Huh. What do you know? Who, and I mean who coulda known? ---------------------------- Link The CDC's New 'Best Estimate' Implies a COVID-19 Infection Fatality Rate Below 0.3% According to the Centers for Disease Control and Prevention (CDC), the current "best estimate" for the fatality rate among Americans with COVID-19 symptoms is 0.4 percent. The CDC also estimates that 35 percent of people infected by the COVID-19 virus never develop symptoms. Those numbers imply that the virus kills less than 0.3 percent of people infected by it—far lower than the infection fatality rates (IFRs) assumed by the alarming projections that drove the initial government response to the epidemic, including broad business closure and stay-at-home orders. The CDC offers the new estimates in its "COVID-19 Pandemic Planning Scenarios," which are meant to guide hospital administrators in "assessing resource needs" and help policy makers "evaluate the potential effects of different community mitigation strategies." It says "the planning scenarios are being used by mathematical modelers throughout the Federal government." The CDC's five scenarios include one based on "a current best estimate about viral transmission and disease severity in the United States." That scenario assumes a "basic reproduction number" of 2.5, meaning the average carrier can be expected to infect that number of people in a population with no immunity. It assumes an overall symptomatic case fatality rate (CFR) of 0.4 percent, roughly four times the estimated CFR for the seasonal flu. The CDC estimates that the CFR for COVID-19 falls to 0.05 percent among people younger than 50 and rises to 1.3 percent among people 65 and older. For people in the middle (ages 50–64), the estimated CFR is 0.2 percent. That "best estimate" scenario also assumes that 35 percent of infections are asymptomatic, meaning the total number of infections is more than 50 percent larger than the number of symptomatic cases. It therefore implies that the IFR is between 0.2 percent and 0.3 percent. By contrast, the projections that the CDC made in March, which predicted that as many as 1.7 million Americans could die from COVID-19 without intervention, assumed an IFR of 0.8 percent. Around the same time, researchers at Imperial College produced a worst-case scenario in which 2.2 million Americans died, based on an IFR of 0.9 percent. Such projections had a profound impact on policy makers in the United States and around the world. At the end of March, President Donald Trump, who has alternated between minimizing and exaggerating the threat posed by COVID-19, warned that the United States could see "up to 2.2 million deaths and maybe even beyond that" without aggressive control measures, including lockdowns. One glaring problem with those worst-case scenarios was the counterfactual assumption that people would carry on as usual in the face of the pandemic—that they would not take voluntary precautions such as avoiding crowds, minimizing social contact, working from home, wearing masks, and paying extra attention to hygiene. The Imperial College projection was based on "the (unlikely) absence of any control measures or spontaneous changes in individual behaviour." Similarly, the projection of as many as 2.2 million deaths in the United States cited by the White House was based on "no intervention"—not just no lockdowns, but no response of any kind. Another problem with those projections, assuming that the CDC's current "best estimate" is in the right ballpark, was that the IFRs they assumed were far too high. The difference between an IFR of 0.8 to 0.9 percent and an IFR of 0.2 to 0.3 percent, even in the completely unrealistic worst-case scenarios, is the difference between millions and hundreds of thousands of deaths—still a grim outcome, but not nearly as bad as the horrifying projections cited by politicians to justify the sweeping restrictions they imposed. "The parameter values in each scenario will be updated and augmented over time, as we learn more about the epidemiology of COVID-19," the CDC cautions. "New data on COVID-19 is available daily; information about its biological and epidemiological characteristics remain limited, and uncertainty remains around nearly all parameter values." But the CDC's current best estimates are surely better grounded than the numbers it was using two months ago. A recent review of 13 studies that calculated IFRs in various countries found a wide range of estimates, from 0.05 percent in Iceland to 1.3 percent in Northern Italy and among the passengers and crew of the Diamond Princess cruise ship. This month Stanford epidemiologist John Ioannidis, who has long been skeptical of high IFR estimates for COVID-19, looked specifically at published studies that sought to estimate the prevalence of infection by testing people for antibodies to the virus that causes the disease. He found that the IFRs implied by 12 studies ranged from 0.02 percent to 0.4 percent. My colleague Ron Bailey last week noted several recent antibody studies that implied considerably higher IFRs, ranging from 0.6 percent in Norway to more than 1 percent in Spain. Methodological issues, including sample bias and the accuracy of the antibody tests, probably explain some of this variation. But it is also likely that actual IFRs vary from one place to another, both internationally and within countries. "It should be appreciated that IFR is not a fixed physical constant," Ioannidis writes, "and it can vary substantially across locations, depending on the population structure, the case-mix of infected and deceased individuals and other, local factors." One important factor is the percentage of infections among people with serious preexisting medical conditions, who are especially likely to die from COVID-19. "The majority of deaths in most of the hard hit European countries have happened in nursing homes, and a large proportion of deaths in the US also seem to follow this pattern," Ioannidis notes. "Locations with high burdens of nursing home deaths may have high IFR estimates, but the IFR would still be very low among non-elderly, non-debilitated people." That factor is one plausible explanation for the big difference between New York and Florida in both crude case fatality rates (reported deaths as a share of confirmed cases) and estimated IFRs. The current crude CFR for New York is nearly 8 percent, compared to 4.4 percent in Florida. Antibody tests suggest the IFR in New York is something like 0.6 percent, compared to 0.2 percent in the Miami area. Given Florida's high percentage of retirees, it was reasonable to expect that the state would see relatively high COVID-19 fatality rates. But Florida's policy of separating elderly people with COVID-19 from other vulnerable people they might otherwise have infected seems to have saved many lives. New York, by contrast, had a policy of returning COVID-19 patients to nursing homes. "Massive deaths of elderly individuals in nursing homes, nosocomial infections [contracted in hospitals], and overwhelmed hospitals may…explain the very high fatality seen in specific locations in Northern Italy and in New York and New Jersey," Ioannidis says. "A very unfortunate decision of the governors in New York and New Jersey was to have COVID-19 patients sent to nursing homes. Moreover, some hospitals in New York City hotspots reached maximum capacity and perhaps could not offer optimal care. With large proportions of medical and paramedical personnel infected, it is possible that nosocomial infections increased the death toll." Ioannidis also notes that "New York City has an extremely busy, congested public transport system that may have exposed large segments of the population to high infectious load in close contact transmission and, thus, perhaps more severe disease." More speculatively, he notes the possibility that New York happened to be hit by a "more aggressive" variety of the virus, a hypothesis that "needs further verification." If you focus on hard-hit areas such as New York and New Jersey, an IFR between 0.2 and 0.3 percent, as suggested by the CDC's current best estimate, seems improbably low. "While most of these numbers are reasonable, the mortality rates shade far too low," University of Washington biologist Carl Bergstrom told CNN. "Estimates of the numbers infected in places like NYC are way out of line with these estimates." But the CDC's estimate looks more reasonable when compared to the results of antibody studies in Miami-Dade County, Santa Clara County, Los Angeles County, and Boise, Idaho—places that so far have had markedly different experiences with COVID-19. We need to consider the likelihood that these divergent results reflect not just methodological issues but actual differences in the epidemic's impact—differences that can help inform the policies for dealing with it.
This has already been discussed on other threads and completely debunked. Why are you bringing it up again. The CDC published 5 different scenarios in a planning study... somehow some yahoos siezed on the fifth scenario to claim the official Infection Fatality Rate (IFR) is under 0.3%. This is not what the CDC said. Even worse the yahoos then went on to compare this IFR of 0.3% to the CFR of the seasonal flu and come up with the wrong conclusion that COVID is only 3 times more deadly than the flu at most. Sorry -- the IFR of the seasonal flu is between 0.012% to 0.021%. This still means that COVID is at least 30 times more deadly than the seasonal flu. Even with the planning study number of 0.3% from the CDC paper for scenario 5. In other news from the CDC... how will they even estimate the number of infections when the tests fail 50% of the time. This makes any projection on the number of infections nearly meaningless. Studies should be based on tested confirmed positive cases. Antibody tests for Covid-19 wrong up to half the time, CDC says https://www.cnn.com/2020/05/26/health/antibody-tests-cdc-coronavirus-wrong/index.html May 26th Antibody tests used to determine if people have been infected in the past with Covid-19 might be wrong up to half the time, the US Centers for Disease Control and Prevention said in new guidance posted on its website. Antibody tests, often called serologic tests, look for evidence of an immune response to infection. "Antibodies in some persons can be detected within the first week of illness onset," the CDC says. They are not accurate enough to use to make important policy decisions, the CDC said. "Serologic test results should not be used to make decisions about grouping persons residing in or being admitted to congregate settings, such as schools, dormitories, or correctional facilities," the CDC says. (More at above url)
I don't know why I'm bringing it up. I thought the CDC were the "experts". Are you saying they are not the experts? Or are you saying they did not say what the article says they said? The article clearly states which scenario it is quoting from. But the scenario is what the CDC published. Additionally, regardless of how wrong the antibody tests are, why is it multiple locations don't jive with the data coming from NYC for example?
The experts over at the CDC have once again reversed their position. Now it seems the virus will live quite some time on a hard surface. I cannot believe we keep going to these dopes for opinions on anything. The experts have been wrong, completely and totally wrong about every single thing from day one. On their opinions we have destroyed the economy, bankrupting who knows how many businesses, sent tens of millions to the unemployment line and cost us trillions of dollars in money to be paid back with decades of oppressive taxes. And they get paid to "help out" . WTF?
The CDC is nothing more than an outlet for political narrative being pushed by the Trump administration at this point... even generating a nonsense "Pandemic Planning" study based on data sets led by scientists in Iran. The CDC Released New Death Rate Estimates For The Coronavirus. Many Scientists Say They’re Too Low. Public health experts are accusing the CDC of bending under political pressure to say the coronavirus is less deadly. https://www.buzzfeednews.com/article/stephaniemlee/coronavirus-cdc-infection-fatality-rate New CDC estimates of coronavirus death rates look suspiciously low and present almost no data to back them up, say public health experts who are concerned that the agency is buckling under political pressure to restart the economy. A week ago, as the US began to reopen, the CDC put out five scenarios for how the coronavirus crisis could play out across the country. This “pandemic planning” document is being used throughout the federal government and is meant to help public officials make decisions about when and how to reopen, according to the CDC. In addition to providing various rates of hospitalizations and infections, the CDC gave new estimates of the total fatality rate of the virus, ranging from about 0.1% (its least deadly scenario) to 0.8% (its deadliest scenario). The agency also cited a “best estimate” of 0.26%. While no one yet knows the coronavirus’s actual death rate, the agency’s range of possible rates seemed alarmingly low to many epidemiologists, compared to existing data in places both inside and outside the US. For instance, estimates of New York City’s total death rate, 0.86% to 0.93%, are even higher than the CDC’s worst-case scenario. Estimates from countries like Spain and Italy are also higher, ranging from 1.1% to 1.3%. Researchers also lambasted the CDC’s lack of transparency about its data sources. The eight-page document disclosed almost nothing about its numbers, citing only internal data and a preprint — a study that has not been peer-reviewed — led by scientists in Iran. “This is terrible. This is way too optimistic,” Andrew Noymer, an associate professor of population health at the University of California at Irvine, told BuzzFeed News, adding, “With this document, the CDC is determined to smash its credibility with the public health community of which it is supposedly a leader.” The CDC did not return multiple requests for comment. Nevertheless, some observers have seized on the CDC’s estimates to bolster their view that the virus isn’t that deadly, and that it is safe to reopen the economy. On Tuesday, Stanford University epidemiologist John Ioannidis cited the CDC numbers in an op-ed for the Boston Review, saying “it is clear that the numbers are much lower than first feared.” Ioannidis, who is famous for starting a movement to root out shoddy science, has recently found himself on the receiving end of criticism for his role in a controversial antibody study in Northern California. That study produced low estimates for the coronavirus’s death rate, which Ioannidis then cited in the media, including on Fox News, to say that it was in the same ballpark as the flu. The CDC numbers also quickly gained notice from others who share Ioannidis’s view that the virus is not deadly enough to justify economic lockdowns, including right-leaning commentators and media outlets. “SPEAK OUT. GO OUT,” tweeted Cliff Maloney, president of the libertarian student organization Young Americans for Liberty, sharing the CDC’s new fatality numbers. Out of the 1.68 million Americans diagnosed with COVID-19, almost 100,000, or about 5.9%, are confirmed to have died from it to date. But most scientists agree that the true rate of deaths for all infected people, also known as the infection fatality rate, is likely to be lower when undiagnosed cases are added to the denominator. Many people who get sick with the disease show mild or no symptoms, and a lack of diagnostic testing in the US also means that infections are undercounted, though no one knows yet by how much. (That’s not the only factor throwing a wrench into the equation: Deaths, too, are believed to be undercounted.) To Amesh Adalja, an infectious disease researcher at the Johns Hopkins Center for Health Security, the CDC’s best-guess death rate seemed right around where he would expect. “I don’t have a problem with that number,” he said, adding, “The more we look, the more we’re finding patients that have antibodies, that don’t recall illness, and people who have very mild illness and are not getting tested.” The coronavirus is not equally deadly to everyone everywhere. Infection fatality rates vary with many factors, from location to population density to age to healthcare availability. But five other experts told BuzzFeed News they were perplexed that the CDC’s highest estimated fatality rate is lower than estimates for some of the world’s hardest-hit areas. In the CDC’s deadliest scenario, the infection fatality rate for the virus is about 0.8%. But in New York City, an estimated 0.86% to 0.93% of all people who got sick died, according to two preliminary analyses of available data, including a recent antibody survey that provided the best estimate yet of the total number of residents who have been infected. Those figures would put the death rate in the city — hit with the most lethal outbreak in the US, with at least 16,600 COVID-19 deaths to date — beyond the CDC’s worst-case scenario. “Surely the worst-case scenario should at least be New York for the whole country,” said Gideon Meyerowitz-Katz, an epidemiologist at the University of Wollongong in Australia, who has been tracking infection fatality rates in New York City and elsewhere. And Natalie Dean, a University of Florida biostatistician, said, “The point is that you [should] capture a range of scenarios based on what data we have available right now. With the data we have available right now, we can’t rule out something higher. A worst-case scenario needs to be a real worst-case scenario.” Other estimates in hot spots outside the US are also higher than the agency’s deadliest estimate. In Spain, a massive antibody survey of more than 60,000 people put its overall fatality rate at around 1.1% to 1.3%. In Italy, researchers estimate that 1.2% of all cases have resulted in death, and in France, 0.8%. These estimates are on the higher end of the disease’s apparent fatality across the world. A preliminary analysis of more than two dozen studies from Europe, China, the US, and elsewhere, conducted by Meyerowitz-Katz and colleague Lea Merone, suggests that the overall infection fatality rate is between 0.5% and 0.78%. Even the lower end of that range is higher than what the CDC says is its “best estimate” for the rate, which is about 0.26%. The CDC’s proposed fatality rates “are more in line with a relatively mild seasonal flu season than with COVID-19,” said Gerardo Chowell, a public health expert at Georgia State University. Those estimates are at least an order of magnitude lower than ones elsewhere in the world, he added, including South Korea, which has a case fatality rate around 0.7% and one of the highest testing rates for the coronavirus in the world. Another preprint, released last week by Ioannidis of Stanford, put forth a much lower range that is closer to the CDC’s, from 0.02% to 0.4%. (Meyerowitz-Katz and others have criticized the paper for including some questionable estimates on the lower end while leaving out higher rates in places like Spain, as well as for its statistical analysis.) But the CDC document provided almost no sources for its projections, making it impossible for scientists to understand how it came up with them. The white paper, posted May 20, states that it is based on “data received by CDC” prior to April 29, and its death rate projections on “preliminary COVID-19 estimates, CDC.” The only coronavirus-related study cited is a preprint about the virus’s incubation period, led by Iranian researchers and released nearly two months ago. The CDC did not respond to questions about its data sources or why the preprint was the only coronavirus study cited. (The paper’s lead scientist in Iran also did not return a request for comment.) The low estimates and lack of transparency have frustrated scientists, who have been watching the coronavirus’s death rate become weaponized in the increasingly partisan debate over reopening the economy. “When I see that — especially for something that has become a question and has become more politicized than I ever would have expected — there’s an obligation to explain the source,” said Dean, the University of Florida biostatistician. Carl Bergstrom, an epidemiologist at the University of Washington, expressed concern that the CDC’s numbers will skew projections going forward because there will be some pressure to use the US government’s models. “Given that these parameter sets underestimate fatality by a substantial margin compared to current scientific consensus, I see this as deeply problematic,” he said by email. As June approaches, all 50 states are in some stage of reopening. Public health experts, including Anthony Fauci, director of the National Institutes of Allergy and Infectious Diseases, worry that some parts of the country may be starting up too quickly and could cause a new wave of infections and deaths. Noymer, the UC Irvine demographer, said the nation can’t make informed decisions about the way forward without the most accurate data possible. “I am not in favor of indefinite and severe lockdowns,” he said. “But as we balance the risk and reward, we have to have hopefully realistic estimates of both.” He added, “These estimates are doing a disservice to policy because it’s not a realistic estimate of the risk.”
You're right. Because it seems to me that this is a way of saying "we were completely wrong, so we needed to change the model to fit the facts that transpired that we never expected."
Ah, so the CDC "experts" are not the "experts" we should be listening to anymore. Can you do me a favor? Can you make a table of the Good and Evil "experts" so we know which of the "experts" we should trust opinions on? Because the WHO was supposed to be the "experts", you know, them being the World Health Organization and all, but they told us the virus wasn't contagious back in the beginning of the year. Boy was that wrong, huh? Now we are being told the Center for Disease Control are no longer "experts" to trust because they are being pushed by Trump. So I need you to tell me who I can believe. Should I just play it safe and believe any "expert" who tells me to remain locked in my closet for the next 4 years?
even in the worst case scenario which is NYC .... IFR still below 1. And there are no clusters like NYC happening any more. Scenario five... the Data shows Infection Fatality Rate of .26 And that the lowest hanging fruit for this virus are either gone or better protected the final IFR is likely to be lower than .26 (if .26 was calculated properly using actual data.) from GWBs article... "In the CDC’s deadliest scenario, the infection fatality rate for the virus is about 0.8%. But in New York City, an estimated 0.86% to 0.93% of all people who got sick died, according to two preliminary analyses of available data, including a recent antibody survey that provided the best estimate yet of the total number of residents who have been infected. Those figures would put the death rate in the city — hit with the most lethal outbreak in the US, with at least 16,600 COVID-19 deaths to date — beyond the CDC’s worst-case scenario. “Surely the worst-case scenario should at least be New York for the whole country,” said Gideon Meyerowitz-Katz, an epidemiologist at the University of Wollongong in Australia, who has been tracking infection fatality rates in New York City and elsewhere. And Natalie Dean, a University of Florida biostatistician, said, “The point is that you [should] capture a range of scenarios based on what data we have available right now. With the data we have available right now, we can’t rule out something higher. A worst-case scenario needs to be a real worst-case scenario.” Other estimates in hot spots outside the US are also higher than the agency’s deadliest estimate."