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Fact #5: This Is Probably The Last Time We Lock The World Down For A Virus — But Only If We Learn Our Lesson
“[The government’s anti-COVID-19 measures] are grotesque, absurd and very dangerous […] The life expectancy of millions is being shortened. The horrifying impact on the world economy threatens the existence of countless people. The consequences on medical care are profound. Already services to patients in need are reduced, operations cancelled, practices empty, hospital personnel dwindling. All this will impact profoundly on our whole society.
All these measures are leading to self-destruction and collective suicide based on nothing but a spook.”
– Dr. Sucharit Bhakdi, medical doctor and specialist in microbiology, one of the most cited research scientists in German history.
I’ve made the case that our reaction to COVID has been gravely exaggerated. COVID is a virus that is especially deadly to older people with pre-existing conditions, and virtually harmless to everyone else. And if that wasn’t enough, COVID will likely end up with a fatality rate similar to the seasonal flu.
Wait — why did we lock up the world again?
Harvard Professor of the Culture of Medicine David S. Jones, MD, PhD might have some answers — which he published early in this pandemic in the New England Journal of Medicine:
History suggests that we are actually at much greater risk of exaggerated fears and misplaced priorities. [emphasis mine] There are many historical examples of panic about epidemics that never materialized (e.g., H1N1 influenza in 1976, 2006, and 2009). There are countless other examples of societies worrying about a small threat (e.g., the risk of Ebola spreading in the United States in 2014) while ignoring much larger ones hidden in plain sight.
The data proves that our reaction to COVID has been (and still is in some countries) based on the flawed assumption that COVID is the next Spanish Flu. One could argue that early in this crisis there might have been worrying indications pointing in this direction… but for at least 2 months it’s been clear that our worst fears would never come true.
But where did this assumption come from? What triggered such fear? Why did everyone become convinced that COVID could result in millions of deaths?
In this section, we’ll explore how the decision to lock a third of the planet down came to be, whether the lockdowns were effective or not, what consequences the lockdowns will have on society and what lessons should be learned from this crisis.
5.1 First Lesson: The Epidemic Model That Made A Third of The Planet Panic Was Completely & Dangerously Flawed
In a Business Insider article, award-winning reporter Bill Bostock explains that one mathematical model coming from a team led by Professor Neil Ferguson, head of the department of infectious disease epidemiology at Imperial College London (ICL) greatly influenced how most of the world reacted to the COVID pandemic:
On March 16, around a month after the earlier interview, Ferguson delivered a bombshell 20-page paper to UK Prime Minister Boris Johnson. The message was clear: 510,000 people could die if the government didn’t abandon its current strategy of allowing the disease to spread. […]
On March 23, the UK scrapped “herd immunity” in favor of a suppression strategy, and the country made preparations for weeks of lockdown. Ferguson’s study was responsible. [emphasis mine]
[Ferguson’s] simulations have been influential in other countries as well, cited by authorities in the US, Germany, and France.
Ferguson’s study predicted that if the US did nothing, more than 2.2 million Americans would die (March 17th). It also predicted that if the UK did nothing, 510,000 people would die. The same team predicted that if left unchecked, COVID could kill more than 40 million people worldwide.
The paper predicted that hospitals would be overwhelmed, and recommended mitigation strategies to “flatten the curve” (suppression of the virus) which included population-wide social distancing, home isolation of cases, and closing down schools and universities. The researchers indicated that “these policies would need to be maintained until large stocks of vaccine are available to immunise the population – which could be 18 months or more.” [emphasis mine]
They also admitted that if both the US and the UK applied these mitigation strategies to the very letter for more than a year, we would still see 1.1-1.2 million deaths in the US, and more than 250,000 in the UK.
To be clear: The ICL did not recommend a global lockdown. Politicians took that decision seemingly out of sheer political pressure coming from a panicked public.
A) Ferguson’s (Imperial College London/ICL) model was based on borderline ridiculous assumptions
The predictions above were obviously overblown, considering that the US currently has 100,000 alleged COVID deaths, while the UK has around 37,000 (Johns Hopkins tracker, May 26th).
The ICL got it terribly wrong. But why?
Models can only be as good as the assumptions they’re based on. And as renowned Stanford scientist, John Ioannidis, put it, “some of the major assumptions and estimates that are built in the [ICL’s] calculations seem to be substantially inflated”.
Here are some examples of glaring mistakes in the ICL paper that have now been identified by experts worldwide:
- It made the false assumption that no country would increase their ICU capacity. Like many other countries, Sweden was able to double its capacity in just 10 days, and eventually triple its overall ICU capacity. Giesecke, one of the two epidemiologists who leads Sweden’s COVID response, commented that “the paper completely overlooks [that fact]”.
- It made the false assumption that the overall fatality rate of COVID would end up being 0.9%, ignoring the fact that there already was strong evidence coming out of China that a large fraction of all COVID cases were asymptomatic. At the same time, analyses from top researchers, like John Ioannidis, were demonstrating that the infection fatality rate (IFR) would likely be closer to 0.3%. In mid-March, Ioannidis called the global reaction to COVID a possible scientific “fiasco in the making”.
- It made the ridiculous assumption that 81% of the entire population would be infected. As a comparison, “even the deadly ‘Spanish Flu’ (H1N1) pandemic of 1918–19 infected no more than 28% of the U.S. population. The next H1N1 ‘Swine Flu’ pandemic in 2009-10, infected 20-24% of Americans” (source).
- It made the false assumption that the number of COVID cases and/or deaths would keep doubling every three or four days for months on end (exponential growth). In reality, starting from the very beginning the curve of new cases started to bend, indicating that COVID would unsurprisingly follow a curve similar to all prior respiratory viruses before it (more on the topic soon when I’ll talk about Farr’s law).
- It made the false assumption that the elderly would not be isolated to minimize the number of infections in this at-risk population. The nursing homes were hit badly, but overall every country did their best to do just the opposite and isolate risk groups. (Note: Most of them failed to do so, considering around 50% of all COVID deaths in most countries come from nursing homes).
When you stack all these false assumptions, you get a false result. An overblown prediction, and an equally overblown reaction. Yes — “models are just models”, but this model was completely flawed from the get go, and should never have been used as a basis for health policies that impact billions of people.
I didn’t personally fully grasp how wrong Ferguson’s predictions were was until I saw these two graphs:
Image credit: Lockdownsceptics.org
This first graph shows what the ICL paper predicted would happen in Sweden. Lockdownsceptics.org explains what this graph means:
In case you can’t read the small print, the blue area is the daily deaths per 100,000 the Imperial model would have predicted in the “do nothing” scenario, the yellow area is what would have happened if Sweden had stuck with mitigation – which is what it did, obviously [emphasis mine] – and the red area is the actual number of Swedes who’ve died.
A Swedish research group from the University of Uppsala applied the ICL model to Sweden, and found out that Sweden was supposed to have 40,000 COVID deaths shortly after May 1st. As of May 16th, the alleged number of deaths from COVID is 4,125.
Image source: Alberta COVID-19 Update, April 28th 2020
Canada has also been greatly influenced by the ICL paper, as the COVID-related hospitalizations projections made in the Province of Alberta clearly demonstrate. The tiny gray bars at the bottom are actual hospitalizations, a fraction of their lowest prediction.
B) Even when data became available, decision-makers clinged to the dreadful ICL model
Models are just predictions of what “could be”. Data corresponds to what is actually happening. Reality.
As the pandemic progressed, it became increasingly clear that the ICL predictions were completely wrong. When I dove into this whole madness in early March and started writing my first COVID article (published on April 1st 2020), it was already very clear that the COVID data didn’t justify the amount of Corona-Panic experienced worldwide — which was equally comforting and disturbing to me.
On March 23rd, the UK announced a complete reversal of their strategy — and decided to lockdown the entire country instead of following mitigation strategies similar to the Swedish approach.
Then two days later, on March 25th, something bizarre happened. Ferguson appeared in front of the UK Parliament’s Science and Technology Committee and said that he now predicted that only 20,000 people would die from COVID. He also stunningly admitted that up to two thirds of those who died from COVID would have died anyway in a short timeframe, but from other causes.
He later explained that his “new” lower death toll prediction (20,000 instead of 510,000) was no retraction of his original predictions. The 20k deaths corresponded to a “best case scenario” presented in the original ICL paper. Ferguson said that considering the UK was under lockdown and that the mitigation strategies seemed to be working already (after two days?!), that scenario was now plausible. Many people raised an eyebrow over these arguments. The UK kept its lockdown going, still wanting to avoid the infamous 510k deaths worst-case-scenario.
The ICL paper greatly influenced the US response, even though the US CDC had actually predicted a very heavy death toll (1.7M) in the US if nothing was done a few days prior to its release.
The problem is this: Over the following weeks, even as the US death toll projection started crumbling, politicians did not walk back on their policies that were based on exaggerated and now clearly unrealistic predictions.
On March 26th, Dr. Deborah Birx, the White House’s Coronavirus Response Coordinator, admitted during a press conference that COVID death toll modeling the US government was using simply didn’t make sense (Note: I could not find a single media outlet who reported on this quote below):
The predictions on the model don’t match the reality on the ground.
We are about 5 times the size of Italy. If we were Italy and you did all these divisions, Italy should have close to 400,000 deaths. They’re not close to achieving that. [emphasis mine] These are the kinds of things we’re trying to understand…
When Birx made that admission, Italy only had 8,215 COVID deaths — miles away from the 400,000 deaths that the models predicted.
Let me state this again: More than two whole months ago (ages during this crisis), it was already clear that the mathematical models used in the US were overestimating the Italian death toll by more than 48X, and surely overestimating COVID-related hospitalizations, COVID cases, and the need for ventilators.
But nothing was done, and the death toll predictions crumbled over the next few weeks, as the data became clearer:
- March 13: 1.7M deaths if we do nothing (CDC model)
- March 17: 2.2M deaths if we do nothing (ICL model)
- March 26: Dr. Birx admits “predictions on the model don’t match the reality on the ground.”
- March 29: 100-200k deaths
- April 2: 178k deaths (full social distancing through May, IHME model)
- April 5: 136k deaths (full social distancing through May, IHME model)
- April 7: 82k deaths (full social distancing through May, IHME model)
- April 8: 60k deaths (full social distancing through May, IHME model)
The IHME (Institute for Health Metrics and Evaluation — an independent global health research center at the University of Washington) has been the main model adopted since early April, and it now predicts that “relaxing social distancing” will increase the death toll to more than 147k in the US by early August. We’ll see in a minute why lifting the lockdown is probably not the culprit for this potential increase.
C) Ferguson has a devastating track record
I was completely speechless when I realized that the Ferguson who made apocalyptically-wrong predictions for COVID is the same Ferguson that has made equally apocalyptically-wrong predictions several times in the past.
Ferguson argues that he prefers “to be accused of overreacting than under-reacting.” He has been staying true to his word:
- 2001: Ferguson predicts that the foot and mouth disease would cause a disaster in UK cattle, leading to the pre-emptive killing of more than 10 million animals, and costing more than £10M to UK taxpayers. The real number of cases? 2026. Some experts argue that the crisis was an “abuse of mathematical models” and “scientific opportunism”.
- 2002: Ferguson predicts that the mad cow disease (BSE) could kill up to 150,000 people in the UK. The real death toll? 177.
- 2005: Ferguson predicts the Bird Flu would kill 200M people worldwide, citing the 1918 “Spanish” flu outbreak. The real death toll? 440. (440 people, not millions)
- 2009: Ferguson predicts the Swine Flu (H1N1) outbreak would kill 65,000 in the UK, and works with the WHO to predict that it’ll kill millions worldwide. The real death toll? 457 in the UK, and 18,500 confirmed deaths worldwide. [The real death toll from H1N1 is still unclear and up for debate. Later studies claimed the real death toll was over 200,000, but further investigation by reporter Sharyl Attkisson revealed that the vast majority of presumed H1N1 infections in the US were in fact H1N1-negative, a fact that the CDC had hidden. Ignoring these revelations, the CDC still claims to this day that there has been 14-34M cases of H1N1 in the US that year].
- 2020: Ferguson misses the mark by a mile, once again, with the COVID crisis. This time, however, the consequences of being off mark are way more devastating.
An article in National Review highlights that, “Ferguson has been wrong so often that some of his fellow modelers call him ‘The Master of Disaster’”. As investigative reporter Jon Rappoport summed up perfectly: “Why would anyone believe what Ferguson has been predicting in this COVID hustle?”
If Ferguson and his collaborators have gotten it so wrong in the past, what measures have they put in place to ensure this doesn’t happen again? No one seems to know, and the situation leaves us with more questions than answers.
All we know is that up until Ferguson was pressured into making his mathematical models public (see point D) ), the code was kept in a black box, far away from scrutiny by his peers. We also know that the ICL paper — to be fair, like most papers during this fast-paced pandemic — had not been peer-reviewed.
D) Ferguson’s mathematical models are a coding disaster
The moment Ferguson was pressured into releasing his code to the open source development platform GitHub, things started to look even more ridiculous.
Many senior software engineers, like this one who worked at Google for 8 years, reviewed the code and described it as “amateur work”, “scary”, and “riddled with bugs”.
A few highlights include:
- This is not the original code, and has “been upgraded for over a month by a team from Microsoft and others.” For the moment Ferguson has not responded to requests to release the real original code that led to the predictions found in the March 16th ICL paper.
- Due to bugs, the code can produce very different results given identical inputs. “They routinely act as if this is unimportant”.
- “The program gives different results if it is run on different machines [emphasis mine] — according to a team at Edinburgh University which ran the model”. (source)
A reviewer concluded that the ICL paper and all policies that were based on it should immediately be retracted:
All papers based on this code should be retracted immediately. Imperial’s modelling efforts should be reset with a new team that isn’t under Professor Ferguson, and which has a commitment to replicable results with published code from day one.
On a personal level, I’d go further and suggest that all academic epidemiology be defunded. This sort of work is best done by the insurance sector. Insurers employ modellers and data scientists, but also employ managers whose job is to decide whether a model is accurate enough for real world usage and professional software engineers to ensure model software is properly tested, understandable and so on. Academic efforts don’t have these people, and the results speak for themselves.
This is surely not the final word on the code that was used in the ICL paper, but is extremely concerning. As a journalist in the Telegraph brilliantly put it: “Did we base one of the biggest peacetime policy decisions on crude mathematical guesswork?”
I personally hate all the “tabloid drama” around the story, but cannot fail to mention the fact that Ferguson himself broke the lockdown rules when he decided to continue seeing his lover in person, claiming he believed he was “immune to [COVID]”. He unfortunately showed poor judgment and hinted that he himself might not fully agree with the Corona-Panic that was fueled by his recent work.
After this scandal went public, he resigned from the UK government’s scientific advisory group (SAGE) on May 5th.
Everywhere in the world, people still stuck with a serious case of Corona-Panic keep clinging to the idea that we have saved “millions of lives”, that “lockdowns worked”, or were even “necessary”. There’s no way that we did all this for nothing… right?
Politicians want to save face, and keep repeating that meme. On April 16th, Trump repeated that “models predicted between 1.5 and 2.2 million deaths”, and claimed that since the US has around 100,000 deaths from COVID, it logically means the lockdown saved 2 million lives.
In the Province of Quebec, Canada, health officials vaguely stated a few weeks ago that we have saved 30 to 60,000 lives, not citing any source to back up that claim. Later, they changed their tune to “thousands of lives” that have been saved, a PR message that has been repeated multiple times during a massive TV show called “Une chance qu’on s’a” (Rough translation from French: We’re lucky to have each other) — which has been watched by 24% of all Quebeckers (2M people) on May 10th.
Do these statements truly hold ground? Were global lockdowns effective and necessary?
A) The overblown models were never true in the first place
Did the US save 2 million lives? Of course they didn’t. The 2.2M figure which came from the ICL paper was completely overblown.
If you believe they did, please answer this one: Did Sweden save 36,000 lives, considering the ICL predicted they would see 40,000 deaths by May 1st, while in reality they had around 4,000? The answer: No, they didn’t.
In 2005, Ferguson predicted the Bird Flu would kill 200M people worldwide. The death toll was 440 people in total, worldwide. Did we save 199,999,560 lives? No, we did not.
Alan Reynolds, senior fellow at the Cato Institute, sums it up:
The British model that once postulated a scenario in which 2.2 million U.S. lives could be at risk was simply wrong, and references to it should stop.
B) In many countries, infections peaked before lockdowns were imposed
The goal of imposing global lockdowns was to aggressively flatten the curve — keep the number of COVID infections low in order to avoid overwhelming the hospital system, and avoid the excess deaths that could have occurred by the lack of proper medical care.
It’s a strategy that has never been adopted this widely, and that could have technically worked if it had been done sooner. But considering that COVID was already spreading widely weeks sooner than everyone previously thought, lockdowns came too late in the game to make a significant difference.
In fact, in many countries, the number of COVID cases (if you take the number of cases at face value, that is) peaked before lockdowns were imposed.
Alistair Haimes from The Critic explains how we can use basic math to verify if lockdowns really decreased the number of infections:
First, we are told that the average time from becoming infected to showing symptoms is about 5 days: the “incubation period”. Secondly, we are told that the average time from symptoms to death is 18 days.
Armed with just those two numbers, 5 and 18, and no maths skills more complex than addition and subtraction, let’s look at the experience of China, Italy and the US to check that we really can see a “hockey-stick” in the infection curves 5 days (incubation period) after lockdown measures were introduced.
Just, you know, to verify that the lockdown theory actually works, given that a quarter of the planet is now under lockdown with the world economy in a coma and an unprecedented suspension of civil liberties. It seems worth some back-of-the-envelope double-checking.
Image source: The Critic
Despite the weird blip on 1 February, this classic bell-shaped epidemic curve (the blue lines) shows a clear peak in symptom-onset around 25 January, implying an infection-peak (subtracting 5) around 20 January. But hang on: lockdown proper in Hubei (the lion’s share of cases) wasn’t until 23 January, so this implies that the curve was already turning down before they declared the lockdown. [emphasis mine]
Professor Knut Wittkowski, who headed the Rockefeller University’s Department of Biostatistics, Epidemiology, and Research Design for 20 years, agrees with this assessment, and previously explained in an interview (that has now been “shockingly” taken down by YouTube) that infections in the whole country of China peaked around February 1st to 5th, while schools closed 2 weeks later, on February 20th.
Image source: The Critic
Again, a classic epidemic curve, with a peak of symptom-onset 10–13 March, implying (subtracting 5 days) an infection-peak 5–8 March: too early for the turn in the graph to have been caused by the lockdown announced on 9 March.
Image source: The Critic
Finally, in the US, CDC data suggests that cases peaked around 26-30 March, implying an infection-peak (subtracting 5 days) around 21-25 March – before most stay-at-home orders had been issued.
Some estimate that this peak happened even earlier. Prof. Wittkowski considers that the US peak of hospitalizations for all flu-like illnesses (including COVID) happened on March 18th, and that the peak of infections in the US was around March 8th — way before lockdown measures were imposed.
Image source: Coronavirus Task Force press briefing, April 17th 2020.
Image source: Robert Koch Institute
Lockdown Sceptics explains that the same phenomenon has been seen in Germany:
This chart from the Robert Koch Institute shows that by March 23rd, when the German Government imposed its most severe lockdown measures, the reproduction figure was already below 1, meaning the number of new infections was declining.
In addition, it shows that in the following weeks, after the lockdown was in place, the R figure didn’t decline any further. So the lockdown didn’t result in any additional reduction of new cases. [emphasis mine]
Reproduction rate in Switzerland. Image source: ETH/Vernazza
As reported by SPG:
The Swiss chief physician of infectiology, Pietro Vernazza, uses the results of the German Robert Koch Institute and ETH Zurich to show that the Covid19 epidemic was already under control before the “lockdown” was even introduced:
‘These results are explosive: Both studies show that simple measures such as the renunciation of major events and the introduction of hygiene measures are highly effective. The population is able to implement these recommendations well and the measures can almost bring the epidemic to a halt. In any case, the measures are sufficient to protect our health system in such a way that the hospitals are not overburdened’.
In Norway, health officials recently admitted that the lockdown was unnecessary to tame COVID, since that R0 had fallen to close to 1 before it was imposed on March 12:
Our assessment now, and I find that there is a broad consensus in relation to the reopening, was that one could probably achieve the same effect – and avoid part of the unfortunate repercussions – by not closing.
But, instead, staying open with precautions to stop the spread. This is important to admit, because if the infection levels rise again – or a second wave hits in the winter – you need to be brutally honest about whether lockdown proved effective.
For South Korea, Wittkowski explained (source here, censored interview) that both in the city of Daegu and nationally, infections peaked just a few days after measures were imposed. He concludes:
Both in China and South Korea, social distancing started only long after the number of infections had already started to decline, and therefore it had very little impact on the epidemic. [emphasis mine] That means they had already reached herd immunity.
Image source: Prof. Knutt Wittkowski
In a recent study, Wittkowski also analyzed the peak of infections in Spain and concluded:
In Spain, 2020 excess mortality exceeded projections for only four weeks (Fig 16), starting on the same day as the main shutdown (03-14). As infections must have started and peaked about three weeks earlier, the shutdown may have hastened the decline (Fig 12), but couldn’t [have] caused much “flattening” of the curve, which also has the normal, narrow, 4-week width.
In other words, nature ran its course, and the peak of COVID infections followed a pattern similar to all other respiratory infections before it.
Image source: Daily Mail
The Daily Mail reported that Professor Carl Heneghan, Oxford Professor of Evidence-Based Medicine, claims that the peak of infections in the UK happened before the lockdown, and that simple measures like handwashing and social distancing dramatically reduced the spread of COVID:
A leading expert at the University of Oxford has argued the peak was actually about a month ago, a week before lockdown started on March 23, and that the draconian measures people are now living with were unnecessary.
Professor Carl Heneghan claims data shows infection rates halved after the Government launched a public information campaign on March 16 urging people to wash their hands and keep two metres (6’6″) away from others.
The fact that the COVID-19 line (in green) goes up after the UK started imposing measures might indicate a strong confirmation bias: More doctors started diagnosing COVID instead of other respiratory infections, and the number of tests started increasing as the UK plunged into this crisis.
Another graphic put together by independent media Off Guardian shows that the number of new infections in the UK started decreasing 3 weeks before Boris Johnson announced a countrywide lockdown:
Image source: Off Guardian
C) The virus ran its “normal” course virtually regardless of interventions that were taken, and Farr’s law still holds true
As Carl Heneghan and Tom Jefferson from the Oxford’s Centre for Evidence-Based Medicine states, “[William] Farr showed that epidemics rise and fall in roughly a bell-shaped curve (a normal distribution) shape”.
Farr’s law is a well-known phenomenon in epidemiology: “What goes up must come down”.
In early March, I found an article on Medium where author and self-proclaimed optimist David Paul Kirkpatrick asked a simple question: “Why Are We Ignoring Farr’s Law of Epidemics?”. He also said that based on the fact that China had likely already seen its peak of infections, “coronavirus should be gone by this summer”.
Obviously , he got slammed in the comments section with “This post is irresponsible” and “This guy has no background in medicine or epidemiology”.
Two months later, it’s obvious that COVID is no “unprecedented” virus, and that it follows the same course as pretty much all other respiratory infections before it — the bell-shaped curve that William Farr had identified almost 200 years ago.
I’ve picked the examples from Europe, where the data is more mature. Image source: Singapore University of Technology and Design (SUTD) Data-Driven Innovation Lab (last updated May 7th)
Military scientist Prof. Isaac Ben-Israel has also demonstrated that “simple statistics show the spread of the coronavirus declines to almost zero after 70 days — no matter where it strikes, and no matter what measures governments impose to try to thwart it” (source).
Ben-Israel explains his analysis further:
Given the data, it is imperative to elaborate on what caused the decline in the number of new infections. Some may claim that the decline in the number of additional patients every day is a result of the tight lockdown imposed by the government and health authorities. Examining the data of different countries around the world casts a heavy question mark on the above statement.
It turns out that a similar pattern – rapid increase in infections that reaches a peak in the sixth week and declines from the eighth week – is common to all countries in which the disease was discovered, regardless of their response policies: some imposed a severe and immediate lockdown that included not only “social distancing” and banning crowding, but also shutout of economy (like Israel); some “ignored” the infection and continued almost a normal life (such as Taiwan, Korea or Sweden), and some initially adopted a lenient policy but soon reversed to a complete lockdown (such as Italy or the State of New York). Nonetheless, the data shows similar time constants amongst all these countries in regard to the initial rapid growth and the decline of the disease. [emphasis mine]
Image source: Prof. Ben-Israel
Sharing the graphic above, Ben-Israel explains that “Certainly, a full complete lockdown reduces the spread of the virus. However, as the above data shows, there is an apparent similar decline in the rate of infection even in countries that did not enforce a full shutdown”.
He concludes that “Given that the evidence reveals that the Corona disease declines even without a complete lockdown [emphasis mine], it is recommendable to reverse the current policy and remove the lockdown”.
D) There’s no correlation between the severity of COVID-related interventions and the number of COVID cases or deaths
As reported by Iain Davis in Off Guardian:
In terms of limiting infection rates, there is no discernible benefit to lockdown regimes. In fact, Oxford University found a direct correlation between infection rates and the relative severity of lockdown regimes. It suggests the more stringent the lockdown, the higher the infection rate. [emphasis mine]
Image source: Off Guardian
This is not unexpected, as numerous epidemiological studies have shown that infection rates for C19 are higher when people are exposed to it for prolonged periods in confined spaces. Locking people up in their homes is probably the worst thing you could do if you wanted to reduce the infections and the duration of the outbreak.
The same dire findings hold true for COVID deaths — there are basically no indications that lockdowns and more drastic measures reduced the overall COVID death toll.
This graphic shared in a presentation by the Numis Securities (investment banking) Healthcare Research Team demonstrates how non-lockdown countries fare compared to lockdown countries when it comes to COVID deaths per million population:
Deaths per million in various countries. In orange, lockdown countries. In black, non-lockdown countries.
Image source: Numis Securities Research
Around the world, several experts in mathematics or statistics came to the exact same conclusion:
- Scientist T.J. Rodgers
- Prof. Ramesh Thakur, Crawford School of Public Policy, Australia
- Prof. Michael Levitt, winner of the 2013 Nobel in Chemistry
- Prof. Karol Sikora, the Founding Dean and Professor of Medicine at the University of Buckingham Medical School and an ex-director of the WHO Cancer Programme
- Prof. Yoram Lass, former director of Israel’s Health Ministry
- Author and political scientist Wilfred Reilly
I’ll just comment on the last one since I could write 20 more pages here if I’m not careful. Reilly followed his April 22nd article with a second article in which he clearly demonstrates that more than two weeks later, “lockdowns still aren’t working”.
When I wrote my last piece for spiked, the US states overall had an average of 54 Covid-19 deaths per million persons. The social-distancing states, with South Carolina counted as a social-distancing state, had an average of 12 Covid deaths per million.
As of today, that figure has jumped to 147 deaths per million for all US states (126 per million minus New York), and 34 per million for social-distancing states. Deaths per million have increased by 22 in the social-distancing states, and by 72 to 93 in the lockdown states, during only the past two weeks. This gap in new, post-lockdown deaths per million people once again suggests that the lockdowns are not working. [emphasis mine]
Technology entrepreneur and Havard MBA Yinon Weiss came to the exact same conclusion after comparing data from 50 US States, Spain, Italy, France, UK and Sweden:
Image source: Yinon Weiss
Weiss concluded that: “There is no general correlation between how fast a State shut down and how many people died in the first 3 weeks following an early mortality milestone.”
Statistician William M. Briggs has been creating similar graphics which also clearly show that countries with no lockdown are in general way better off:
COVID deaths per million in various countries In orange: lockdown countries. In green: non-lockdown countries. Image source: William H. Briggs
Briggs stresses that comparing data from one country to another in a fair manner is next to impossible — there are vast differences in compliance towards mitigation measures, state of health of the population (existence of pre-existing conditions or lack thereof), different definitions of what constitutes a COVID case or a COVID death, the quality and capacity of the medical system, the kind of interventions that were used on COVID-positive patients, the age of the population, and many more. So what can we make of all of this?
What should we conclude? Strike that. What can we conclude. Only one thing: we cannot conclude that lockdowns worked.
The only evidence for lockdowns is the desire that lockdowns worked. That, and the embarrassment (and worse) in admitting to error. [emphasis mine] What politician anywhere will [cope] with ruining their economy and the lives of millions of their citizens? Who can say ‘Ah, it was only a few trillion’? This will not happen. It just won’t. All politicians will and must go on repeating that their lockdowns “saved lives”.
Finally, Joel Hay, PhD pointed out that the COVID data coming out from US prisons confirms that lockdowns haven’t made a difference in excess deaths:
The lockdowns did not cause or prevent the April spike in excess deaths. If the lockdowns mattered then prisons (90% C19 seropositive, crammed together like sardines) would have peaked earlier.
E) Lockdowns were never meant to, cannot and will not eliminate COVID from the surface of the planet
The lockdown narrative went south somewhere in the midst of this Corona-Panic.
The initial justification for a lockdown was a desire to “flatten the curve” and dramatically lower the number of COVID infections in order to avoid hospitals from getting overwhelmed. The horror show coming from Northern Italy that had been all over the media was enough to make any politician sweat bullets. The pressure to act now, not later, was crushing.
But very rapidly, it became clear that the vast majority of hospitals worldwide were not overwhelmed — and had been preparing for a Ferguson-level catastrophic health crisis that never came.
Statistician William H. Briggs explains that as of May 12th, “ER volumes are down about 40% to 50%. So much for overwhelming the system”.
Sen. Scott Jensen, MD recently warned that the medical system in the United States is under serious financial difficulties — because of a lack of patients:
The initial rationale was ‘we need to flatten the curve, we need to build up our preparation so that we don’t overwhelm our hospital facilities’. Right now most hospitals […] they’re dying on the vine. Occupancy rates are 25%, we’re losing $31M a day in hospitals.
We have flattened the curve. We have pushed the peak down. We have adequate hospital capabilities now. If we’ve done the things that we’ve said we wanted to do, then why would we continue to lock down? There’s no reason to.
Even in New York City, the effects of the initial overblown predictions are obvious. After treating just 179 patients in 3 weeks, the 500-bed US Navy ship that was setup to prepare for the worst left on April 22nd because of a lack of patients.
Journalist Alex Berenson reported that on that same date, Ohio hospitals were losing $42M a day, which “implies a loss of about $1.2 billion a day — $36 billion a month — for hospitals nationally”.
Iain Davis reported that on April 10th:
Close to half of the UK’s hospital beds were empty. With just 60% of acute beds occupied this is 30% less than this time last year. In the same period last year the NHS was creaking under the pressure of demand, prompting then Prime Minister Theresa May to suggest scrapping NHS targets. […]
The Health Service journal (HSJ) reports that the NHS has four times as many empty beds as normal. Confirming that more than 40% of acute beds are unoccupied. Even in London, the alleged epicentre of the C19 pandemic, that figure is still nearly 29%.
A total of 9 temporary hospitals have now shut down because of a lack of patients, something that has been called a “heroic failure” by science journalist Rob Lyons.
Again, this will vary from country to country, but overall it’s clear that hospital systems prepared for a tsunami which never came. Other examples include:
- Switzerland: started furloughing medical staff in early April because of the lack of patients
- Germany: In early April, German intensive care units also showed “no increased occupancy.” (SPR) Some German hospitals had vacancy rates of up to 70%.
- Canada: Around mid-April, doctors said they were “still waiting for [the] feared surge of COVID-19 patients”.
To be fair: Hospitals have partially been empty because elective (non-urgent) procedures have been postponed, because ICU beds have been cleared and patients sent elsewhere (like in nursing homes, which was a huge mistake) and also because a lot of people have started avoiding hospitals out of fear.
But the fact remains that the curve was basically flat from the start, and that COVID never had the ability to overwhelm medical systems in the vast majority of cases.
Instead of re-adjusting our view of this virus — and admitting that the models were a complete hyperbole, both citizens and politicians did the exact opposite, and pushed towards longer lockdowns.
“Flattening the curve” became “every life matters”. For a lot of citizens — and I’m talking about my personal experience with people locally here in Quebec — it became “we will win this fight against COVID — we will kill the virus if we stay locked inside our homes long enough”. Most people also ended up wanting to avoid COVID like the Plague, and wanting their children to avoid getting COVID at all costs.
As Stanford scientist Dr. Jay Bhattacharya reminded everyone in a recent interview, “lockdowns are not a technique for disease elimination”. The main goal of a lockdown was — in theory — not to reduce the total number of COVID infections, but to spread these infections over time. The truth is that these infections were already spread very thin in the first place.
F) Data from non-lockdown countries cannot possibly co-exist with the idea that we saved “millions of lives”
If lockdowns have saved millions of lives, then why did Sweden, Taiwan, Belarus, South Korea and multiple other countries not experience a massive death toll? Hint: That’s because lockdowns haven’t saved many lives — if any.
Let’s focus on the Swedish example since this one has sparked a lot of controversy around the world.
Throughout the pandemic, mainstream media and Corona-Panic-stricken folks tried to argue that Sweden’s response to COVID was a “dangerous bet”, “Russian roulette”, and “leading [citizens] to catastrophe”. They were heavily criticized by scientists from all around the world, including 22 scientists based in Sweden.
But as I’ve explained in my first COVID article, lockdowns simply do not have a scientific basis. Swedes were not the ones running a dangerous experiment; the lockdown countries were. And they failed.
Let me be clear: Sweden’s approach was not to do nothing; far from it. They focused on several evidence-based ways to minimize the spread of COVID:
- Social distancing on a voluntary basis
- No gatherings of more than 50 people
- No bar service
- Distance learning in high schools and universities
- Trying to isolate the elderly and protect nursing homes, although by their own account they failed miserably (like most other countries, since 50-70% of all deaths come from nursing homes)
They avoided: Harsh controls, policing, fining, location-tracing tech, or global lockdown. Along with some other non-lockdown countries, they made sure their citizens experienced a version as close as possible to “normal life”:
Swedes having a picnic, eating a meal at their local restaurant and celebrating a graduation, in the midst of the Corona-Panic.
Image credit: New York Times, ‘Life Has to Go On’: How Sweden Has Faced the Virus Without a Lockdown, April 28th 2020.
The Swedes did not see 40,000 of their citizens die to COVID like Ferguson had predicted. They reached a plateau of COVID infections on April 13th and it has been declining since. Their hospitals were never overwhelmed, just like it has been the case in the vast majority of hospitals around the world. And we can argue that their economy suffered less than countries who imposed a lockdown, although this is still up to speculation.
When it comes to COVID deaths, it’s often pointed out that Sweden has a higher number of deaths per million compared to their neighboring countries, like Denmark. That’s true. However, what is not being said is that this difference is barely statistically significant, and would hardly justify a lockdown — considering how destructive and deadly lockdowns themselves are (more on this soon — in 5.3).
Political writer and global affairs analyst Patrick Henningsen recently commented on this (May 1st):
Sweden, which has a population of roughly 10.5 million, has recorded 21,092 cases and 2,586 fatalities from COVID-19, that’s roughly 256 deaths per million people. By contrast, its southern neighbor Denmark which has a population of 5.8 million has recorded 9,1058 cases and 452 fatalities, roughly 78 deaths per million persons. Norway [has] a similar population at 5.4 million, and has recorded 7,738 cases and 210 deaths, that’s 39 deaths per million. Finland [who] has a population of 5.5 million confirmed just 4,995 cases and 211 deaths, with 38 deaths per million.
Critics of Sweden have all seized upon these differences in order to condemn their government for being ‘irresponsible’ and “playing Russian roulette” with their citizens’ lives. If one didn’t know better from all the hysterical rhetoric, you’d think there was an impending genocide happening there. While these sort of polemic arguments seem to work in the narrow band of reality that are social media threads, the reality is that after scaling up its neighbors’ results to be in line with Sweden’s larger population which is roughly twice their size, the difference is statistically insignificant for a country of 10.5 million. [emphasis mine]
They are basically arguing that when comparing Sweden to its neighbor Denmark, that a proportional difference of approximately 1,500 fatalities warrants Sweden closing all its schools and shutting down its entire economy and suffering all the chaos and ill effects that goes with that course of action.
Note: As of May 26th, Sweden now has 4,125 alleged COVID deaths (392/M), compared to 563 in Denmark (102/M). Also important to mention: “Sweden has won praise in some quarters for preserving at least some semblance of economic normalcy and keeping its per capita death rate lower than those of Belgium, France, Italy, the Netherlands, Spain, and the United Kingdom”.
What might change the world’s view on the Swedish approach is the fact that they might be close to reaching “Herd Immunity” — a breaking point where a large enough percentage of the entire population is immune to a virus, which makes it naturally unable to spread widely.
Senior scientist Johan Giesecke previously claimed that Stockholm would achieve herd immunity by mid-May, but the latest calculations by Stockholm University mathematician Tom Britton shows “that 40 percent immunity in the capital could be enough to stop the virus’s spread there and that this could happen by mid-June.”
It’s still debated whether herd immunity is really something that can be achieved with COVID, but if it can, then countries who have not locked down and let the virus run its course will likely fare much better in the long run.
In the end, the results in Sweden and other non-lockdown countries like Belarus, South Korea, Taiwan, Iceland and Japan demonstrate that lockdowns were not necessary and definitely did not “save millions of lives”. Journalist Daniel Hannan recently said that “if Sweden succeeds, lockdowns will all have been for nothing” — and he was unfortunately quite right.
Sweden’s approach has — kind of ironically — been appraised by the World Health Organization on April 29th, when Dr. Mike Ryan said: “I think if we are to reach a new normal, Sweden represents a model if we wish to get back to a society in which we don’t have lockdowns. [emphasis mine]”
I’m a humanist, so when I hear “Every life matters” — at first I kind of agree with the premise.
But the extremely dangerous reality is that the vast majority of people who used this phrase during the COVID pandemic didn’t really understand its true meaning. Not even close.
If every life really mattered, it would mean that throughout this entire crisis, decision-makers would have taken into consideration how their interventions (like lockdowns) would impact the health of every citizen — not just those who get COVID.
Dr. David Katz, former director of the Yale-Griffin Prevention Research Center, is one of the few experts who’s been openly talking about this devastatingly ignored issue:
There is more than one way for this pandemic contagion to hurt people. It can hurt them directly via infection, and it can hurt them indirectly via our responses to the contagion. [emphasis mine]
And both are bad, preventing both is good, and we should be gathering more data […] to navigate between those two perils.
But… are we actually gathering more data on the health consequences of a global lockdown? Are we openly looking at both sides of this grim equation?
There’s a lot of modeling being done about the coronavirus. I don’t see anyone modeling the health effects of what we’re doing to the economy…
You cannot engage in cost-benefit analysis unless you know the costs!
In the current climate, merely bringing up the topic makes you a corona-heretic. If you argue that we also need to think about the economy, you get accused of favoring money over people.
But this is not a debate of money vs lives — it’s lives vs lives. Decades of scientific data clearly show that economic crises, or even just isolation itself will kill people. A lot of them.
In this section, I’ll barely scratch the surface, but will try my best to point out a few ways that this overreaction to COVID, global lockdowns and their related economic crises might lead to an excess death toll:
A) Unprecedented rise in unemployment
In early April, The Guardian reported that COVID-related lockdowns (affecting nearly 3.5 billion people worldwide) will wipe out 6.7% of all working hours worldwide in the second quarter. This is equivalent to the loss of a whopping 195M jobs.
Extremely poor people will be hit the most — and “forecasts now predict 35 to 65 million people will slide into absolute poverty as a result of the global recession. And many of them face starvation” (source).
In my previous article (published April 1st) I was already concerned that 3.3M Americans (1% of the population) had filed for unemployment in a single week, beating the previous record of 695,000 (0.3% of the population at the time) in October of 1982 by a very large margin.
A few weeks later, this number has now climbed by 10-fold — now standing at 36 million (although there are indications the real number might be closer to 50 million, since millions of Americans haven’t been able to file unemployment claims).
Source: Department of Labor unemployment insurance weekly claims report April 30th, 2020. Image Credit: Connie Hanzhang Jin/NPR
The Fed had estimated in late March that up to 47M Americans could lose their job, and that the overall unemployment rate could rise up to 32%. At the moment, that curve is not about to flatten.
Things are expected to be dire for a long while. “The Congressional Budget Office has forecast that the unemployment rate will still be 9.5% by the end of next year.” (source)
In a country where 78% of workers said they lived “paycheck to paycheck” prior to the COVID crisis, it’s easy to see why many financial experts predict an economic crisis that’ll be much worse than anything we’ve seen before.
The same has been seen around the world. In Australia, underemployment and unemployment rates have skyrocketed. In the UK, half of all adults are now paid by the State. The government had already invested 100B pounds to bailout businesses at the beginning of May.
B) “Deaths of despair”: Economic crashes, unemployment and poverty literally kill people
Okay, these are “just jobs”. But the urgent problem we’re facing is that a rise in unemployment is directly correlated with a rise in suicides, homicides and several other causes of deaths — a phenomenon often called “deaths of despair”.
Political economist Toby Rogers, PhD, explains:
There is a large volume of academic literature on “the social determinants of health” and “deaths of despair” caused by increases in the unemployment rate. The pioneering work in this field was conducted by Harvey Brenner (then at Johns Hopkins University) on behalf of the Joint Economic Committee of the United States Congress in the mid 1970s. Reviewing U.S. historical data over the period 1940 to 1973, Brenner found that:
‘… a 1% increase in the unemployment rate sustained over a period of six years has been associated (during the past three decades) with increases of 36,887 total deaths, including 20,240 cardiovascular deaths, 920 suicides, 648 homicides, 495 deaths from cirrhosis of the liver, 4,227 state mental hospital admissions, and 3,340 state prison admission’.
Based on the Brenner model, Rogers currently predicts that unemployment alone will kill anywhere from 300,000 to more than 1.8M Americans in the long run:
Lower bound. If the unemployment rate increases by 5 points as a result of the various lockdowns, then 294,170 additional lives will be lost, not from coronavirus, but from deaths of despair.
Mid-range. If the unemployment rate increases by 16.5 points (as predicted by Treasury Secretary Mnuchin), then 970,761 additional lives will be lost to deaths of despair.
Upper bound. And if the unemployment rate increases by 10-fold — which is what we are already seeing in several states — then 1,853,271 lives will be lost to deaths of despair from government orders to lock down, shut down, and shelter in place.
It’s impossible to predict how many deaths of despair we’ll see emerge around the world because of COVID-related lockdowns, but it’s already plausible that this toll will be astronomically greater than deaths from COVID itself (around 350k alleged COVID deaths worldwide as of May 26th, Johns Hopkins tracker).
Estimates about these deaths of despair range widely, and are based on modeling — so remember to take those with at least a grain of salt. Still, many researchers and analysts agree that this toll will be substantial:
- A recent study by the nonprofit Well Being Trust in the US says that we may see up to 75,000 additional deaths of despair from suicide, drug and alcohol abuse.
- A highly respected 1982 academic research book “Corporate Flight: The Causes and Consequences of Economic Dislocation” by Bluestone, Harrison and Baker estimates that every additional 1% rise in unemployment causes 37,000 excess deaths (including 20,000 heart attacks, 920 suicides, 650 homicides) and 4,000 mental hospital admissions and 3,300 state prison admissions.
- Investment research firm Ionosphere Capital estimates that “a 31% increase in unemployment (47M) with a lockdown extending through May will result in a doubling of drug overdoses (69,735) and an additional 15,137 suicides. Together, these account for 84,872 layoff-related deaths”.
There are already strong indications that these deaths of despair have already started increasing:
I’ve seen various reports that mental health and suicide hotlines have exploded in the last several weeks. In the US State of Indiana, the number of calls made to the “211 hotline” has increased by 2,000% according to Family and Social Services Administration Secretary Dr. Jennifer Sullivan.
Figures vary widely, but Stanford scientist John Ioannidis has also claimed that each bump of 1% in unemployment normally leads to a 1% increase in suicides.
Other data points to consider include:
- Suicides have doubled in the French department of Creuse
- Suicide centers in the UK have seen an extensive increase in the number of people coming in with thoughts of self-harm or suicide
- Previous studies have linked economic crises with a significant rise in suicides. If we apply the math found in this study, and that the rise in suicides is equivalent to the Great Depression, we could expect the economic devastation related to COVID lockdowns to cause an additional 26,400 suicides per year
- Mara Grunau, executive director of the Centre for Suicide Prevention in Calgary, Canada, expects a rise in suicides within 12 to 18 months because of of the COVID-related economic crash
- A very recently published 2020 study revealed that the 2008 economic crash led to a significant increase in suicides in the US
- Dr. Mike deBoisblanc, head of trauma at the John Muir Medical Center in Walnut Creek, USA, said in a recent interview: “We’ve never seen numbers like this, in such a short period of time. I mean we’ve seen a year’s worth of suicide attempts in the last four weeks.”
Mental health issues
Just Facts has compiled a massive amount of scientific data on mental health and considers that our reaction to the global mental toll of COVID might end up being way more far-reaching than the death toll from the virus itself:
Based on a broad array of scientific data, Just Facts has computed that the anxiety created by reactions to Covid-19—such as stay-at-home orders, business shutdowns, media exaggerations, and legitimate concerns about the virus—will destroy at least seven times more years of human life than can possibly be saved by lockdowns to control the spread of the disease. [emphasis mine] This figure is a bare minimum, and the actual one is likely more than 90 times greater.
Just Facts explains that the contributors to these mental health impacts include but are not limited to:
- empirically grounded concerns about the virus.
- anguish over the death of loved ones, although this is limited to a relatively small fraction of the public because the virus has killed one out of every 5,000 Americans, while one out of every 116 Americans die every year.
- media outlets that overstate the deadliness of Covid-19 by:
- government stay-at-home orders and self-imposed isolation, as evidenced by:
- a survey commissioned by the University of Phoenix in late March that found 44% of U.S. adults are more lonely than they have ever been in their lives, which is a risk factor for suicide and many other psychologically driven fatal afflictions.
- the late-March Kaiser Family Foundation survey, which “found that 47% of those sheltering in place reported negative mental health effects resulting from worry or stress,” a rate that “is significantly higher than the 37% among people who were not sheltering in place.”
- the late-March Benenson Strategy Group survey, which found that “71% of Americans say they are concerned that ‘social distancing’ measures will have a negative impact on the country’s mental health—including 28% who are extremely or very concerned about this.”
- government-mandated shutdowns of businesses in nearly every state that have cost millions of jobs and are reflected in the:
- late-April Kaiser Family Foundation survey, which found that 35% of adults and 55% of workers “have lost their jobs or had a reduction in hours or pay as a result of” responses to Covid-19.
- mid-March American Psychiatric Association survey, which found that 57% of adults are concerned that responses to the pandemic “will have a serious negative impact on their finances,” and 68% fear it “will have a long-lasting impact on the economy”.
Recent data coming out of the UK supports this idea. As reported by Lockdown Sceptics:
The Royal College of Psychiatrists (RCP) has reinforced this with evidence from its latest survey of 1,369 practitioners, carried out between May 1st and 6th. Its conclusion is that those with no previous history of mental illnesses are becoming unwell in alarming numbers. [emphasis mine]
According to the Guardian, four out of 10 psychiatrists say they have seen an increase in the number of people urgently requiring emergency care for mental health. Particularly prevalent are 18-25 year-old men with no previous history of mental illness. Participants in the survey reported “patients having severe psychotic symptoms which incorporate Covid-related themes” and that “many of our patients have deteriorated or developed mental disorders as a direct result of the coronavirus disruption, for example social isolation, increased stress [or that they have] run out of meds.
C) Rise in domestic violence and child abuse is a direct consequence of locking people inside
Deaths of despair can also happen in non-lockdown countries, in case I didn’t make that point clear. (At least they minimized the economical impact as much as they could.) But the increase in domestic violence and child abuse is a direct consequence of prolonged lockdowns:
- Domestic violence had already increased significantly by mid-April in the UK (source)
- In Lagos, domestic and sexual violence has been increasing (source)
- “Women and children who live with domestic violence have no escape from their abusers during quarantine, and from Brazil to Germany, Italy to China, activists and survivors say they are already seeing an alarming rise in abuse. […] According to our statistics, 90% of the causes of violence [in this period] are related to the Covid-19 epidemic.” (source)
- In the UK, “the first three weeks of lockdown saw the largest number of killings of women over any 21-day period in the last decade.” (source)
- “There was every reason to believe that the restrictions imposed to keep the virus from spreading would have such an effect, said Marianne Hester, a Bristol University sociologist who studies abusive relationships. Domestic violence goes up whenever families spend more time together, such as the Christmas and summer vacations, she said.” (source)
- Rise in child abuse is also on the rise: “By the end of March, with much of the country under lockdown, there was a 22% increase in monthly calls from people younger than 18, and half of all incoming contacts were from minors. That’s a first in RAINN’s history, Camille Cooper, the organization’s vice president of public policy, tells NPR.” (source)
D) Poor countries will be hit harder: Millions of people will starve to death or from a lack of proper health care
Yes, let’s go there — as uncomfortable as this may feel. As reported by Reuters on April 16th:
The [new] U.N. report warned that “economic hardship experienced by families as a result of the global economic downturn could result in hundreds of thousands of additional child deaths in 2020, reversing the last 2 to 3 years of progress in reducing infant mortality within a single year.” [emphasis mine]
The United Nations said an estimated 42 million to 66 million children could fall into extreme poverty as a result of the coronavirus crisis this year, adding to the estimated 386 million children already in extreme poverty in 2019.
The U.N. report on children also said 188 countries have imposed countrywide school closures, affecting more than 1.5 billion children. […] The world body also said in a risk report that nearly 369 million children across 143 countries who normally rely on school meals for a reliable source of daily nutrition have now been forced to look elsewhere.
COVID-related lockdowns and economic devastation could also lead to a new wave of famine in third world countries, and might “push an additional 130 million people to the brink of starvation”.
In so-called rich countries, poor access to food is also a problem. A recent report found that 20% of all families in the United Kingdom have a hard time feeding their children. In the US, up to 54M Americans could starve if they don’t get access to food banks.
As reported by Lockdown Sceptics, economic hardship will also dramatically restrict access to health services in poorer countries, leading to a devastating number of deaths in children and their mothers:
According to a preprint in the Lancet, more than one million children under five and 60,000 more mothers could die in the next six months alone as a result of disruptions to health services caused by the pandemic in low- and middle-income countries. [emphasis mine] Among those things “caused” by the pandemic they include “intentional choices made in responding to the pandemic”, e.g. imprisoning entire populations in their homes.
As Dr. Peterson puts it: “If you’re asking families to stay at home in one room in a slum, without food or water, that won’t limit virus transmission… We need to lift our eyes and look at the total picture of public health.”
A delay in the diagnosis of certain transmissible illnesses like tuberculosis (TB) could prove to be equally devastating. According to a new study, each month of lockdown could increase the number of cases of TB (because of the lack of testing and treatment) by more than 600,000.
The Telegraph reports:
The modelling study, carried out by a team of researchers including those at Imperial College, London, found that if services were shut down for two months and then took two months to recover there would be an additional 1.8m cases and 342,000 deaths globally between now and 2025.
However, in the worst case scenario of a three-month lockdown and a 10-month restoration period there would be 6.3 million cases and 1.4 million deaths over the same period.
This time, I’m crossing my fingers that the ICL (remember, those who predicted 2.2M COVID deaths in the US?) has done as usual and completely overestimated this death toll.
E) Postponing elective procedures and the fear of going to the hospital have already been deadly
Many countries who opted for a lockdown strategy also opted to postpone elective (non-urgent) procedures such as cancer screenings, exams, and surgeries — to make room for the tidal wave of COVID patients that never came.
This choice may come at a very high price, especially when it comes to cancer. In mid-April, Richard Sullivan, a professor of cancer and global health at King’s College London and director of its Institute of Cancer Policy said:
The number of deaths due to the disruption of cancer services is likely to outweigh the number of deaths from the coronavirus itself over the next five years. [emphasis mine] The cessation and delay of cancer care will cause considerable avoidable suffering. Cancer screening services have stopped, which means we will miss our chance to catch many cancers when they are treatable and curable, such as cervical, bowel and breast.
When we do restart normal service delivery after the lockdown is lifted, the backlog of cases will be a huge challenge to the healthcare system.
Sullivan is not the only expert sounding the alarm about the lack of cancer screenings and treatments. As reported by the Express:
A separate independent analysis carried out by Professor Karol Sikora, former advisor to the World Health Organization on cancer care, has estimated that over the next six months up to 60,000 cancer patients will die [emphasis mine] and approximately 15,000 patients – of all ages – will suffer illness or be forced to undergo unnecessary invasive treatments due to the loss of cancer services.
Last month in Scotland, doctors had already noted a reduction of 72% in urgent suspected cancer referrals. Even in Sweden, that figure is down by 33% — the proof that non-lockdown countries are also experiencing a version of this phenomenon, probably caused by the fear of going to the hospital.
The evidence that deaths from heart attacks are on the rise is crushing around the world. Out of fear, a lot of people stay at home and only seek help when it’s too late.
- United Kingdom: Public Health England noted a 50% drop in patients who came to the hospitals for heart complaints. “Attendances relating to myocardial infarction at emergency departments have dropped right down, whereas ambulance calls in relation to chest pain have gone right [up]” (source).
- United States: About half of cardiologists that were surveyed said they had experienced a drop of 40-60% in heart patients. The number of 911 calls related to heart events in NYC has also increased dramatically, and the mortality rate of those who call has gone way up — which shows many people seek emergency help way too late.
- Italy: In the Lombardy region of Italy, said Bernhard Reimers, MD (Humanitas Research Hospital, Milan), STEMI cases [note: ST–Elevation Myocardial Infarction — very serious heart attacks] are down by an estimated 70%” (source)
- Spain: The interventional cardiology working group of the Spanish Society of Cardiology published a paper that shows a drop of 40% in STEMIs in Spain, a number that’s said to be closer to 80% in the city of Madrid. (source)
I could go on, and on, and on — but you already see the portrait here. Cancelled interventions, lack of screenings for life-threatening conditions and the overall Corona-Panic has itself already killed in the tens of thousands.
This is not speculation. The Telegraph reported on a devastating analysis that came out a month ago:
Reorienting the NHS to focus on the Covid-19 emergency was essential but indirect deaths are mounting fast and now threaten to eclipse the carnage wreaked by the virus itself.
A new analysis by Edge Health, a leading provider of data to NHS trusts, warns that a second and then a third wave of “non-corona” deaths are about to hit Britain. Unless radical solutions can be found to resume normal service and slash waiting lists, the NHS may be forced to institute a formal regime of rationing.
The “second wave” is already breaking. It is made up of non-coronavirus patients not able or willing to access healthcare because of the crisis. Based on ONS and NHS data, Edge Health estimates these deaths now total approximately 10,000 and are running at around 2,000 a week. [emphasis mine — and that’s in the UK alone!)
They include a wide range of typical emergency admissions, including stroke and heart attack patients, as well as those with long term chronic conditions such as diabetes who are not able to access the primary or secondary care services they need. Many are sadly dying in their homes. Others are just getting to the hospital too late.
[…] Already 2.1 million scheduled operations are thought to have been cancelled and this is on top of the 4.5 million people who were on hospital waiting lists before the crisis.
For concerned citizens:
For decision makers and the media:
I’ve spent well over 200 hours putting together this article since I wrote my last article on… wow, it’s already been 9 weeks ago. I have to move on with my other projects, including the launch of a new EMF mitigation course I’ll announce soon.
And, yeah: In the end, I have no intention to become “The COVID Guy”. We still have a long way to go before the problem that electromagnetic pollution is becomes widely recognized.
There are many, many things I wish I had time to include in this article. My intention was to adopt a positive tone, although on most days I really felt like screaming or punching my screen over the level of nonsense I was reading left and right in the media.
I want to conclude this article with a short list of important things I want to address on the surface. Things I cannot possibly ignore and that will help readers that made it this far realize that I’m very well aware of these additional angles. Let’s get into it:
1) Omitting EMFs and 5G from the COVID discussion was completely intentional
“You’re ‘The EMF Guy’… how come you didn’t even address EMFs?” Good question, written by a reader in the comments section of my first article.
The reasons I chose not to include 5G and EMFs in my analysis of the COVID situation is that I rapidly concluded that COVID was a threat way less important than everyone made it to be. That was my angle from the get go, and all the rest looked like a distraction to me.
If something is not a massive health threat, why try to put the blame on 5G or some other thing? It didn’t make sense to me at the time, and it still does not.
At the moment, here’s what I believe when it comes to the COVID-5G-EMF link:
- COVID and EMF-related symptoms/electro hypersensitivity/microwave sickness do share some commonalities.
- The link between EMFs and a suppression of the immune system is plausible, but still debated among EMF scientists (great discussion from Prof. Dariusz Leszczyński and a few of his colleagues here).
- A recent virology study sent to me by a colleague demonstrates that excessive intracellular calcium cells exacerbates viral replication. Combined with the work of Dr. Martin Pall which shows that EMFs (all forms of “electrosmog”) impact voltage-gated calcium channels (VGCCs) and increase intracellular calcium, this could mean that EMFs increase viral replication. I’d like to see more studies testing this hypothesis.
- There’s a correlation between areas with high levels of COVID infections and high levels of EMFs. Correlation is not causation though. The same areas (Wuhan, Northern Italy, New York, etc.) have a high population density, more stress, more smog, etc. I personally have no doubt that living in a high electrosmog area puts you at greater risk of ill health, period.
- There are a few indications that the 60 GHz frequency might interfere with the body’s ability to get oxygen. However, I have found zero credible evidence that WiGig (wifi operating around 60 GHz) is widely used, and zero evidence that 60 GHz is being used in 5G towers that are being rolled out worldwide. If you have evidence that shows otherwise, please let me know. I might be wrong on this.
- Countless experts I’ve heard talk about the possible 5G-COVID link like Dr. Rashid Buttar unfortunately have no expertise whatsoever in EMFs, and it shows. I like Buttar’s work but he easily confuses frequencies and technical terms, and doesn’t seem to grasp the basics of how EMFs can impact biology. This contributes to the massive confusion about 5G I’m seeing online, and unfortunately hinders the credibility of the movement.
2) Waiting for a vaccine that might never exist is stupid
I’m not anti-vaccination (I know some of my readers won’t like me for it, but it’s the truth — I’m open to hearing both sides here) or anti-anything, really. I’m pro-“things that work and that are safe”.
Claiming that we’re even going to have a vaccine for COVID one day at this point is still pure speculation. Top German virologist Professor Hendrik Streeck reminded everyone in a recent interview that all prior attempts to make vaccines for previous coronaviruses have failed.
The vaccine would probably be RNA-based, which in fact would make it a kind of gene therapy if my understanding is correct. I have not seen evidence that any vaccine of this type has ever been approved or shown to be effective in humans.
Prior vaccines for coronaviruses have failed because they had serious side effects on animals during testing, but this time around they’ve decided to skip animal trials altogether. Seriously? It’s no wonder huge pro-vaccine advocates like Dr. Paul Offit think that rushing a vaccine is a very dangerous idea.
When Prime Minister Trudeau claimed that “things will never go back to normal until we have a vaccine”, I think he was just struck with a serious case of Corona-Panic.
By the looks of it, COVID might fade away by itself or be included in the regular seasonal causes of flu-like illnesses way before a vaccine is ever manufactured. I might be wrong on this, the future will tell.
3) We need to focus on improving patient outcomes and protecting risk groups
Protect people who are at risk, especially those in nursing homes. This doesn’t mean we should lock them up forever… this would be more deadly than anything.
I think that improving the outcomes for hospitalized patients will basically eliminate the need for a vaccine. A few points on treatments — and disclaimer, I’m obviously not a medical doctor:
- I think that hydroxychloroquine probably has some merits, and I don’t think that Didier Raoult is nuts.
- Dr. Wodarg from Germany has identified that hydroxychloroquine might prove to be dangerous or even deadly for those with a G6PD deficiency. This might explain why people with certain genetic backgrounds die from COVID in greater proportions… Is the treatment worse than the disease? In some cases, maybe.
- Ventilators surely do more harm than good — considering the 97.2% death rate in 65+ yo patients in NYC. This interview with Dr. Cameron Kyle-Sidell is a good one to watch if you want to explore that topic further.
- Ensuring people have enough vitamin D might be key. A few studies like this one from Indonesia have shown that normal vitamin D status is a key factor to reduce your risk of dying from COVID. Nothing surprising here. Dr. Mercola has the best information about how to get enough vitamin D here. Note: Getting in the sun is way better than taking a pill.
- Speaking of spending time outside, it’s about time that decision makers come to their senses and tell people that COVID rarely if ever is transmitted outside. It’s mainly transmitted through prolonged contact inside homes and buildings. More here.
Follow the Swedish example, which will ironically soon be touted as the ultimate approach. Switzerland is also the perfect example of how to lift lockdowns properly. On May 11th, the Swiss even told their citizens who are over 65 to resume their normal activities, all while maintaining a certain amount of social distancing. That sounds fair and rational to me.
4) Masks probably are a side effect of the Corona-Panic, and not a real evidence-based way to protect ourselves
I might be wrong on this, but the evidence I’ve seen is really contradictory.
- Since there’s rarely any outside transmission of COVID, why would we wear them outside instead of breathing fresh air?
- Cloth masks have been shown to be ineffective in the past.
- In a recent commentary, Dr. Brosseau, a national expert on respiratory protection and infectious diseases and professor (retired) from the University of Illinois at Chicago, said that the masks-for-all policies are not evidence-based.
- A recent review of COVID-related interventions throughout Europe confirmed that masks did not lead to any significant impact in reducing COVID transmission.
Quebec is thinking about making face masks mandatory — but at this point I think this is just a response to political pressure, mainly from citizens struck with Corona-Panic.
5) The WHO and other people who either created or maintained the Corona-Panic need to face an independent investigation
Again, I didn’t want this article to turn political, and talk about the “agendas” that might be going on. I’m not also someone who loves getting into a lot of speculation. I’ll stick with facts, and will not engage into speculation about whether any of the people/corporations mentioned below have nefarious agendas. One thing is sure, there are a lot of blatant conflicts of interests not being addressed.
A few random thoughts here:
- The World Health Organization is around 80% financed by voluntary contributions. Top donors include the Gates Foundation, the pharmaceuticals GlaxoSmithKline, Bayer AG, Sanofi, Merck and Gilead Sciences — on top of an organization called “Global Alliance for Vaccines and Immunization” (GAVI). Many documentaries (this one in German, this one in French, this one in English) have exposed how much the WHO is — quite obviously — influenced by corporate interests. The WHO was under investigation after H1N1 for having pushed a “fake pandemic”, but the whole thing eventually died down.
- “GAVI are partnered with the WHO, UNICEF, the Bill & Melinda Gates Foundation and the World Bank to sell vaccines globally. The World Bank contributed nearly $146 million themselves and the largest individual payment, by some margin, at nearly $325 million came from the Bill & Melinda Gates Foundation (BMGF). Though like many other foundations and corporations, through their various networks of interlinked partnerships, their overall contribution was much higher.” (source)
- The Imperial College London, now ex-home of Neil “Mr. Apocalypse” Ferguson, is heavily funded by the Gates Foundation and by GAVI.
- The Gates Foundation gives out billions t