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One of the more bizarre things that have happened related to the COVID-19 pandemic is the way that antivaccine activists have formed an unholy alliance with COVID-19 conspiracy theorists. On the other hand, it might seem bizarre to those not familiar with antivaccine pseudoscience, but it actually makes perfect sense to those of us who have been following the antivaccine movement for a long time, for the simple reason that all antivaccine pseudoscience is based on conspiracy theories. So it isn’t much of a surprise that someone I’ve been following for a very long time (16 years!) has gone all-in on COVID-19 conspiracy theories. I’m referring to J.B. Handley, the man who, with his wife, founded Generation Rescue, an antivaccine group dedicated to the now refuted hypothesis that mercury in vaccines causes autism. When last we met him three years ago, he was once again attacking vaccine science and spewing his usual antivaccine misinformation. Before that, he was known for misogynistic attacks on female journalists writing about antivaxxers and attacks against defenders of science in general. These days, he’s posting his pseudoscience on the website of Robert F. Kennedy, Jr.’s antivaccine group Children’s Health Defense in an article entitled “LOCKDOWN LUNACY: The Thinking Person’s Guide.” It’s useful to examine, because it’s basically a cornucopia of COVID-19 misinformation, disinformation, and conspiracy theories.

Handley’s article is constructed based on what he calls “facts.” As is so frequently the case with articles of this sort, his sixteen “facts” are a mixture of facts (deceptively presented), nonsense, and “sort-of” facts that are partially true, all used to cast doubt on the conventional narrative about COVID-19. All of them are basically cherry picked claims. Before I dig in, let me just mention something about J.B. Handley. He is not a scientist of any sort. He’s a businessman who co-founded and co-managed Swander Pace Capital, a private equity firm, until retiring in early 2014. He has no background in science, immunology, autism, infectious disease, vaccines, or, of course, COVID-19. Moreover, he’s known for his admiration of antivaccine icon Andrew Wakefield, whom he likens to “Nelson Mandela and Jesus Christ rolled up into one.” None of that stops him from engaging in his usual nonsense of the sort that I’ve been commenting on since 2005. So, with that history in mind, let’s dig in. Here’s his first “fact”:

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%.

Here, I like to cite Carl T. Bergstrom, a professor of biology, whose Twitter feed is essential reading (if you’re on Twitter) in this era of COVID-19. He notes that this claim is false, both in its estimate of how low the COVID-19 infection fatality rate is and on what the infection fatality rate is of typical seasonal flu. For instance, Handley cites John Ioannidis’ much-criticized (and rightfully so) seroprevalence study carried out in Santa Clara County, California that claimed to have found that the number of people who’d been infected with SARS-CoV-2 in the California county of Santa Clara was 50 to 85 times higher than previously thought, elevated numbers that suggested that the vast majority of COVID-19 were milder than previously thought and that the infection fatality rate was much lower than previously thought. The problems with this study are summarized here, here, and here, but the bottom line is that it examined a biased sample. As Bergstrom notes, the best estimates range of the infection fatality rate of COVID-19 range from 0.5% to 1.5%:

Unsurprisingly, Handley also cites Dr. Scott Atlas, a Fellow at the Hoover Institution of Stanford University, a well-known conservative think tank known for downplaying the severity of COVID-19 and opposing lockdowns as a strategy to slow the spread of COVID-19. One notes that Dr. Atlas is a neuroradiologist and has no particular expertise in infectious disease or epidemiology. His entire shtick is to argue that COVID-19 is no big deal, that the risk of dying from it is so low that radical measures to stop it are not indicated.

Next up:

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

This is true, but the proper response to this is: So What? Handley basically uses these data to argue that it’s only old people who are dying; so closing schools makes no sense. There is an argument to be made that, because children are much less likely to become severely ill from COVID, school closures should be reconsidered, there is still a lot of uncertainty in this area. He cherry picks a single study suggesting that schools in Ireland are not a driver of COVID-19 spread, and runs with it. At least he concedes that older teachers and school employees might have something to fear.

Handley goes on:

Fact #3: People infected with COVID-19 who are asymptomatic (which is most people) do NOT spread COVID-19

As is Handley’s usual practice, he cherry picks a single case and a single study. There is actually abundant evidence that presymptomatic or asymptomatic individuals can spread COVID-19. For example, Eric Topol and Daniel Oran reviewed the evidence by examining a number of cohorts with COVID-19, finding that, yes, around 40% of COVID-19 cases are asymptomatic but also finding that asymptomatic patients can drive transmission:

Asymptomatic persons seem to account for approximately 40% to 45% of SARS-CoV-2 infections, and they can transmit the virus to others for an extended period, perhaps longer than 14 days. Asymptomatic infection may be associated with subclinical lung abnormalities, as detected by computed tomography. Because of the high risk for silent spread by asymptomatic persons, it is imperative that testing programs include those without symptoms. To supplement conventional diagnostic testing, which is constrained by capacity, cost, and its one-off nature, innovative tactics for public health surveillance, such as crowdsourcing digital wearable data and monitoring sewage sludge, might be helpful.

While it’s not entirely clear if completely asymptomatic COVID-19 patients who never develop symptoms transmit COVID-19 less frequently than presymptomatic people (those who ultimately do go on to develop symptoms), there is little doubt that asymptomatic people, whether they do or don’t go on to develop symptoms, do transmit COVID-19.

Next up:

Fact #4: Emerging science shows no spread of COVID-19 in the community (shopping, restaurants, barbers, etc.)

I laughed at this one. “Emerging” science shows no such thing. Handley’s claim is based on interviews with a single German scientist in Business Insider and RTL Today. As Bergstrom notes, Handley confuses the absence of evidence for the evidence of absence, noting that community spread while shopping or doing other activities out in public is much harder to track down via contact tracing methodology than spread among co-workers, family members, and the like, because there is no easy way to figure out who was in the store or other facility at the same time and connect spread that way. We also know that spread by respiratory droplets is important, which supports the spread of the disease whenever humans are in close contact.

Handley then goes on to lie:

Fact #5: Published science shows COVID-19 is NOT spread outdoors.

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.

Actually, the very study cited demonstrated that transmission outdoors is actually possible. Also, not surprisingly, Handley ignores studies that do show outdoor transmission of coronavirus. One such study (caution: on a preprint server) estimates that the chance of transmission of COVID-19 in a closed environment is 18.7 times greater compared to an open-air environment (95% confidence interval. It’s probably true that transmission is considerably less likely outdoors, but it’s nonsense to claim that COVID-19 is not spread outdoors.

“Fact #6” amuses me, given the topic of last week’s post:

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.

And:

Fact #7: There’s no science to support the magic of a six-foot barrier.

I covered both of these issues in detail last week. Masks work. Social distancing of 1-2 meters works. I don’t feel a compelling need to cover the same ground again here. Handley is, as is usual for him, full of crap on this issue. He even repeats old World Health Organization recommendations as though they were new. In fairness to Handley, the WHO hadn’t updated its recommendations when it was originally written, but oddly enough, he hasn’t mentioned that the WHO has changed its recommendations on wearing masks to recommend that people over 60 and people with underlying medical conditions should wear a medical-grade mask when they’re in public and cannot socially distance, while the general public should wear a three-layer fabric mask in those situations.

Next up:

Fact #8: The idea of locking down an entire society had never been done and has no supportable science, only theoretical modeling.

And:

Fact #10: The data shows that lockdowns have NOT had an impact on the course of the disease.

This is one of those claims that’s sort of true, but misleading. We haven’t faced a pandemic like that of COVID-19. I’m particularly amused, though, how Handley cites the WHO as not having a total lockdown on its list of pandemic mitigation measures as late as 2019. He cites a report entitled Non-pharmaceutical public health measures for mitigating the risk and impact of epidemic and pandemic influenza. He even reproduces this table:

Under “extraordinary measures”, workplace measures and closures are listed, as are internal travel restrictions. Those are basically the building blocks of our current lockdown. Unsurprisingly, Handley can’t help but blame it on the Chinese:

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.

One can argue whether lockdowns go too far, but recent studies in Nature (ignored by Handley, of course) suggest that pandemic lockdowns are responsible for dramatically decreasing community transmission of coronavirus and having prevented tens of millions of infections and having saved millions of lives. In fairness, these studies were released after Handley’s article was published, but, again, Handley has updated his article but only with cherry picked material that (he thinks) supports his viewpoint. Oddly enough, he hasn’t updated it with these studies.

Handley also cites a report that COVID-19 was circulating widely in the US many months earlier than previously thought. This claim is not supported by molecular biology and has not been confirmed.

Handley also relies on a report from that noted institution with expertise in infectious disease and epidemiology, J.P. Morgan. Unsurprisingly, being a finance man himself, he thinks that this is a reason to take it seriously:

I’m going to start with a source that you might consider unusual, the global bank JP Morgan. Of all the facts I have covered, this one about the ineffectiveness of lockdowns has become the most politicized, because it’s being used to begin playing the blame game. JP Morgan, on the other hand, creates their analysis to do something very nonpartisan: make money. Their analysts crunch data to see which economies are likely to restart first, and you shouldn’t be surprised at this point to discover three things: 1) the least damaged economies are the ones that did the lest [sic] onerous lockdowns, 2) lifting lockdowns has had no negative impact on deaths or hospitalizations, and 3) lifting lockdowns had not increased viral transmission. Reading the JP Morgan conclusions is profoundly depressing, because here in the U.S. many communities are STILL being put through many different lockdown mandates, despite overwhelming evidence to their ineffectiveness. Consider this chart from JP Morgan that shows “that many countries saw their infection rates fall rather than rise again when they ended their lockdowns – suggesting that the virus may have its own ‘dynamics’ which are ‘unrelated’ to the emergency measures.”

Yes, because J.P. Morgan is out to make money, Handley considers its views more credible than those of scientists. Never mind that the report wasn’t public. Never mind that the data used to come up with the conclusions were never made public. Never mind that the report was not peer-reviewed. Personally, I like this retort the best:

Now, let’s go back to…

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.

Handley attacks Neil Ferguson for previous estimates that turned out (to him, at least) to be overestimates, such as for Mad Cow Disease, but it’s rather bizarre. Ferguson’s estimate had a huge error range, and the actual number of deaths from the disease fell in that range. You can argue that such huge uncertainty in the estimates make the estimates rather useless, but Ferguson wasn’t exactly wrong. Handley also cherry picks the worst case scenarios estimated by Ferguson for deaths from bird flu in 2005 and H1N1 in 2009 and concludes that, because the ultimate numbers of deaths were far lower than worst case scenarios, that Ferguson is not to be trusted.

In any event, the Imperial College model for COVID-19 did indeed estimate that there would be 2.2 million US deaths if the pandemic proceeded to herd immunity uncontrolled and 1.1 million US deaths if it went through to herd immunity with controls in place. Bergstrom notes that we’ve put massively intrusive controls in place but have had nearly 120,000 deaths anyway, while only around 5% of the population has been infected. At that rate, if 50% of the population goes on to be infected, we could easily top one million deaths.

Handley also attacks the IHME model, which has a lot of problems, correctly pointing out that it performed poorly. However, as Bergstrom notes, the model actually underestimated the number of US deaths.

Onwards:

Fact #11: Florida locked down late, opened early, and is doing fine, despite predictions of doom.

At the risk of relying too heavily on Bergstrom:

Next up:

Fact #12: New York’s above average death rate appears to be driven by a fatal policy error combined with aggressive intubations.

This is partially true. It is true that COVID-19 took a huge toll in nursing homes in New York. However, the bit about “aggressive intubations” is a misrepresentation of a controversy in how to manage COVID-19 patients requiring mechanical ventilation that turned into a conspiracy theory that “ventilators are killing COVID-19 patients”. Basically, way back in early April (which, these days, seems like ancient history), an emergency medicine doc named Dr. Cameron Kyle-Sidell produced a YouTube video in which he questioned how ventilators were being used to treat COVID-19 patients. His concerns were mainly that doctors were too fast to place patients on a ventilator and that they were using ventilator settings for acute respiratory distress syndrome (ARDS). One of the key characteristics of ARDS is that the lungs become noncompliant (stiff) as part of the inflammatory process that impairs their ability to exchange oxygen. Consequently, high ventilatory pressures are often needed, specifically positive end expiratory pressure (PEEP), the pressure at the end of expiration, which helps keep the alveoli (air sacs) open.

Although Dr. Kyle-Sidell’s video was treated as though it were a shocking revelation that proved that doctors don’t know what they’re doing when it comes to treating COVID-19, in reality what he was saying wasn’t anything that radical at all. It also seemed to reveal an ignorance of how COVID-19 was actually being treated in ICUs at the time. Dr. Rohin Francis wrote a great article on MedPage Today entitled “The Great Ventilator Fiasco of COVID-19“, where he noted that the “very core principle of ventilating a patient is to reduce oxygen and pressure being delivered as much as possible. ITU [intensive treatment unit] nurses are experts at doing exactly this and it’s been an absolute fundamental of management for decades.” Basically, Handley doesn’t know what he’s talking about here and is mixing a legitimate criticism of New York’s handling of nursing home cases of COVID-19 with nonsense about ventilators killing patients.

Next up:

Fact #13: Public health officials and disease epidemiologists do NOT consider the other negative societal consequences of lockdowns.

I’m with Carl Bergstrom here. This one is straight up nonsense. Public health officials frequently consider these issues, but they do so in the context of modeling disease.

Handley can’t stop, though:

Fact #14: There is a predictive model for the viral arc of COVID-19, it’s called Farr’s Law, and it was discovered over 100 years ago.

Farr’s law basically states that the number of cases per day in viral outbreaks follow a bell-shaped curve. The problem is that Farr’s law isn’t always accurate. For instance, using Farr’s law to predict the the size of the AIDS epidemic resulted in a massive underestimation of the true scope of the epidemic. It also turns out that the IMHE model that Handley attacked used Farr’s law to model the size of the COVID-19 outbreak in the US and failed badly by underestimating it.

Next up, a prediction, not a fact:

Fact #15: The lockdowns will cause more death and destruction than COVID-19 ever did.

This is a common talking point among COVID-19 deniers. Of course, the correct comparison is not the current lockdown versus the pre-COVID-19 pandemic situation, but rather what would have happened if there were no lockdown and coronavirus were allowed to run unchecked through the US population. Unsurprisingly, Handley cherry picks quotes from some lockdown opponents that don’t take into account how much reduced economic activity there likely would have been due to behavioral changes among Americans in the setting of an uncontrolled pandemic.

Finally:

Fact #16: All these phased re-openings are utter nonsense with no science to support them, but they will all be declared a success.

This, too, is a prediction and not a fact. It remains to be seen if this will be true. He continues:

Yup, still waiting for your Phase 1 or Phase 2 re-opening? Trust me, whomever conjured up your state’s plan is quite literally making things up as they go along. And, given the extreme range of plans taking place—even in neighboring counties—the odds that they have ANYTHING to do with the arc of the virus is exactly ZERO, but you already knew that if you read this far. The good news is they will ALL succeed, because we never needed to lockdown in the first place—MISSION ACCOMPLISHED.

I’ll give Handley some credit. For some states, he’s not entirely wrong. That doesn’t excuse the mass of nonsense that preceded his last “prediction”. On the other hand, he is wrong when it comes to many states, including my own state of Michigan.

I first “met” J.B. Handley over 15 years ago, when he was the founder of Generation Rescue, an organization that promoted the discredited idea that mercury in the thimerosal preservative that used to be in several childhood vaccines caused autism. It’s the same organization that Jenny McCarthy went on to become president of. I guess I shouldn’t be surprised that in the era of COVID-19 he’s still promoting pseudoscience.

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Posted by David Gorski

Dr. Gorski's full information can be found here, along with information for patients. David H. Gorski, MD, PhD, FACS is a surgical oncologist at the Barbara Ann Karmanos Cancer Institute specializing in breast cancer surgery, where he also serves as the American College of Surgeons Committee on Cancer Liaison Physician as well as an Associate Professor of Surgery and member of the faculty of the Graduate Program in Cancer Biology at Wayne State University. If you are a potential patient and found this page through a Google search, please check out Dr. Gorski's biographical information, disclaimers regarding his writings, and notice to patients here.