LOCKDOWN LUNACY: the thinking person's guide - May 30 2020 - By J.B. Handley
Posted: Sun May 31, 2020 9:42 pm
part 1 of 2 - LOCKDOWN LUNACY: the thinking person's guide - May 30 2020
By J.B. Handley
LOCKDOWN LUNACY: the thinking person's guide
For anyone willing to look, there are so many facts that tell the true story, and it goes something like this:
Knowing what we know today about COVID-19’s Infection Fatality Rate, asymmetric impact by age and medical condition, non-transmissibility by asymptomatic people and in outdoor settings, near-zero fatality rate for children, and the basic understanding of viruses through Farr’s law, locking down society was a bone-headed policy decision so devastating to society that historians may judge it as the all-time worst decision ever made. Worse, as these clear facts have become available, many policy-makers haven’t shifted their positions, despite the fact that every hour under any stage of lockdown has a domino-effect of devastation to society. Meanwhile, the media—with a few notable exceptions—is oddly silent on all the good news. Luckily, an unexpected group of heroes across the political landscape—many of them doctors and scientists—have emerged to tell the truth, despite facing extreme criticism and censorship from an angry mob desperate to continue fighting an imaginary war.
My goal is to engage in known facts. You, the reader, can decide if all of these facts, when you put them together, equate to the story above.
Fact #1: The Infection Fatality Rate for COVID-19 is somewhere between 0.07-0.20%, in line with seasonal flu
The Infection fatality Rate math of ANY new virus ALWAYS declines over time as more data becomes available, as any virologist could tell you. In the early days of COVID-19 where we only had data from China, there was a fear that the IFR could be as high as 3.4%, which would indeed be cataclysmic. On April 17th, the first study was published from Stanford researchers that should have ended all lockdowns immediately, as the scientists reported that their research “implies that the infection is much more widespread than indicated by the number of confirmed cases” and pegged the IFR between 0.12-0.2%. The researchers also speculated that the final IFR, as more data emerged, would likely “be lower.” For context, seasonal flu has an IFR of 0.1%. Smallpox? 30%.
As the first study to peg the IFR, the Stanford study came under withering criticism, prompting the lead researcher, Dr. John Ioannidis to note,
“There’s some sort of mob mentality here operating that they just insist that this has to be the end of the world, and it has to be that the sky is falling. It’s attacking studies with data based on speculation and science fiction. But dismissing real data in favor of mathematical speculation is mind-boggling.”
Like all good science, the Stanford data on IFR has now been replicated so many times that our own Centers for Disease Control came out this week to announce that their ‘best estimate’ showed an IFR below 0.3%. In this article on the CDC’s new data, they also highlighted how the cascading declines in IFR has removed all the fears of doomsday:
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.
If you’re still unconvinced that the IFR of COVID-19 is roughly in line with a bad flu season, the most comprehensive analysis I have seen comes from Oxford University, who recently stated:
“Taking account of historical experience, trends in the data, increased number of infections in the population at largest, and potential impact of misclassification of deaths gives a presumed estimate for the COVID-19 IFR somewhere between 0.1% and 0.41%.”
Finally, just last week, Stanford’s Dr. Ioannidis published a meta-analysis (because so many IFR studies have been done around the world in April and early May) where he analyzed TWELVE separate IFR studies and his conclusion is so good, I’ll just leave you with it:
The infection fatality rate (IFR), the probability of dying for a person who is infected, is one of the most critical and most contested features of the coronavirus disease 2019 (COVID-19) pandemic. The expected total mortality burden of COVID-19 is directly related to the IFR. Moreover, justification for various non-pharmacological public health interventions depends crucially on the IFR. Some aggressive interventions that potentially induce also more pronounced collateral harms1 may be considered appropriate, if IFR is high. Conversely, the same measures may fall short of acceptable risk-benefit thresholds, if the IFR is low…Interestingly, despite their differences in design, execution, and analysis, most studies provide IFR point estimates that are within a relatively narrow range. Seven of the 12 inferred IFRs are in the range 0.07 to 0.20 (corrected IFR of 0.06 to 0.16) which are similar to IFR values of seasonal influenza. Three values are modestly higher (corrected IFR of 0.25-0.40 in Gangelt, Geneva, and Wuhan) and two are modestly lower than this range (corrected IFR of 0.02-0.03 in Kobe and Oise).
Opinion #1: Dr. Scott Atlas
Dr. Scott Atlas
Soon after the Stanford study released its data (he wasn’t a study author), Stanford’s Dr. Scott Atlas published an opinion piece in The Hill newspaper with the title, “The data is in — stop the panic and end the total isolation.” He wrote:
The recent Stanford University antibody study now estimates that the fatality rate if infected is likely 0.1 to 0.2 percent, a risk far lower than previous World Health Organization estimates that were 20 to 30 times higher and that motivated isolation policies…Let’s stop underemphasizing empirical evidence while instead doubling down on hypothetical models. Facts matter.
Facts do matter, but no one listened. Dr. Atlas’ article also helps frame Fact #2.
Fact #2: The risk of dying from COVID-19 is much higher than the average IFR for older people and those with co-morbidities, and much lower than the average IFR for younger healthy people, and nearing zero for children
Source: CDC
In January 2020, Los Angeles had an influenza outbreak that was killing children, the LA Times noted that “an unlikely strain of influenza has sickened and killed an unusually high number of young people in California this flu season.” COVID-19 is the opposite of that. Stanford’s Dr. Ioannidis said, “Compared to almost any other cause of disease that I can think of, it’s really sparing young people.”
Italy reported three days ago that 96% of Italians who died from COVID-19 had “other illnesses” and were, on average, 80 years old. From Bloomberg:
“The latest numbers show that new cases and fatalities have a common profile: mostly elderly people with previous illnesses,” ISS chief Silvio Brusaferro said at a news conference Friday.
The best age stratification data I have seen comes from Worldometers.info. Here’s their chart estimating death rate by age group. Please note that death rate is MUCH higher than IFR because death rate uses confirmed COVID-19 cases as the denominator, but it shows you how different the fatality rates are by age:
While this data is “crude”, it’s safe to extrapolate that an 80+ year-old person has a serious risk of dying from COVID-19 while a child faces almost no risk. This fact should drive policy, as Dr. Atlas explains:
Of all fatal cases in New York state, two-thirds were in patients over 70 years of age; more than 95 percent were over 50 years of age; and about 90 percent of all fatal cases had an underlying illness. Of 6,570 confirmed COVID-19 deaths fully investigated for underlying conditions to date, 6,520, or 99.2 percent, had an underlying illness. If you do not already have an underlying chronic condition, your chances of dying are small, regardless of age. And young adults and children in normal health have almost no risk of any serious illness from COVID-19.
Consider this excellent article from the British Medical Journal, titled “Shielding from covid-19 should be stratified by risk” written by Cambridge University professors:
Protecting those at most risk of dying from covid-19 while relaxing the strictures on others provides a way forward in the SARS-CoV-2 epidemic, given the virus is unlikely to disappear in the foreseeable future. Such targeted approaches would, however, require a shift away from the notion that we are all seriously threatened by the disease, which has led to levels of personal fear being strikingly mismatched to objective risk of death. Instead, the aim should be to communicate realistic levels of risk as they apply to different groups, not to reassure or frighten but to allow informed personal decisions in a setting of necessary uncertainty.
As one simple example: closing schools makes almost no sense given what we know about COVID-19, while protecting teachers over the age of 60—to pick a somewhat defensible age boundary—may well make sense. This is why so many countries who seem to respect data more than we do here in the U.S. have already re-opened their schools. In fact, Denmark’s schools have been open since mid-April!! And, for those keeping score, Reuters just reported yesterday that, “Reopening schools in Denmark did not worsen outbreak, data shows.” Here’s a quote:
“You cannot see any negative effects from the reopening of schools,” Peter Andersen, doctor of infectious disease epidemiology and prevention at the Danish Serum Institute said on Thursday told Reuters. In Finland, a top official announced similar findings on Wednesday, saying nothing so far suggested the coronavirus had spread faster since schools reopened in mid-May.
Another great article on schools, titled, “It is fear – not science – that is stopping our children being educated” in The Telegraph newspaper last week, here’s a quote:
There is little about coronavirus we can be absolutely sure of – this is a brand new disease and our knowledge grows by the day - but most of the available evidence so far strongly suggests that children are neither suffering from coronavirus nor spreading it. Studies in South Korea, Iceland, Italy, Japan, France, China, the Netherlands and Australia all concur that youngsters are “not implicated significantly in transmitting Covid”, not even to parents and siblings.
Adult paranoia, stoked by over-the-top government messaging, union intransigence and media conniptions, is now being inflicted on the youngest members of our society to whom the virus poses a threat so tiny scientists call it “statistically irrelevant”. Instead of nursery rhymes, mixed infants may soon be invited to sing something called the “two-metre-song” as they stick their arms out to keep their friends at bay.
Brand new science (May 28) released from Northern Ireland clearly shows that schoolchildren do NOT serve as vectors for COVID-19. Titled, No evidence of secondary transmission of COVID-19 from children attending school in Ireland, 2020, the study could not be more clear:
These findings suggest that schools are not a high risk setting for transmission of COVID-19 between pupils or between staff and pupils. Given the burden of closure outlined by Bayhem [4] and Van Lanker [5], reopening of schools should be considered as an early rather than a late measure in the lifting of restriction.
Finally, Dr. Scott Atlas took on the topic of schools in this recent interview:
“There’s no science whatsoever to keep K-through-12 schools closed, nor to have masks or social distancing on children, nor to keep summer programs closed. What we know now is that the risk of death and the risk of even a serious illness is nearly zero in people under 18.
(Special note: there’s a new boogeyman, Kawasaki disease, that some are trying to link to COVID-19. Here’s a great article about that, or see the website of the UK’s Kawasaki Disease Foundation where they discuss the “mishandling of information” about Kawasaki disease.)
Fact #3: People infected with COVID-19 who are asymptomatic (which is most people) do NOT spread COVID-19
Guangdong Provincial People’s Hospital
On January 13, 2020, a 22-year old female with a history of congenital heart disease went to the emergency room of Guangdong Provincial People’s Hospital complaining of a variety of symptoms common to people with her condition, including pulmonary hypertension and shortness of breath due to atrial septal defect (hole in the heart). Little did she know her case would set off a cascade of events resulting in a recently published paper that should have ended all lockdowns around the world simultaneously. Three days into her hospital stay, her condition was improving. Routine tests were run, and to the clinicians alarm and surprise, she tested positive for COVID-19. As the physicians noted, “the patient had never fever, sore throat, myalgia or other symptoms associated with virus infection.” Said differently, she was completely asymptomatic for COVID-19.
It’s not that easy to find people who are infected with COVID-19 but asymptomatic, because they don’t seek medical attention. Here in Oregon where I live, you can’t even get a COVID-19 test unless you have symptoms. So, the stars aligned to put this woman in a hospital with researchers studying COVID-19, and she became the subject of an extensive contact study published on May 13 in Respiratory Medicine, titled, “A study on infectivity of asymptomatic SARS-CoV-2 carriers.”
The researchers wanted to find out whether this woman, with a COVID-19 infection but no symptoms, had infected anyone else, so they chose to look at every single contact they could identify within the previous 5 days prior to her positive test. So, how many people did they have to screen? 455. Not a small number, as the researchers explain:
455 contacts who were exposed to the asymptomatic COVID-19 virus carrier became the subjects of our research. They were divided into three groups: 35 patients, 196 family members and 224 hospital staffs. We extracted their epidemiological information, clinical records, auxiliary examination results and therapeutic schedules.
As you can see, being hospitalized led to the majority of the contacts this woman had, both with other patients and with many members of the hospital staff. Notably, all of these contacts took place indoors and one might argue many of the contacts—at least with hospital staff—would have involved relatively intimate contact. Amongst the patients, the average age was 62, arguably making them higher risk, and many of those patients were immunocompromised for a variety of reasons, including chemotherapy and cardiovascular disease. So how many of the 455 people were infected by the asymptomatic 22-year old woman?
“In summary, all the 455 contacts were excluded from SARS-CoV-2 infection...”
Said differently, exactly zero people were infected. The scientists, in typically understated fashion, offer up a comment about the question I hope you are asking yourself right now (namely, why are we all on lockdown if asymptomatic people with COVID-19 can’t spread the infection?), stating, “the result of this study may alleviate parts of the public concern about asymptomatic infected people.”
If this study had been published in early March, the odds that the world would have locked down are very, very low. Yet, this study, published only two weeks ago, is nowhere to be found in the media, and is never mentioned by policy makers. It just sits there, sharing the truth for anyone willing to listen.
Fact #4: Emerging science shows no spread of COVID-19 in the community (shopping, restaurants, barbers, etc.)
"There is no significant risk of catching the disease when you go shopping. Severe outbreaks of the infection were always a result of people being closer together over a longer period of time…”
- Professor Hendrick Streek , University of Bonn
We just learned that asymptomatic people infected with COVID-19 are very unlikely to be able to spread the infection to others. Emerging and published science shows transmission of COVID-19 in retail establishments is extremely unlikely. Professor Hendrik Streeck from the University of Bonn is leading a study in Germany on the hard-hit region of Heinsberg and his conclusions, from laboratory work already completed, is very clear:
Dr. Hendrick Streek
"There is no significant risk of catching the disease when you go shopping. Severe outbreaks of the infection were always a result of people being closer together over a longer period of time.
“When we took samples from door handles, phones or toilets it has not been possible to cultivate the virus in the laboratory on the basis of these swabs….”
Uh oh. You mean closing parks, closing stores, wearing gloves and masks at the grocery store, fumigating our groceries, and just being generally paranoid wasn't necessary? As Dr. Streeck confirms:
"It is important to obtain this data in order to make sure that decisions are taken based on facts rather than assumptions. The data should serve as a basis of information for the government so they can then think about their further course of action," he said.
And he continues:
“People could lose their jobs. They might not be able to pay their rent anymore and staying inside for a longer time can lead to weakening of our immune system.”
“The goal is not a complete containment of the virus. We need to know where the actual capacity limits of our hospitals are. How many infections are too many? What do intensive care medics say?”
And, finally:
“It is important to start thinking about a ‘rollback’ strategy and his hope is to “deliver the relevant facts so that people have a good foundation for their decisions.”
Fact #5: Published science shows COVID-19 is NOT spread outdoors
No. Just no.
In a study titled Indoor transmission of SARS-CoV-2 and published on April 2, 2020, scientists studied outbreaks of 3 or more people in 320 separate towns in China over a five-week period beginning in January 2020 trying to determine WHERE outbreaks started: in the home, workplace, outside, etc.? What’d they discover? Almost 80% of outbreaks happened in the home environment. The rest happened in crowded buses and trains. But what about outdoors? The scientists wrote:
“All identified outbreaks of three or more cases occurred in an indoor environment, which confirms that sharing indoor space is a major SARS-CoV-2 infection risk.”
Said differently, there’s really no science to support all the outdoor bans that my home state of Oregon and so many other states have put in place. I’ll leave you with my favorite quote from the study because it’s really quite infuriating to read when you consider some of the ways Governors here in the U.S have behaved (and some still do) by banning all sorts of outdoor activities, arresting paddle boarders on the water, etc.:
“The transmission of respiratory infections such as SARS-CoV-2 from the infected to the susceptible is an indoor phenomenon.”
Fact #6: Science shows masks are ineffective to halt the spread of COVID-19, and The WHO recommends they should only be worn by healthy people if treating or living with someone with a COVID-19 infection
Just today, the World Health Organization announced that masks should only be worn by healthy people if they are taking care of someone infected with COVID-19:
“If you do not have any repository symptoms such as fever, cough or runny nose, you do not need to wear a mask,” Dr. April Baller, a public health specialist for the WHO, says in a video on the world health body’s website posted in March. “Masks should only be used by health care workers, caretakers or by people who are sick with symptoms of fever and cough.”
Just before the COVID-19 madness, researchers in Hong Kong submitted a study for publication with the mouthful of a title, “Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Personal Protective and Environmental Measures.” Oddly, the study, just published this month, is actually housed on the CDC’s own website, and directly contradicts recent advice from the CDC about wearing a mask. Namely, the study states:
“In our systematic review, we identified 10 RCTs that reported estimates of the effectiveness of face masks in reducing laboratory-confirmed influenza virus infections in the community from literature published during 1946–July 27, 2018….In pooled analysis, we found no significant reduction in influenza transmission with the use of face masks…Our systematic review found no significant effect of face masks on transmission of laboratory-confirmed influenza….Proper use of face masks is essential because improper use might increase the risk for transmission.”
English translation: there is no evidence that wearing masks reduces the transmission of respiratory illnesses and, if masks are worn improperly (like when people re-use cloth masks), transmission could actually INCREASE. Moreover, this study was a meta-analysis, which means it dug deep into the archive of science (all the way back to 1946!) to reach its conclusions. Said differently, this is as comprehensive as science gets, and their conclusions were crystal clear: masks for the general population show no evidence of working to either slow the spread of respiratory viruses or protect people.
Sigh
This study is far from the only one to reach this conclusion (which makes the choice of a grocery store chain like my beloved New Seasons to make masks mandatory for all customers really quite unbelievable). The purpose of science is to arbitrate these thorny issues and while the science is clear, the hysteria continues. It turns out, the effectiveness of masks has a long history of debate in the medical community, which explains why so much science has been done on the topic. I will just highlight a few studies before you fall asleep:
My favorite article is actually a review of much of the science and it’s a great place to start for anyone who likes to do their own research. Titled, “Why Face Masks Don’t Work: A Revealing Review”, it was written to challenge the need for dentists to wear face masks, but all the science quoted and conclusions drawn apply to airborne pathogens in any setting. Some of the best quotes:
“The science regarding the aerosol transmission of infectious diseases has, for years, been based on what is now appreciated to be ‘very outmoded research and an overly simplistic interpretation of the data.’ Modern studies are employing sensitive instruments and interpretative techniques to better understand the size and distribution of potentially infectious aerosol particles…The primary reason for mandating the wearing of face masks is to protect dental personnel from airborne pathogens. This review has established that face masks are incapable of providing such a level of protection.”
And my favorite quote:
“It should be concluded from these and similar studies that the filter material of face masks does not retain or filter out viruses or other submicron particles. When this understanding is combined with the poor fit of masks, it is readily appreciated that neither the filter performance nor the facial fit characteristics of face masks qualify them as being devices which protect against respiratory infections. ”
Here’s an article published in ResearchGate by noted Canadian physicist D.G. Rancourt, written directly in response to the COVID-19 outbreak, published last month. Titled, Masks Don't Work: A review of science relevant to COVID-19 social policy.
“Masks and respirators do not work. There have been extensive randomized controlled trial (RCT) studies, and meta-analysis reviews of RCT studies, which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses, or respiratory illnesses believed to be transmitted by droplets and aerosol particles. Furthermore, the relevant known physics and biology, which I review, are such that masks and respirators should not work. It would be a paradox if masks and respirators worked, given what we know about viral respiratory diseases: The main transmission path is long-residence-time aerosol particles (< 2.5 μm), which are too fine to be blocked, and the minimum-infective-dose is smaller than one aerosol particle.”
To put this in simple terms: in order for a mask to really be effective that covered both your nose and mouth, you would asphyxiate. The minute the mask allows you to breathe, it can no longer filter the micro-particles that make you sick.
Finally, I often see this study from 2015 in the BMJ cited: “A cluster randomised trial of cloth masks compared with medical masks in healthcare workers", and it bears repeating, since MOST of the masks I see people wearing in the community right now are cloth masks. Not only are these masks 100% ineffective at reducing the spread of COVID-19, but they can actually harm you. As the researchers explain:
“This study is the first RCT of cloth masks, and the results caution against the use of cloth masks. This is an important finding to inform occupational health and safety. Moisture retention, reuse of cloth masks and poor filtration may result in increased risk of infection. Further research is needed to inform the widespread use of cloth masks globally.”
Increased risk of infection? Yes, that’s what it says. Other studies have also looked at the impact masks have on your oxygen levels (because you’re are forced to re-breathe your own Co2) and it’s not good. Scientists looked at oxygen levels of surgeons wearing masks while performing surgery and found: “Our study revealed a decrease in the oxygen saturation of arterial pulsations (SpO2) and a slight increase in pulse rates compared to preoperative values in all surgeon groups.”
Just this past week, this article came out in the New England Journal of Medicine, written my several doctors and public health officials with the title, “Universal Masking in Hospitals in the Covid-19 Era,” and this statement seems a perfect way to end my discussion of masks:
We know that wearing a mask outside health care facilities offers little, if any, protection from infection. Public health authorities define a significant exposure to Covid-19 as face-to-face contact within 6 feet with a patient with symptomatic Covid-19 that is sustained for at least a few minutes (and some say more than 10 minutes or even 30 minutes). The chance of catching Covid-19 from a passing interaction in a public space is therefore minimal. In many cases, the desire for widespread masking is a reflexive reaction to anxiety over the pandemic.
Fact #7: There’s no science to support the magic of a six-foot barrier
Iceland has already made the two-meter (6 foot) rule optional, according to this article. The reason for the recommendation to keep 6-feet of distance from your fellow citizens during the pandemic dates back to 1930, explained here by the BBC:
Umm…no
Where does the two-metre rule come from? Surprisingly, it can be traced back to research in the 1930s. Back then scientists established that droplets of liquid released by coughs or sneezes will either evaporate quickly in the air or be dragged by gravity down to the ground. And the majority of those droplets, they reckoned, would land within one to two metres. That is why it is said the greatest risks come from having the virus coughed at you from close range or from touching a surface - and then your face - that someone coughed onto. How conclusive is that?
Are you impressed with that science? Me neither. As this wonderful article explains:
A few early studies suggest that contaminated droplets could stay airborne for a few hours and pose a risk. But that research comes with a caveat: “While this research indicates that viral particles can be spread via bioaerosols, the authors stated that finding infectious virus has proven elusive and experiments are ongoing to determine viral activity in collected samples,” wrote Dr. Harvey Fineberg from the National Academies of Science, Engineering, and Medicine earlier this month.
It goes further:
And the commonly held fear that a random passerby will infect a stranger? Here’s more grade-school level talk from the CDC: “COVID-19 is thought to spread mainly through close contact from person-to-person in respiratory droplets from someone who is infected. People who are infected often have symptoms of illness. Some people without symptoms may be able to spread the virus [which science from China has proven is untrue].”
Not only would that sort of conclusion warrant a failing grade in any post-doctoral program, I am pretty sure the average eighth-grade science teacher would take a big red pen to that passage. “Thought.” “Some?” “May?” Keep in mind, there are no links to any scientific studies or papers for the average thinking person to review to decide whether those claims are legitimate.
The CDC also can’t quite make up its mind about the safety of large gatherings in the COVID-era. In mid-March, the agency asked Americans to limit gatherings of 250 people or more. A few weeks later, the White House, at the behest of the CDC, urged Americans to avoid gatherings of more than 10 people. There is no science, however, to support either number. (What is so fateful about 250 people? Why not 175? And why 10 people? Why not 16 or 17?)
The article takes dead aim at so many Governors who are absolutely running with these completely unsupportable recommendations:
Even that fuzzy advice has been bastardized by the petty tyrant lurking inside every big state governor, small-town mayor, and homeowners’ association president. Over the weekend, Michigan Governor Gretchen Whitmer banned people from going to a neighbor’s house. “All public and private gatherings of any size are prohibited,” Whitmer announced. “People can still leave the house for outdoor activities . . . recreational activities are still permitted as long as they’re taking place outside of six feet from anyone else.”…There will be plenty of soul-searching after this crisis abates: demanding to know the scientific rationale for keeping us six feet apart when people needed each other most should be at the top of the list.
Recently, one of the top scientific advisors in the UK to Prime Minister Boris Johnson has made the same point, his statements covered in the Daily Mail last week in an article titled, Government scientific adviser says Britain's two metre social distancing rule is unnecessary and based on 'very fragile' evidence. Professor Robert Dingwall stated:
‘I think it will be much harder to get compliance with some of the measures that really do not have an evidence base,’ he said. ‘I mean the two-metre rule was conjured up out of nowhere.’
When you digest all of the facts we now know about COVID-19, the simplest policy recommendation actually makes the most sense in my opinion: If you have COVID-19, stay home. If you must go out, wear a mask. Everyone else, wash your hands, and get on with your life. It should have been that easy, but instead we chose to lockdown society, an unprecedented step. Why?
Oh, and this is a real headline. God help us all.
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“The Lockdowns Were the Black Swan”
Indeed, why did we lockdown society, and has it worked? I stole the phrase above from an opinion piece in the Wall Street Journal written by Editorial Board member Holman W. Jenkins, Jr., I believe he captured it perfectly:
We started off sensibly. “This is not something [American families] generally need to worry about,” said CDC’s Dr. Nancy Messonnier in mid-January. “It’s a very, very low risk to the United States,” said Dr. Anthony Fauci a week later.Bill de Blasio, mayor of New York, urged residents to go about their business normally as recently as March 11.As coldblooded as it seems, these were the right statements at the time. Under “flatten the curve,” changes in public behavior aren’t needed until they are needed. Roll that around in your mind a bit. The better we do at equipping local hospitals, the less we need to bankrupt local businesses and their workers to slow the virus as it runs its course through society. That was the idea we started with. Not even the U.K. Imperial College study that so alarmed the world’s policy makers recommended indiscriminate lockdowns and shelter-in-place orders. If we meant what we said, we’ve overshot in many places. Beds are empty. A ventilator shortage did not materialize. We failed to set aside enough capacity to treat other medical conditions like strokes and heart attacks. This is costing lives.
What happened? From Bill Gates to your local editorialist, a new priority waddled to the fore. We decided that, whatever contributes to killing Americans at a routine total rate of 8,000 or so a day, it shouldn’t be the coronavirus.
Accidents, yes—6% of deaths. Heart disease, yes—23%. Flu and pneumonia, yes—2%.
These deaths are allowed but not deaths from the coronavirus even at the cost of economic ruin for millions. Of course the media and public are free to decide now they never wanted flatten the curve; they wanted to be spared the virus altogether. But explain how this is to be done. And explain why. The Economist magazine says we can’t restart the economy without an “unprecedented” $180 billion testing regime. Unprecedented is an interesting word because China, a country of 1.4 billion people with eight cities larger than New York, either must have developed such a system with nobody noticing or hasn’t found it necessary.
Why did we lockdown in the first place? Here are the facts.
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Fact #8: The idea of locking down an entire society had never been done and has no supportable science, only theoretical modeling
Dr. D.A. Henderson
In fact, the first time the idea was ever raised to lockdown everyone was in 2006, in this paper titled Targeted Social Distancing Designs for Pandemic Influenza. The paper detailed “how social contact network–focused mitigation can be designed” and modeled (more on that in a moment!) various outcomes based on how people behaved. At the time, cooler heads prevailed and criticized the ideas in the paper, notably this critique from Dr. D.A. Henderson, the man who led the public effort to eradicate smallpox. According to the New York Times:
Dr. Henderson was convinced that it made no sense to force schools to close or public gatherings to stop. Teenagers would escape their homes to hang out at the mall. School lunch programs would close, and impoverished children would not have enough to eat. Hospital staffs would have a hard time going to work if their children were at home.
The measures embraced by Drs. Mecher and Hatchett would “result in significant disruption of the social functioning of communities and result in possibly serious economic problems,” Dr. Henderson wrote in his own academic paper responding to their ideas.
The answer, he insisted, was to tough it out: Let the pandemic spread, treat people who get sick and work quickly to develop a vaccine to prevent it from coming back.
Soon after, Dr. Henderson and several other prescient colleagues penned an important paper encapsulating many of these ideas, Disease Mitigation Measures in the Control of Pandemic Influenza, including this astonishing (given what just happened) conclusion:
There are no historical observations or scientific studies that support the confinement by quarantine of groups of possibly infected people for extended periods in order to slow the spread of influenza. A World Health Organization (WHO) Writing Group, after reviewing the literature and considering contemporary international experience, concluded that “forced isolation and quarantine are ineffective and impractical.”2 Despite this recommendation by experts, mandatory large-scale quarantine continues to be considered as an option by some authorities and government officials.35,43
The interest in quarantine reflects the views and conditions prevalent more than 50 years ago, when much less was known about the epidemiology of infectious diseases and when there was far less international and domestic travel in a less densely populated world. It is difficult to identify circumstances in the past half-century when large-scale quarantine has been effectively used in the control of any disease.
And they ended with a sentence so important I’m going to use really big font:
The negative consequences of large-scale quarantine are so extreme (forced confinement of sick people with the well; complete restriction of movement of large populations; difficulty in getting critical supplies, medicines, and food to people inside the quarantine zone) that this mitigation measure should be eliminated from serious consideration.
If you’d like to read more about the origins of the lockdown idea and how it continued to circulate in public health circles, check out, “The 2006 Origins of the Lockdown Idea.” If you’d like to read more about Dr. D.A. Henderson, check out, “How a Free Society Deals with Pandemics, According to Legendary Epidemiologist and Smallpox Eradicator Donald Henderson.” Both articles are awesome and will make you sick to your stomach when you realize how many good scientists knew that a lockdown would be a disaster, and cost more lives than it could ever save.
You’re likely equally shocked to see that as late as 2019, the World Health Organization DIDN’T EVEN LIST the idea of a total lockdown in their report titled “Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza.” Here’s their table of 18 possible non-pharmaceutical measures for countries to take in a pandemic, note all the things listed under the “Not recommended in any circumstances” row that are now happening every day!
Obvious question: if there was no science to support a lockdown and we’d never actually done one before and many in public health said it would be a terrible idea, why did it happen? There’s really two answers as best I can tell. The first answer is that the World Health Organization, early on in the pandemic, chose to praise the Chinese response of locking down Hubei Province, which effectively served to legitimize the practice, despite the extreme limitations of data available to anyone about the Chinese lockdown’s actual effectiveness. This article discusses the issue, and raises the question:
What changed the WHO’s mind and prompted it to praise the response of the Chinese authorities in Hubei province, which included the virtual incarceration of 60 million people? It was this, more than anything else, that persuaded governments across the world to lockdown their citizens.
The second answer is that newly-created disease models scared the living daylights out of world leaders, and the modelers stood ready to offer a simple solution to their made-up numbers: lock everything down, NOW!
Fact #9: The epidemic models of COVID-19 have been disastrously wrong, and both the people and the practice of modeling has a terrible history
While many disease models have been used during the COVID-19 pandemic, two have been particularly influential in the public policy of lockdowns: Imperial College (UK) and the IHME (Washington, USA). They’ve both proven to be unmitigated disasters.
Imperial College: It’s safe to say that the reason the United States locked down, and the reason the White House extended their lockdowns was almost exclusively due to the models created by Imperial College Professor Neil Ferguson. As the Washington Post explained:
Officials have said the Imperial College’s eye-popping 2.2 million death projection convinced Trump to stop dismissing the outbreak and take it more seriously. Similarly, officials said, the new projection of 100,000 to 240,000 deaths is what convinced Trump to extend restrictions for 30 days and abandon his push to reopen parts of the country by Easter, which many health experts believe could have worsened the outbreak.
Oddly, Professor Ferguson has a history of massive overestimation of pandemics, but apparently no one bothered to consider that in taking his advice. The Spectator spelled out his incredibly bad calls on three previous emerging diseases (he actually has more terrible calls, I’m just highlighting three):
2002, Mad Cow Disease:
In 2002, Ferguson predicted that between 50 and 50,000 people would likely die from exposure to BSE (mad cow disease) in beef. He also predicted that number could rise to 150,000 if there was a sheep epidemic as well. In the UK, there have only been 177 deaths from BSE.
2005, Bird Flu:
In 2005, Ferguson said that up to 200 million people could be killed from bird flu. He told the Guardian that ‘around 40 million people died in 1918 Spanish flu outbreak… There are six times more people on the planet now so you could scale it up to around 200 million people probably.’ In the end, only 282 people died worldwide from the disease between 2003 and 2009.
2009, Swine Flu:
In 2009, Ferguson and his Imperial team predicted that swine flu had a case fatality rate 0.3 per cent to 1.5 per cent. His most likely estimate was that the mortality rate was 0.4 per cent. A government estimate, based on Ferguson’s advice, said a ‘reasonable worst-case scenario’ was that the disease would lead to 65,000 UK deaths. In the end swine flu killed 457 people in the UK and had a death rate of just 0.026 per cent in those infected.
I don’t know, don’t you think that history should have mattered more before relying on his model to lock down our entire country? It actually gets worse. From the National Review:
Johan Giesecke, the former chief scientist for the European Center for Disease Control and Prevention, has called Ferguson’s model “the most influential scientific paper” in memory. He also says it was, sadly, “one of the most wrong.”
And more:
Jay Schnitzer, an expert in vascular biology and a former scientific direct of the Sidney Kimmel Cancer Center in San Diego, tells me: “I’m normally reluctant to say this about a scientist, but he dances on the edge of being a publicity-seeking charlatan.”
One simple example of how wrong the Imperial College model was would be Sweden, here’s the details:
Indeed, Ferguson’s Imperial College model has been proven wildly inaccurate. To cite just one example, it saw Sweden paying a huge price for no lockdown, with 40,000 COVID deaths by May 1, and 100,000 by June. Sweden now has 2,854 deaths and peaked two weeks ago. As Fraser Nelson, editor of Britain’s Spectator, notes: “Imperial College’s model is wrong by an order of magnitude.”
And, finally:
Indeed, Ferguson has been wrong so often that some of his fellow modelers call him “The Master of Disaster.”
Oh, and Professor Ferguson recently resigned from his position because he broke lockdown curfew…to have an affair with a married woman. I’ll end with a quote from the man who I believe will emerge as the biggest hero of this whole mess, Sweden's Anders Tegnell, the man who chose not to lock his country down:
One person who’s skeptical of Professor Ferguson’s modeling is Anders Tegnell, the epidemiologist who’s been advising the Swedish Government. “It’s not a peer-reviewed paper,” he said, referring to the Imperial College March 16th paper. “It might be right, but it might also be terribly wrong. In Sweden, we are a bit surprised that it’s had such an impact.”
IHME: If the Imperial College model was really the motivation for both President Trump, Boris Johnson, and then many other world leaders to lockdown, the IHME models have almost always been the “science” state Governors cite to demonstrate how many lives their lockdowns are saving. It’s a nice gig, really. Find a model that massively overestimates the deaths in your state, lock it down, and then have the modelers show you how many lives you have saved. Luckily, other scientists have been watching, and the IHME model has received one of the most ferocious beat-downs I have ever seen in the scientific literature from Professors at the University of Sydney, Northwestern, and UTEP. Titled, Learning as We Go – An Examination of the Statistical Accuracy of COVID-19 Daily Death Count Predictions and released last week, the study effectively says that the IHME model is dangerously inaccurate, but in a somewhat cordial, scientific way. The authors write:
Specifically, the true number of next day deaths fell outside the IHME prediction intervals as much as 76% of the time, in comparison to the expected value of 5%. Regarding the updated models, our analyses indicate that the April models show little, if any, improvement in the accuracy of the point estimate predictions.
And then they land the big punch:
Our analysis calls into question the usefulness of the predictions to drive policy making and resource allocation.
In English: the IHME models are so bad at forecasting they shouldn't be relied upon for anything. Need more? National Review’s Andrew McCarthy was very eloquent all the way back on April 9th in criticizing the IMHE models’ inaccuracy and uselessness:
The model on which the government is relying is simply unreliable. It is not that social distancing has changed the equation; it is that the equation’s fundamental assumptions are so dead wrong, they cannot remain reasonably stable for just 72 hours. And mind you, when we observe that the government is relying on the models, we mean reliance for the purpose of making policy, including the policy of completely closing down American businesses and attempting to confine people to their homes because, it is said, no lesser measures will do.”
And how does Mr. McCarthy, a senior fellow at the National Review Institute, think these models have performed?
“To describe as stunning the collapse of a key model the government has used to alarm the nation about the catastrophic threat of the coronavirus would not do this development justice.”
My own Governor here in Oregon, Kate Brown, is fond of invoking the phrase that she is “following the science.” Recently, a Circuit Court overturned her lockdown order after a lawsuit was filed from a number of churches. Governor Brown released this statement:
From the beginning of this crisis, I have worked within my authority, using science and data as my guide, heeding the advice of medical experts. This strategy has saved lives and protected Oregonians from the worst of the COVID-19 pandemic.
What “science” is Governor Brown relying upon? The IHME model. Still think that’s “science”?
Finally, Michael Fumento wrote an excellent article arguing that “After Repeated Failures, It’s Time To Permanently Dump Epidemic Models.” As he explains:
The models essentially have three purposes: 1) To satisfy the public’s need for a number, any number; 2) To bring media attention for the modeler; and 3) To scare the crap out of people to get them to “do the right thing.” That can be defined as “flattening the curve” so health care systems aren’t overridden, or encouraging people to become sheeple and accept restrictions on liberties never even imposed during wars. Like Ferguson, all the modelers know that no matter what the low end, headlines will always reflect the high end. Assuming it’s possible to model an epidemic at all, any that the mainstream press relays will have been designed to promote panic.
unabated.
About the author: J.B. Handley is the best-selling author of How to End the Autism Epidemic. He graduated with honors from Stanford University, and currently serves as a Managing member of Bochi Investments, a private investment firm. He can be reached at jbhandleyblog@gmail.com
LOCKDOWN LUNACY: the thinking person's guide - May 30 2020
By J.B. Handley
https://jbhandleyblog.com/home/lockdownlunacy