oh, and Revenge of the Ned’s
                  The only movie I know of that includes successful rape conversion

            2. You forgot Trading Places.

              1. i mean … *I* didn’t forget Trading Places

                Billy Ray Valentine, Capricorn.

              2. That list could probably be twice as long, but 5 minutes was all i was willing to spend thinking about it.

              3. Moscow On The Hudson
                Johnny Dangerously
                Meatballs

                1. it’s a .88 magnum. it shoots through schools.

                  can’t believe i forgot Johnny Dangerously der

            3. Red Dawn, Die Hard (because you have to have one shoot them up action flick with Willis, Schwarzenegger, Stallone or Norris and I chose this one because Alan Rickman was in it), The Last Starfighter (one of the most underrated Sci-Fi movies ever), Young Guns, Short Circuit, Gremlins, Top Gun, Field of Dreams, Big (because you have to have one Tom Hanks movie), Romancing the Stone (because Michael Douglas, Danny Devito, Kathleen Turner).
              Hell I don’t have a Kurt Russell movie… Maybe I should change Die Hard to Tango and Cash, because than I could cover both Stallone and Russell. But Escape from New York should be on the list. Hell for that matter if we are going to add dystopian sci fi, we could also add The Running Man or Total Recall. And leaving out John Hughes really eliminates a lot of the pop culture of the 1980s. I was going to put Weird Science but than I remembered it was a Hughes movie also.
              If we are going to do series lien Star Wars (and agree Empire was the best by far) I think an argument for Wrath of Khan and or The Voyage Home could be made, as well. With The Voyage Home you get the added benefit of it actually being set in 1980s USA.

              1. Shit rereading some of the other lists. Yes to Back to the Future and yes to Aliens, and yes to Spaceballs. Actually there isn’t a movie yet listed that I disagree with. Most definitely The Princess Bride. Is there a better movie to quote than The Princess Bride? There is also a lot of fantasy movies of differing degrees of quality. I see Labyrinth mentioned, but there are others I could argue for their inclusions.

                1. How about Three men and a baby? Or for that matter Police Academy? (I thought of Police Academy because my argument for Three Men and a Baby is Tom Selleck, Steve Guttenberg and Ted Danson which made me think of Steve Guttenberg’s other famous role).

              2. >>The Last Starfighter (one of the most underrated Sci-Fi movies ever)

                yes. yes it was. and he just watched Weird Science but the others probably not. thanks!

                1. I would recommend to your friend that he watch Robot Chicken and Family Guy and watch any 80s movie or television show referenced. LOL.

                  1. Futurama would also be good for reference suggestions.

                2. Also if he isn’t a diehard Trekkie I would not let him start with any of the odd numbered movies.

                  1. II Wrath of Khan is the greatest submarine battle ever.

                    1. It was. Also, to be noted Roddenberry always envisioned the episode Balance of Terror as a destroyer vs submarine battle from WWII.

                    2. And the interesting thing is Roddenberry himself was Army Air Corp and not naval.

              3. I thought of Tango and Cash, but thought it was early 90s?

              4. Running Man and Total Recall for sure
                Also Road Warrior

                1. i sent him a conglomerate list of all this ^^^. thanks everybody

            4. Gorky Park
              Full Metal Jacket (“F-U-C…K-E-D…A-G-A-I-N”)
              Escape from New York
              Heartbreak Ridge
              The Naked Gun (“Nice beaver!” “Thanks, I just had it stuffed.”)
              Platoon
              Scanners (I think this was early 80s)
              Body Double
              Highlander (“There can be only one!”…good Highlander movie)

        2. I grew up in the same county as the town that stood in for Hickory in the movie. They actually got basketball gym scoreboards that were period-correct from area collectors to use in the movie– I remember a newspaper article from the time about them.

          1. very cool. and thanks for the lists everyone i’ll have to hit him w/all of them.

          2. I grew up in the same county as the town that stood in for Hickory in the movie.

            Weird. If we didn’t run into each other at the Mr. Gattis in Crawfordsville or Turkey Run, we almost certainly played against each other in some HS sport.

            The “town meeting” was held at the church in Elizaville where our township’s 4-H meetings were held. Also, took a few basketball programs at the Memorial Gym in Lebanon where the Regional game is set in the movie.

            Kinda surprised they had to go to collectors, I must’ve played in at least a handful of gyms that were still period specific; right down to the underground locker/boiler rooms, paneled bleachers, and 50+ bulb scoreboards.

    2. Cletus? I assumed Shooter was the one who died. Both reasonable candidates for ‘Complications from COVID’ toe tags, though.

  18. Where Does Brian Kemp Go For an Apology?
    The IHME model has revised down significantly the expected cases in Georgia and Democrats and the press are moving goal posts.
    https://ewerickson.substack.com/p/where-does-brian-kemp-go-for-an-apology

    The IHME model is the most widely cited and relied upon model for COVID-19. The White House and Georgia’s Governor rely on it. On May 12, the IHME model predicted Georgia would still have hundreds of daily new cases into August and would have 1,783 daily new cases on June 12, 2020.

    Yesterday, the model updated and the update was significant. Georgia is now expected to have no cases of the virus by August and only 367 new daily cases on June 12.

    1. “On May 12, the IHME model predicted Georgia would still have hundreds of daily new cases into August and would have 1,783 daily new cases on June 12, 2020. Yesterday, the model updated and the update was significant. Georgia is now expected to have no cases of the virus by August and only 367 new daily cases on June 12.”

      So it took two days to figure out that the earlier model was off by between 500% and infinity. The models are getting better /sarc.

  19. https://twitter.com/JordanSchachtel/status/1260989286326972419

    NYC went into lockdown on 3/22. Record high diagnosis date was 4/6. The lockdown caused a massive, avoidable wave of intra-family transfer. Couple that with nursing home policy that added 1000s of excess deaths, & u have the worst COVID policy initiatives in USA by a wide margin.

  20. Philly’s health czar had both good and bad news today. Bad news was death toll topped 1,000. Good news: the “model” showed the toll would have been more than 6,000 without the strict cower in place orders of Gauleiter von Wolf and Oberfuhrer Kenny. These smucks will twist their arms out of their sockets during the next campaign bragging about results that are impossible to quantify.

  21. Of course, given the likely error bars, 0.58 percent IFR is probably statistically indistinguishable from the 0.5% IFR for the ’68 pandemic flu. You know, the last major pandemic, in which we didn’t close anything?

    1. Hey now. Jfree the idiot said not to compare this to the flu.

    2. Well, Boehm assured us yesterday that SARS-COV-2 was literally “the biggest disease threat America has faced IN A CENTURY.”

      https://reason.com/2020/05/13/mission-creep-and-wasteful-spending-left-the-cdc-unprepared-for-an-actual-public-health-crisis/

      That’s right …. A CENTURY.

      Going all the way back to 1919 … we’ve never faced anything even remotely on this level.

      “Reason”

      1. I know, it’s ridiculous. “Let’s pretend the other flu pandemics never happened.”

        But it’s not just flu. We didn’t eradicate small pox until 1977! (Last outbreak in the US was 1949). It was globally endemic and killed millions annually worldwide, 300 million in the 20th century alone. Covid-19 doesn’t even compare.

  22. “Nearly six times” higher than the flu? The flu’s case death rate ranges between 0.12% and 0.18%. And a case death rate of 0.58% means that the case survival rate is 99.42%.

    Is it even valid to compare COVID-19 to the flu given the fact that the flu has been around for decades, that some people have developed varying degrees of immunity to some flu strains, and that we have had a flu vaccine for decades?

    A more valid comparison might be to compare COVID-19 to the 1957-1958 Asian Flu and the 1968 Hong Kong Flu, since these were new strains, as is COVID-19. The Asian Flu killed 116,000 Americans, even though an effective vaccine was developed five months into the outbreak. The Hong Kong Flu killed 100,000 Americans. As of yesterday, COVID-19 had killed about 80,000 Americans. (On a side note, during the Asian Flu and Hong Kong Flu pandemics, we did not shut down half the economy and did not force tens of millions of Americans to lose their jobs.) 116,000 deaths in 1959 would at least 150,000 today, since our population was 30% smaller then than it is now.

  23. SIX TIMES!

    Whatever.

    The trade off is still not in our favour.

    Open the damn economy up.

    We have to learn to live with it. The sooner the better for our psyche.

    Simple as that.

    1. The infection-fatality rate for COVID-19 in Indiana is 0.58 percent, nearly six times worse than seasonal flu.

      1. Set hair on fire.
      2. Jump out window.

  24. You can do a lot worse than Ron’s covid take on covid response —

    At least it hasn’t killed anyone —
    https://vvattsupwiththat.blogspot.com/2020/05/primum-non-nocere.html

  25. “It is, however, sad that the disparate preliminary results of these studies are being selectively used by today’s culture war factions to confirm their already existing biases.”

    Such as Ronald Bailey.

    1. For example, as a tool of fear-mongering:

      https://www.cnn.com/2020/05/12/opinions/governors-reopen-states-opinion-bar-yam/index.html

      “But as a pandemic expert who has been warning about diseases like Covid-19 for nearly 15 years, my message to Americans is simple: save yourselves, your families and your communities by staying at home and ignoring your governor’s ‘ludicrous’ policies.”

      “Countries that have not imposed sufficiently strict measures, like the US, continue to struggle to contain infection rates.” Sweden? What’s a Sweden? Never heard of it. (same guy, probably)

      Thanks, CNN.

      1. First, we must understand that coronavirus is very deadly. Those who claim the death rate is exaggerated are plain wrong and downplaying the emergency. While death rate estimates have varied, recent data from China, the United Kingdom and France, reflecting deaths outside hospitals, including in nursing homes, puts the Covid-19 global fatality rate at around 6.8%, based upon analysis we did at endcoronavirus.org, using data from Johns Hopkins University.

        JFC. This guy apparently actually believes this? And I thought JFree said that no one, ever, even the biggest panic whores, claimed a fatality rate over 1%?

  26. Of course the numbers for Cold/Wuhan will be higher than the seasonal flu, this is the first year of it. By this fall the percentage should go down as more people are exposed and gain resistance. When they say “there is no guarantee an infected person is immune from a further infection“ that is being disingenuous, just as with the common cold you are not immune but your body builds resistance and the symptoms become less severe. This virus is not going away and the chance an effective vaccine being developed is low, what will happen is we our bodies will learn to live with it as we do with other common cold viruses. The aged, well…the day of being able to live till a hundred on tons of medication may be over for a while…at least until those who have built up resistance reach retirement. Looks like I can give up living to 100.

    1. Excellent take. As for the “aged,” if I was over 80 (certainly over 90) and saw what was being done to save my one-foot-in-the-grave ass, I would say: “Please stop destroying your futures younger people for my sake.” Greatest Generation my ass.

  27. Every single one of these seroprevalence studies has underscored that the virus is FAR less deadly than we were first told. To most, it’s not very deadly at all, to others it’s quite deadly.

    We need to focus on narrowing down the characteristics of the latter group and then targeting protective and treatment measures at them while the rest of us return to work.

    Lockdowns of course help to prevent spread, but they do not do anything to eradicate. And a waiting for a vaccine is an open-ended endeavor. Sure, someone might come up with one in record time, but we have zero vaccines developed today for any of the known human-affecting coronaviruses.

    It’s time to re-open.

  28. That’s six times worse than the average seasonal flu. Bad flu seasons come around every now and then.

    More importantly, you should really compare years of life lost. Given the patterns of COVID19 mortality, it may well be less serious than even the average seasonal flu.

  29. This is a huge pile of numbers without including some critical ones.

    Of the four thousand tested, how many were positive for the virus AND the antibodies? If someone is aymptomatic and has had the virus in their system for a while, there WILL also be antibodies. Until this is sorted out, we have a meaningless pile of speculation.
    No clues as to HOW the “random” subjects were foind, identified, etc. They went and got college students to make the racial numbers included in the surveys match percentages of the general population. What if choosing students in itself brought in a bias?
    Nor do we know the makeup of the samples in INdiana, how did they come to their gross numbers? Did they test everyoine in the state?
    Until a clear methodology is established, each tester will induce his own bias in some way or another. UNtil ALL such biases are equalised, we won’t get meaningful data. It is certain that when some government hooh hah is looking for “data” and “statistics” to “justify” one or another position, or wants to up and announce “listen up folks, THIS is what WE’re gonna do…..” and needs number s to support HIS decision he will look for the “results” that support HIS foregone conclusion. Politicians gotta politick. Some folks got an electioin they want to win. Other folks got an electioin they want someone ELSE to LOSE. I think it was Sam Clemens infamously stated: there are lies, damn lies, and statistics”. I think this article dealt with some statistics.

  30. This “study” is an outlier in terms of fatality rate from other such studies. It’s way too soon to assume anything, but I doubt these numbers are indicative of the reality.

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