Posted on 05/25/2020 4:15:28 PM PDT by NoLibZone
That rate is much lower than the numbers used in the horrifying projections that shaped the government response to the epidemic.
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[s] 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.
Re: “Do you have any data that led you to this estimate or is it just your gut?”
COVID Tests Performed - 14.6 million
Positive Tests - 1.66 million
Positive Test Percentage - 11.4%
I have been calculating the Positive Test Percentage every day for about 5 weeks.
It has never fallen below 11%.
No one is reporting antibody test numbers.
Antibody tests will capture the millions of people who got infected and had no symptoms, or, had mild symptoms and never went to a doctor.
For perspective - the CDC estimates that a minimum of 39 million Americans were infected with influenza during the 6 month influenza season - that is almost a 12% infection rate.
https://www.cdc.gov/flu/about/burden/preliminary-in-season-estimates.htm
We can bet the evil are working in thier supported labs for the next event. They see what can be accomplished world wide
Thanks. And in a worse-case example, far removed from the average, Word Meters finds that New York City (May 1) had an Infection Fatality Rate (IFR) of 1.4% and a 0.28% crude mortality rate to date, or 279 deaths per 100,000 population. (https://www.worldometers.info/coronavirus/coronavirus-death-rate) And we have an (CDC) estimated 116,000 death from the 57-58 Asian flu out of a total population of about 173,000,000.
No, you just think you do. Even the CDC people are now wondering if it helped or hurt. The only thing you have is the power of fear over reality.
Economically, estimates project total losses in state and local revenue of up to 45 percent, effecting 90,000 nonfederal-government entities that provide and pay for most of the government services that Americans receive.[39] And while states look to the Federal government to bail them out, the additional costs and declining revenues stemming from Covid-19 are expected to produce a 2020 budget deficit in excess of $4.2 trillion.[40]
And most of government income comes from taxes, via businesses and those who are employed ( income taxes, payroll taxes, and corporate taxes)[41], yet businesses are failing across America, and in New York alone the governor stated that small businesses constitute “90 percent of New York's businesses” and “more than 100,000 have shut permanently since the pandemic hit.”[42]
Moreover (as of May 20), with 2.43 million in America filing for an unemployment,[43] the rate is at least 20%.[44] Also, according to one meta-analysis of 42 studies involving 20 million people, the risk of death increases 63 percent when one loses their job, and that for every one percentage point increase in the unemployment rate, there are 37,000 deaths, mainly from heart attacks, but another 1,000 from suicides and another 650 from homicides.[45]
And as concerns just suicide, we have reports such as “Calls to suicide and help hotline in Los Angeles increase 8,000% due to coronavirus,”[46] and “Doctors at John Muir Medical Center in Walnut Creek say they have seen more deaths by suicide during this quarantine period than deaths from the COVID-19 virus,”[47]
See just one is nothing else.
And again, just where is the precedent for this, apart from the 1918 flu? 116,000 deaths of out a population of about 173,000,000 equates to about 200,000 deaths today, yet even then there is not comparative response.
Of course, Governor Cuomo was similarly “shocked” to learn that 66 percent of hospital admissions for coronavirus in New York City came from people who had stayed at home in response to his lockdown orders. Really?
http://www.freerepublic.com/focus/f-news/3848520/posts
And expect those numbers to keep dropping. This was always a hoax and let us not forget all the freepers who bought into it hook, line and sinker. Where are they now?
The fallacy is that the economic damage is the result of government lockdowns. It isn't.
People and businesses had begun to shut down and shelter on their own well before government edicts.
If the cases and deaths had followed the NY curve in the rest of the country the slowdown would have been much worse no matter what government did.
Likewise, the recovery will depend on people's level of confidence, not what their governor or especially the President says.
These doctors are imagining a scenario where everyone keeps going to work, sporting events, restaurants, on cruises, etc. etc. while lots of people are getting sick and dying around them.
Not a serious analysis.
People who died at home rarely got tested early on in the pandemic. In many cases the tests just weren't available. Postmortem testing is picking up now but wasn't the norm.
The lung damage would also be obvious in autopsy.
The overall autopsy rate in the US is well under 15%.
The rate for chronically ill elderly people who die in bed at home is probably vanishingly small.
Thia page has the last 10 years of “regular flu” cases & fatalities (est.) if you want to recreate my “recent flu CFR range of 0.096% to 0.176%” numbers.
https://www.cdc.gov/flu/about/burden/index.html
That's why I said 'the last three months.' "Early on" couldn't possibly apply to any time after March 1.
The rate for chronically ill elderly people who die in bed at home is probably vanishingly small.
That would make your point about undiagnosed deaths at home early on a meaningless fraction of a percent.
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I do have to correct my mistake in post #97. The SARS (H1N1 influenza) epidemic in 2009 is not what I was originally referring to in post #95. Total U.S. deaths 12k+.
What I meant to cite was the total U.S. fatalities of the 2017-2018 flu season (H3N2). The CDC estimates 80k deaths. That is with a vaccine.
A point which renders your fatuous arguments moot.
Your first assertion is wrong and misleading since it presupposes my argument was about goverment mandated shutdowns, your second assertion does not help you. For we are not talking about some degree of beginning, but that of the basic shutdown, and it was media and government exhortations and later edicts that progressively resulted in lockdowns with its massive (20%) weeks of unemployment. Which degree of response remains without comparative precedent regardless of how much you insist on defending it, like as liberals do. Do you really think we would be seeing the unprecedented response it Trump was not President?
If the cases and deaths had followed the NY curve in the rest of the country the slowdown would have been much worse no matter what government did.
Which argument is invalid for that would be an unwarranted presumption (meaning expecting that the rest of the country would follow a city with the highest population density of major cities and which presently constitutes about 29% of all Covid case fatalities).
Likewise, the recovery will depend on people's level of confidence, not what their governor or especially the President says.
Which is a logical fallacy, for rather than an either/or choice, people's level of confidence - as well demonstrated - relates to what their governor or especially the President says, but most of all what the media headlines what they say. We are in an age of unprecedented media reception, much of it on tiny screens in which people mainly do not read much more than the headlines. And the media and liberals foster paranoia and hypocritically speak about the tragedy of deaths when they support both abortion and assisted suicide. The fact is that relatively rarely does anyone die of Covid under 60, and most are over 70, and in quarantines. I am 68 and likely had Covid. Wear masks as needed, esp. around the evidently such or the most vulnerable but do not stay sheltered, stop working, etc.
Been there, and it only goes back 10 years. The CDC site leaves much to be desired.
100% BS.
People were dining and drinking out until the last day.
So why then has there been no rebounds in Georgia? In Florida?
Perhaps, the shutdowns were not nearly as effective as your self-assumed powers of reason have assumed. In fact, there is a body of scientific opinion (maybe even some a tad more well-versed in the topic than yourself) that have argued they have had a negligible effect on the overall course of the virus.
That would make your point about undiagnosed deaths at home early on a meaningless fraction of a percent.
???
Sure they were.
Except at the NBA arenas and spring training fields and NHL arenas and movie theaters and and and.
Then you said "The rate for chronically ill elderly people who die in bed at home is probably vanishingly small."
If the second statement is true, and I tend to agree that it is, the first statement doesn't mean much. If the number of people who die at home is vanishingly small the number who died of Covid is even smaller and wouldn't add enough to the official count to mean anything.
There are lots of arguments out there.
What's the scientific reason the curve turned downward in NY? It certainly wasn't herd immunity because we're nowhere near the levels of exposure needed even there.
What mechanism do the well versed propose?
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