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.
Indeed, and with the most deaths being among those who were quarantined. And which "extreme mitigation measures" will exact a death toll likely higher than the virus. Meaning the issue is not that Covid was/in very infectious and too-often lethal to a certain class, but whether the measures enacted in response were what was best. Thus far they have been without precedent relative to the population fatality rate.
Do you have any data that led you to this estimate or is it just your gut?
What's the highest number you've seen for nationwide infection rate in the literature?
So how do you account for 100K deaths in three months despite extreme measures when we have many fewer flu deaths in an entire year with no extraordinary steps taken. Especially when almost all of the Covid deaths were in your elderly and infirm population.
How so?
Meaning 7% of 331,000,000 have been infected, and 100,000 deaths equals a CFR of 0.49%? Too late for me to go any further to-nite. Time to catch some zzz's.
“This whole episode has been a farce.”
Yes it is.
Then when you throw in the vast numbers who insist that .3% is 3 percent instead of 1/3 of 1% you can see why the hysterical over-reacting of the karen/chads.
No wonder they have worked so hard to dumb down our kids for the last 4-5 decades. Now they can sell them anything.
If I recall correctly, about 80% have mild symptoms, 15% get hospitalized and recover and 5% die (close to the 5.8%). This would give about 2 million cases based on 100k deaths, meaning 30 MILLION HAD NO SYMPTOMS OR VERY MILD SYNONYMS!
So while CV appears to have about a 10x death rate compared to flu, it may be that people with flu are 4x more likely to show symptoms. (Flu 25% show symptoms. CV 2/32 = 6.25% show symptoms. 25/6.25 = 4x)
This all unverified based what might be incorrect data/assumptions, such as the 0.3% CV death rate applying to the US. More analysis should also be done for age and at risk groups, etc.
None of that current data is worth a plugged nickle or a dead turtle. Not to mention all the asymptomatic cases of Covid-19 are left completely out of your “data” set. Let’s also remember that influenza is a non-reportable disease so “apples to apples” goes right out the window there.
Yep, approx. (I used 6% for my spreadsheet)...my “W.A.G.” for COVOD-19 “final CFR” (in a year or so) is 0.2%.
Leaving aside the fact that there isn’t a national shutdown so a letter to Trump is purely political, all they’re arguing for is a controlled reopening which no one objects to.
I notice they have no criticism of the original distancing measures, which were being put into effect by the population well before the government acted.
I’m glad you can be so cavalier about a 600% increase in suicide hotline calls. Which is only just the beginning since we’re only 2 1/2 months into this economic crash.
Not cavalier at all. Not taking 100k deaths in three months lightly either.
There aren't 100k deaths from Covid right now.
Not if you take into account the downward adjustments of covid deaths such as the 31% overcount in Colorado.
You’re whatabouting the Spanish flu? That’s what you’ve got?
There aren't 100k deaths from Covid right now.
How many people have died at home never diagnosed with Covid?
How many people have died at home never diagnosed with Covid?
None. Everyone who has died at home in the past three months would have been tested. The lung damage would also be obvious in autopsy.
I knew this would be beyond your reasoning power.
You seriously thought that only 100k people died of the Spanish Flu? LOL
The CDC estimates that 675k died in the U.S.
The population of the U.S. in 1918 was only 103 million then.
I agree, it was not an overreaction in the beginning. There were too many unknowns. With that said, once the real statistics came out and were understood they should have opened things up sometime ago. Now they are trying to delay opening things up impact the elections.
The first amendment to the constitution has been trampled. They suspended the constitution for medical reasons. Next time it willl be for something like ingrown toenails because we all know that global warming causes ingrown toenails. /sarc.
Re: “So how do you account for 100K deaths in three months?”
Simple - they don’t count flu deaths the same way they count COVID deaths.
Here is the link to the CDC memo that explains how to count COVID deaths...
Here is a brief summary of that memo:
(1) All “presumed” COVID deaths are given the same code as COVID deaths that were confirmed by testing.
(2) Death Certificates are to be filled out in a way that essentially guarantees that 100% of the people who have COVID and die are classified as a COVID fatality, regardless of any other diseases that might be present.
Examples:
(1) Influenza precedes at least 50% of pneumonia deaths each year. However, less than 10% of pneumonia deaths are classified as flu deaths.
(2) If a pneumonia victim who has COVID dies, 100% of those deaths are classified as COVID fatalities.
Bottom Line...
Based just on pneumonia deaths alone, influenza fatalities would be over 100,000 EVERY YEAR - if they were counted the same way as COVID fatalities.
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