Pandemic Response

Originally published August 29, 2021; last updated September 20, 2021. See here for the complete revision history. 🕑 70 min.

Motivation

At this point it seems necessary for me to formalize our family’s response to the ongoing pandemic countermeasures. At various points in the past year and a half it seemed reasonable to wait for more data, and in recent months it looked like things would get back to some semblance of normal once everyone who wanted the protection of one of the vaccines had it. However, that no longer appears to be the case, as cities, states, and countries are starting to reimpose various levels of lockdown measures and vaccine mandates.

Before we dive in, if you’d like a concise and approachable book on the subject of COVID-19 and the worldwide response, I highly recommend COVID: Why Most of What You Know is Wrong, by Sebastian Rushworth. The author is a Swedish doctor, and he gives a remarkably level-headed analysis of the data that is easily understandable by a non-expert. I will note the book was finalized in December of 2020, so any data that became available this year were unavailable while the book was being written, and as such the author has changed his take on a few minor points since its publication. Another good resource is Unreported Truths About COVID-19 and Lockdowns, by Alex Berenson, but if you’re only going to read one book on the subject, prefer the former.

A final aside before getting started: It can be easy to dismiss concerns such as those that follow as uninformed, unscientific, paranoid, delusional, etc.; however, researchers at MIT conducted a study to determine how coronavirus skeptics spread information on social media, and they were able to determine that such communities employed high degrees of scientific rigor and rhetoric in their data analysis and argumentation. We encourage you, as they do, to follow the data and see where it leads, and to be willing to re-evaluate any preconceived notions you have. We will endeavor to do the same, and we invite you to correct us where we are mistaken. Our goal here is to educate and encourage a dialogue on any of these points.

Where Do We Stand Today?

Our thinking today was informed by trying to tackle the following questions:

  1. How severe is the pandemic, in terms of hospitalizations, mortality, and any long-term effects of the virus?

  2. How effective have we been in countering it, in terms of measures like masks, lockdowns, and vaccines?

  3. Have there been any negative consequences to adopting the various countermeasures we’ve employed?

Let’s walk through these one at a time.

The Danger of COVID-19

Historical Background

Before assessing the danger of COVID-19, I think it’s instructive to get some historical perspective by looking back at how the world responded to the swine flu in 2009. After it was all over, Der Spiegel sought to reconstruct the timeline of events and what played into the decision-making around the globe. Their article is worth a quick read, but allow me to sum up their analysis here: A fear of prior deadly pandemics, combined with a focus on worst-case scenario predictions out of touch with mounting evidence, along with significant pressure from both the pharmaceutical industry and political players around the world, contributed to a worldwide hysteria for a virus that in the end killed no more than the average flu season.

With that background in mind, let’s take a look at how things have played out this time around.

The Initial Scare

For the first few months as the disease spread throughout Asia, and began to spread through the rest of the world, most countries did nothing but watch to see how things would unfold. Then in March of 2020, the Imperial College of London released a report that seems to have triggered the initial scare. The team that produced the report was led by a mathematical epidemiologist, and they used a combination of mathematical modeling and analysis of data as it was emerging from China to predict that an unmitigated pandemic (meaning without taking any countermeasures) would lead to 510,000 deaths in the UK and 2.2 million deaths in the US, not counting any deaths that would result from the healthcare systems being overrun. Unfortunately the Imperial College report isn’t clear on a cut-off date for those deaths; however, a separate modeling study on Sweden was posted to medRxiv in April, 2020, predicting 96,000 deaths in the country by July 1st. Given such startling predictions, it’s understandable that much of the world responded with, “We can’t just sit here; we have to do something!”

However, it’s important to realize that many of the initial predictions were based on mathematical models trained on a limited amount of data. As a former computational scientist, I think the mathematical modeling community needs to have a lot more humility and transparency about what it can claim, and with what level of certainty, and what it cannot. Now that we have an additional 18 months of real-world data, we can evaluate both how accurate those models were, and how dangerous the disease really is.

What Constitutes a COVID-19 Case?

Before we do that, though, we need to talk a bit about how the world has been tracking the spread of the virus, and for that we need to understand the details of the polymerase chain reaction (PCR) tests. The best write-up I’ve seen on these is from Sebastian Rushworth: How Accurate are the COVID Tests? I highly recommend reading the article, as I won’t be able to do it justice here. In a nutshell, the PCR test is trying to take a viral genome fragment and replicate it enough times such that you have a large enough sample to detect. The number of times you allow the fragment to replicate is what’s known as the cycle threshold (CT). Rushworth says “a positive test result after 40 cycles is almost certainly a false positive, while a positive result after 20 cycles is most likely a true positive.” Unfortunately, as PCR tests were rolled out the world over to track the spread of the disease, no mechanisms were put in place to associate test results with the CTs that produced them, so we (the public and doctors alike) are left in the dark as to what the results truly mean.

On top of this problem, the PCR test has no ability to tell you whether or not you are infectious. The reason here is the tests only detect viral genome fragments in the swab that was done of your nose or mouth. Those fragments may have come from an active infection in your system, they could be remnants from you weathering the disease in the past, or they could have been inhaled from your environment (and it’s not possible to tell if they will or won’t infect you). To determine whether or not you truly had the disease, you need to follow up a PCR test with an antibody test, though this is rarely being done. Rushworth concludes his article with

And that, ladies and gentlemen, is why PCR positive cases are a very poor indicator of how prevalent COVID is in the population, and why we should instead be basing decisions on the rates of hospitalization, ICU admission, and death. If we just look at the PCR tests, we will continue to believe that the disease is widespread in the population indefinitely, even as it becomes less and less common in reality.

Unfortunately it sounds like a good number of PCR tests for COVID-19 are being conducted with a CT of 40 (other sources indicate 45), so the fidelity of the results is highly questionable. That being said, as you hear of “cases rising” or a “resurgence of cases” in your area or around the world, these are the cases being referenced.

Note

The situation may even be worse than this, as it looks like the WHO guidelines for the surveillance of COVID-19 also allow for probable cases to be recorded without any testing. However, my understanding of the medical and legal terminology in that document may be incorrect.

The Rise of the “Casedemic”

The loose criteria for determining COVID-19 cases in turn give rise to a phenomenon that’s been dubbed a “casedemic”, where testing yields a significant number of cases, but you don’t have corresponding impacts in terms of hospitalizations and deaths. Ivor Cummins gives us a good look at what the data show in the video clip below.

If you have time to do some number crunching, I encourage you to compare the time series data for COVID-19 cases and COVID-19 deaths and draw your own conclusions.

Note

If you do look into the raw data, you’ll notice a significant rise in both cases and deaths in late 2020 and early 2021. This is to be expected after locking down much of the world’s population during the summer months when we would normally be outside building viral immunity within the population (see the discussion of seasonality below).

Unfortunately searching the internet for the term “casedemic” has a tendency to provide articles that exhibit significant bias. I’ll provide two links here, in case you want to dig through the information and links therein, but take them with a grain (or perhaps a tablespoon) of salt.

The Swiss Policy Research organization, however, gives us the more level-headed assessment that we have a “casedemic” on top of a pandemic. We understand that the virus is real, and that it’s impacting people all over the world; what we’re trying to assess it its severity.

What Constitutes a COVID-19 Death?

Before we can understand the severity, though, we first need to understand how COVID-19 deaths are tallied. As the Children’s Health Defense organization reports, for some reason “COVID-19 data is collected and reported by a much different standard than all other infectious diseases and causes of death data.” Prior to March of 2020, causes of death in the US were reported according to the Medical Examiners’ and Coroners’ Registration and Fetal Death Reporting guide and the Physicians’ Handbook on Medical Certification of Death put out by the Centers for Disease Control and Prevention (CDC). Under these guidelines, the cause of death would be the last problem in the chain of events that led to death, e.g., renal failure, and that would be listed on the first line in Part 1 of the death certificate. Below that would be listed the other comorbid conditions in the chain of events that led to death, so, e.g., COVID-19 might be at the bottom of that list. Below that, in Part 2 of the death certificate, you would list any other things that happened to be wrong with the patient at the time of death that were unrelated to the chain of events that lead to death.

That was how things worked prior to March of 2020, at which point new guidelines were adopted, which state that “the rules for coding and selection of the underlying cause of death are expected to result in COVID-19 being the underlying cause more often than not.” The updated guidelines make two significant changes to the process of filling out a death certificate.

  1. If the decedent has COVID-19 at the time of death, that should be listed on the first line in Part 1, and all other comorbidities listed in Part 2.

  2. COVID-19 can be listed as the cause of death without a positive lab test.

Why were these changes made? I can’t think of a logical reason, and I haven’t been able to find any justification. Generally speaking I want to stay away from the “why” questions in this analysis, because at this point in the game it’s exceedingly difficult to find direct answers, and one can quickly slip into the realm of opinion and intrigue. Regardless of the motivation, though, we can see what impact the change in coding guidelines had. Data from the CDC indicate that about 94% of the deaths attributed to COVID-19 in the US would have been attributed to other comorbidities if accounted by the rules in place prior to March, 2020. Hang on to this thought, as I’ll come back to it in a moment.

Note

It sounds like there’s disagreement on whether or not these updated guidelines were actually followed by doctors and coroners when filling out death certificates. Without interviewing a large number of people who filled out death certificates in the last 18 months to get an idea (I couldn’t find a study on this yet), I’m assuming the new guidelines that were put in place were followed. However, if this turns out to not be the case, then my concerns about deaths being over-attributed to COVID-19 are significantly diminished.

So How Bad Is It?

Before we get to how bad COVID-19 is, please note that there are many variables that complicate such an assessment when looking at the different countries around the world:

  • differences in health care systems

  • relative health of the population

  • age distribution within the population

  • percentage of the population in assisted living facilities

  • differences in data collection and reporting

  • how bad the prior year’s flu season was

  • etc.

The Swiss Policy Research organization has done an excellent job compiling all the latest information, so I’ll happily point you to their work and encourage you to click through to the source materials.

An initial observation to make from their collected research is that in the early days of the virus, the information coming out of China led to an estimated hospitalization rate (the number of people needing hospital care divided by the number of infections) of about 20%. This fueled the concerns that healthcare systems the world over would be overwhelmed, and to prevent that we needed to do whatever was necessary to “flatten the curve” (or spread hospitalizations out over a longer period of time). In reality the hospitalization rate has been closer to 2%, and relatively few localities have had their healthcare systems overrun. For comparison purposes, a 1–2% hospitalization rate is what we typically see with seasonal influenza.

The next key point to note is that the median age of death globally is in the 80s, meaning half of decedents are younger and half are older. On a related note, a sizeable percentage of deaths occurred in assisted living facilities. How many varies from country to country, based on the age and health breakdown of the population, but in some countries it’s as high as 80%. Correlated with age is also the number of comorbidites a decedent has, or the number of other underlying conditions present at the time of death. The most recent CDC data indicates the average number of comorbidities for those who have died with COVID-19 in the US is four. This is not a virus that affects the population equally, but instead it has greater impact on those who are in poorer health and are nearer the end of life already.

The next key piece of information to look at when assessing the severity of the pandemic is a measure known as the infection fatality ratio (IFR), or the number of deaths divided by the number of infections. For reference, a “bad” IFR is about 0.3%, as exhibited in the influenza epi/pandemics of 1936, 1951, 1957, and 1968. Last October John Ioannidis provided a low estimate of 0.2% for the COVID-19 IFR; however, an earlier paper provided a higher estimate of 0.68%. Ioannidis’ paper used substantially more underlying data, so I’m inclined to consider his the more accurate estimate. The Swiss Policy Research link above gives you the full breakdown by country, so you can see how the IFR varies from place to place. One final tidbit before leaving IFR is that Ioannidis showed if we restrict our consideration to individuals younger than 70, the estimate drops to 0.04%. For comparison purposes, seasonal influenza typically sees an IFR of 0.05–0.1%.

So how bad is COVID-19 in terms of mortality? The data as of March, 2021, suggest an IFR between 0.1% and 0.35%, and the overall global COVID-19 mortality (total deaths divided by the global population) is about 0.035%. For reference, the global mortality rate for the Spanish flu pandemic of 1918 was about 2.3% (granted, medicine has progressed a good deal in the intervening century). Looking at all the data, this looks to be on par with the “bad” flu seasons we see a handful of times per century, and the Children’s Health Defense article referenced above also shows it to be comparable to both influenza and pneumonia.

Finally, some food for thought: Recall at the end of the last section the observation that a sizeable percentage of deaths attributed to COVID-19 would have been attributed to other causes, were it not for a change in cause of death coding procedures. Since all the data we’ve looked at in this section have been based on COVID-19 deaths as recorded, does that mean the severity of the virus is actually substantially less than indicated here? I’ll let you come to your own conclusions.

How Does This Compare to Other Viruses?

At this point it’s beginning to sound like COVID-19 presents like any other virus, as far as the mortality data are concerned, but is it similar to other viruses in other respects? Indeed, yes, and examining how can help us make better sense of the numbers and figures we’re inundated with on a regular basis. Again, I’ll direct you to Ivor Cummins for his balanced walk through what the data can tell us about the seasonality of the virus.

Note

This is the same video embedded above, just started from the beginning instead of part-way through.

He directs us to a book by R. Edgar Hope-Simpson from 1992: The Transmission of Epidemic Influenza. In it the author notes the distribution of epidemic impact depends on climate; specifically, the temperate climates will see relatively sharp peaks, while the tropical climates will have wider distributions spread across the whole year (see, e.g., Chapter 8, particularly Figures 8.4–8.7). We see these same patterns in the COVID-19 data. The dependence on climate also explains the so-called “second wave” the US experienced last year. Since this US consists of such a large area, with such diverse climate, you wind up adding the distributions for the temperate and tropical climates to get the double-hump curve we see every flu season.

Note

The climate variety may also explain the rise in cases and deaths we’re seeing associated with the delta variant, but it’s too soon to know with any certainty.

You don’t have to just take Cummins’ word for it, though; at this point we have a number of studies on the seasonality of COVID-19. For instance, a paper from May, 2021, analyzed the effects of air drying capacity and ultraviolet radiation on COVID-19 dynamics at the seasonal scale. Another paper from June of this year discusses the impact of sunlight on transmissibility, morbidity, and mortality, which seems to validate an earlier study that suggested the importance of vitamin D in fighting the virus.

Cummins also demonstrated the impact the prior year’s flu season had on how hard a country was hit by COVID-19. The excess mortality data show that a country with a relatively light prior season—meaning fewer than expected deaths, leading to a build-up of the frail within the population (e.g., Sweden, the UK)—led to a substantial COVID-19 impact. Similarly, a normal to hard prior season led to a minimal COVID-19 impact (e.g., Finland, Norway).

Are There Any Long-Term Effects?

So far our analysis has been based largely on mortality data, and to a much lesser extent hospitalization rates. But what about the long-term effects of having contracted COVID-19 and then recovered from it? There seems to be significant anecdotal evidence supporting a host of bizarre long-term side effects after recovering from the infection—what’s come to be known as “long COVID”—and we should evaluate that as well in assessing the danger of the disease.

First, let me caution you strongly against arguing solely on the basis of anecdotal evidence—this is something known as the anecdotal fallacy. Beyond that, though, I’ll gladly refer you to this article, again from Sebastian Rushworth, on what long COVID is and isn’t. It’s been hard to peg down, as studies have shown it to be such a hodge-podge of unrelated conditions. Regardless of any particular lingering symptom, most people recover within a month, ~95% are fully recovered by two months, and only ~2% continue to experience side effects after three months. In a nutshell, the studies conducted so far seem to indicate that long COVID is nothing more than post-viral syndrome, which is “a wide range of complex conditions involving physical, cognitive, emotional and neurological difficulties that vary in severity over time.” It’s something that you might suffer as your body recovers from a significant viral infection.

What Can We Conclude?

We’ve been through a lot in this section, so let’s try to pull it all together to reach some final conclusions about the danger of COVID-19.

Our initial fear of the virus looks like it was triggered by either

  1. poor mathematical modeling,

  2. poor communication of the results of that modeling,

  3. poor reaction to the communication of the results of that modeling,

or some combination of all three. As the virus began spreading around the world, it seems our assessment of its severity was exaggerated by loose definitions of both what constitutes a COVID-19 case and a COVID-19 death. Polymerase chain reaction (PCR) tests with a cycle threshold (CT) of 25 or greater produce too many false positives to be useful in surveilling the spread of the disease, and lack of reporting of CTs with test results means doctors and patients alike can’t know whether they represent useful information. Beyond that, a positive PCR result can’t tell you if you have live virus in your system, or if it merely found fragments of dead virus. In addition to “case” being defined so generously, it looks like new cause of death coding guidelines were implemented that would result in COVID-19 being listed as the cause of death more often than not.

Governments and individuals alike have routinely focused on the questionable measure of cases, rather than the more useful measures of hospitalizations and deaths. When you stick to those harder measures, COVID-19 looks to be on par with the bad epi/pandemics we see a few times per century (e.g., 1936, 1951, 1957, 1968), with an infection fatality rate (IFR) of ~0.3%, and a sizeable portion of deaths occurring in assisted living facilities. However, if you look at the portion of the population below age 70, for those individuals this pandemic is no more severe than a typical influenza season (IFR of ~0.04%). Though the hospitalization rate was predicted to be 20%, which would have overwhelmed healthcare systems the world over, in reality the rate has been closer to 2%, and few hospital system have been overwhelmed.

The seasonality data we have at this point seems to support the claim that this pandemic is behaving generally as influenza epi/pandemics do, with the distribution of cases and deaths being largely governed by climate, specifically air drying capacity and ultraviolet radiation. This is good news, as it gives us clues as to what we can do to mitigate the risks. On the personal level, make sure your diet is healthy, get some good exercise, and spend plenty of time outside in the sun. Excess mortality data show that a light prior flu season—indicating a build up of the frail within the population—seems to be a good predictor for the severity of COVID-19 impact, so at a policy-making level, nations or healthcare systems can monitor the prior season’s excess deaths to get a feel for how severe the upcoming viral season will be, and then take appropriate measures to protect the most vulnerable.

Though there is anecdotal evidence to support the notion of long-term side effects after recovering from the disease (what’s been dubbed “long COVID”), an analysis of such cases shows them to be nothing more than post-viral syndrome, which is well-established in the medical literature. Long-lasting effects are therefore not something to worry about.

Bottom line: If you are near the end of life as it is—you’re over 70, have one or more underlying health conditions, or are in an assisted living facility—now is probably a good time to make sure you’re ready to die. (Of course this would’ve been true for you before COVID-19 as well.) If this is you, here are some questions I’d encourage you to wrestle with:

  • Why are you here?

  • What is your purpose in life?

  • What will you do with the time you have left, whether that’s two months or twenty years (and we’ll pray it’s the latter)?

  • Does anything, good or bad, await you after death?

  • How do you know the answers to these questions?

If you don’t fall into the category above, you likely don’t have anything to worry about in terms of your own health and well-being. You may want to talk through all this with those you know in the vulnerable subset of the population, and you may wind up mourning the loss of one or more loved ones.

The Effectiveness of Countermeasures

While our prior analysis indicates it’s reasonable to conclude that COVID-19 does not pose near the threat that’s been reported, let’s suppose for the sake of argument that it does. If the danger is as great as reported—if the initial mathematical modeling is representative of reality—then it’s entirely reasonable for governments to consider encouraging various countermeasures to slow the spread of the disease and thereby decrease the overall death toll. The countermeasures used have generally fallen into the categories of mask mandates, lockdowns, and vaccines, and with the last 18 months’ worth of data in hand, we can now ask the question: Are such countermeasures effective?

Mask Mandates

Let’s look first to the concept of mask mandates. Intuition tells us that if a virus is spread via droplets expelled from the nose and mouth, then covering the nose and mouth should slow the spread of the virus through the population. This is why you’re always told to cough into your elbow, for instance. The question, then, is whether this intuition is empirically verifiable.

Before we get into the evidence, it’s important to make a distinction between two different hypotheses being put forward:

  1. Masks protect me from your infection; that is, they function as personal protective equipment (PPE).

  2. Masks protect you from my infection; that is, they function as source control.

It may be the case that masks are effective for one but not the other.

It’s also worth noting, before diving into the data, that the pandemic guidelines from the WHO, which were in effect before COVID-19 came on the scene, do recommend masks for the general public if a pandemic’s severity is determined to be high; for moderate or low severity, they are not recommended. If this pandemic is as severe as is typically claimed, then recommending masks for the general public is reasonable according to prior guidance. However, if this pandemic is not as severe as we’ve been led to believe, as our prior analysis suggests, then prior guidance indicates the masking of the general public is unnecessary.

Now let’s dig into the evidence. Thankfully, the folks at the Swiss Policy Research organization have done a fantastic job compiling all the latest studies, and I’ll happily point you in their direction rather than replicating their work here. The analysis that follows comes from their collection.

A first question we can ask of the data is whether or not the imposition of mask mandates has any noticeable effect on the case or death rates. Intuitively we would expect masking of the general public to significantly alter the curves in daily case and death rates, though we might expect any change in the curves to be lagged by some amount of time to account for the incubation period of the virus. Unfortunately the data do not bear out this hypothesis, instead displaying the standard Gompertz curve we expect from, e.g., seasonal epidemic influenza, as explained by Ivor Cummins in the video embedded above. Note that this even holds for Bavaria in Germany, which mandated the use of N95 respirators in public in January, 2021.

Since our intuition turns out to be dead wrong, a natural next question is why on earth that is. It turns out there has been concern, at least since last summer, that the virus is spread not only through expelled droplets, but also aerosols. If that’s the case, it poses a problem, as the vast majority of masks are unable to block or filter aerosols, the majority of which “fill a medium-sized room within minutes.” The potential problem is well-illustrated in this video:

Note

There’s been a good deal of backlash against this video, so don’t take it as your sole source that masks don’t work; instead consider it in the broader context of the mounting evidence that supports that claim. When evaluating critiques, try to discern whether those arguing on the other side are giving you empirical evidence, or if they’re simply making assertions without giving you grounds to back them up.

Now if it’s the case that this pandemic spreads via expelled aerosols, and if the vast majority of masks are unable to stop the spread of such aerosols, then we should be able to find ample evidence that masks are not effective for what we think they should be. And indeed we can:

Some of these sources are specific to COVID-19; others pertain to aerosol viruses in general. Some focus on the efficacy of masks serving as PPE, others as source control, and others consider both. What they all have in common is they show “little to no evidence for the effectiveness of face masks in the general population, neither as PPE nor as source control.” Apparently this even holds true in hospital settings, which was a surprise to me.

Before we leave the subject of face masks, we should take a moment to address the various studies that have been completed showing that masks are indeed effective for combatting COVID-19. A number of them are based on mathematical modeling, and, as a former computational mathematician, I’m suspicious of such studies because of how they contributed to the fear and public health policy decisions at the advent of the pandemic. The remainder exhibit either poor methodology or counter-intuitive conclusions drawn from the data presented. From the Swiss Policy Research organization:

Typically, these studies ignore the effect of other measures, the natural development of infection rates, changes in test activity, or they compare places with different epidemiological conditions. Studies performed in a lab or as a computer simulation often aren’t applicable to the real world.

I encourage you to dig through all the sources and draw your own conclusions.

Note

If you’d like another analysis of all of the above from someone more qualified than myself to evaluate the medical evidence, consider reading Why Masks Are a Charade, by Dr Joseph Mercola. For more of a historical perspective, consider Do Masks Work?, by Jeffrey H. Anderson. Both of these articles were published in August, 2021.

If you’d like to do more research on the effectiveness and potential side effects of masks, this page contains links to 79 studies. I recommend skipping over the introductory material and going straight to the sources.

Lockdowns

Another bit of human intuition says that if viral particles are spread via either droplets or aerosols, then simply staying away from other humans should slow the spread of the virus, and thereby decrease the overall death toll (not to mention, keep me healthy). Thus we have the concept of locking down cities and countries to hopefully decrease the total impact of the pandemic.

Before we look into whether or not such measures achieve their desired aim, it’s worth noting that the WHO pandemic guidelines from 2019 stipulate that the following measures are not recommended in any circumstances:

  • Contact tracing

  • Quarantine of exposed individuals

  • Entry and exit screening

  • Border closure

So historically the medical and public health communities thought lockdowns to have no appreciable effect on the length or severity of a pandemic, but we tried them anyway. The question, then, is whether or not they worked.

As we did with masks, we can first ask if the imposition of lockdowns had any noticeable effect on case or death rates. You likely already know the answer, if you’ve been looking at the data as we’ve walked through prior arguments, but here’s a fresh take on it specific to lockdown measures. Given the dates of imposition of lockdown measures, the author finds no subsequent impact on the case or death data. Of particular note is a comparison of the states within the US, where the five states with the highest number of deaths per million all issued stay-at-home orders.

If they appear to have no positive effect on the global scale, perhaps it’s the case they can be effective on a smaller scale, if adhered to strictly. After all, how many people really obeyed 100% of the time? This is a question worth asking, and the US Marine Corps sought to answer it in the midst of boot camp last year. Recruits had to quarantine for two weeks before arrival, and then an additional two weeks after arriving at a closed college campus set aside for the experiment. During the experiment masks were worn at all times except while eating and sleeping, six-foot distancing was maintained at all times, all buildings followed single direction traffic flow patterns, and recruits spent most of their time outdoors. If these recruits stayed clear of COVID-19, this should have been an ideal setup to show that lockdown measures work.

Unfortunately, there was no such luck, as 2.8% of the 1800+ recruits taking part in the experiment wound up testing positive via a PCR test, compared to 1.7% of the 1500+ recruits who elected not to take part. (It would have been better for the study if those who elected not to participate had not followed any of the lockdown measures 100% of the time, such that we could have a better comparison, but that was not the case.) Though recruits shared common grounds, bathrooms, and the mess hall, analysis of the particular genomes in those who tested positive showed transmission to only take place within platoons and sleeping quarters. The analysis also seems to lend support to the notion that most individuals are mildly infectious, while others function as “super spreaders”, as the majority of the genomes could be traced back to two of the 51 recruits who tested positive.

Note

Given what we learned about PCR tests, it might have been the case that there were really only two infected individuals who wound up spreading the disease, and those who tested positive but didn’t trace back to those two were false positives. Unfortunately there’s no way to know for sure.

Okay, so lockdowns don’t seem to impact the case and death rate data, and this one specific instance shows that COVID-19 broke through anyway, but have there been any systematic studies on the effects of lockdowns? Indeed, yes.

One study from last November sought to measure the impact a variety of non-medical factors had on COVID-19 mortality; while they found correlations in some areas, they concluded the “stringency of the measures settled to fight pandemic, including lockdown, did not appear to be linked with death rate.” Then in December a study found that more restrictive non-pharmaceutical interventions (NPIs) like stay-at-home orders and forced business closures had no effect on case growth. At the same time the American Institute of Economic Research pulled together a couple dozen studies providing evidence against the efficacy of lockdowns. At the end of the year, a study from Denmark showed the infection decline to occur before any mandated lockdown measures went into effect, not after. More recently, an analysis from this April sought to examine the impacts of coronavirus restrictions across the US; they found the measures correlated well with unemployment, but not with mortality.

On top of all that, there is even some evidence to suggest that harder lockdowns increase COVID-19 mortality. Given what we learned of the importance of vitamin D in combatting the infection, and what the medical community has known for decades about how your mental and emotional state contributes to your ability to overcome sickness, this makes some intuitive sense, but more investigation is likely required.

“Well wait,” you might ask, “why have I heard so much about Sweden doing so poorly without a lockdown compared to the surrounding countries?” That’s a great question, and there’s a good write-up on it from March of this year. The answer involves a variety of factors like:

  • the age and health breakdown of the population

  • the percentage of the population in extended care homes

  • how many people traveled to the Alps and brought the virus home with them

  • whether or not the virus had reached neighboring countries yet

  • etc.

Before we leave the subject of lockdowns, we should, as we did with mask mandates, examine the evidence that suggest they are indeed effective in controlling the spread of the virus. Unfortunately, we find much the same thing as we did with masks: that such studies are largely based on modeling (e.g., this rapid review consists primarily of modeling studies, though the authors sought to include other kinds as well), and they involve poor methodology and conclusions that contradict the data. Again, feel free to do your own digging and come to your own conclusions.

Note

If you’d like to do more digging on the effectiveness of various lockdown measures, here’s a thorough collection of papers on the subject.

Note

I also endeavored to find empirical evidence on the efficacy of social distancing policies in particular, in terms of slowing viral spread, decreasing overall death toll, etc., but was unable to. There are a number of modeling studies out there predicting the impact of distancing, but given the track record mathematical modeling has had in accurately predicting the course of this pandemic, I’m inclined to disregard them. It seems reasonable to conclude that the evidence supporting the ineffectiveness of both masks and lockdowns can be extended to apply to social distancing as well, but if any observational studies on the impact of distancing are published in the future, they may refute that conclusion.

Vaccines

The final countermeasures we’ll examine here are the COVID-19 vaccines. A first question I have when approaching the topic is how their manufacturers were able to determine their efficacy and ensure minimal side effects on such a short timeframe. Sebastian Rushworth gives us a good overview of both how the vaccines work, and what their trials show. It appears the trials were limited (you might say flawed) in their design:

  • The Astra-Zeneca vaccine trial exhibits a few peculiarities that are concerning: not using double-blind trials throughout, sometimes administering a meningococcus vaccine in place of a placebo, using primarily young, healthy participants (only 4% were over age 70; none younger than 18; ideal body mass index; small percentage with underlying conditions), and being small enough to not detect rare side effects.

  • The Pfizer vaccine trial seems to be much better designed than the Astra-Zeneca one. That said, it did have some limitations: excluding the immunocompromised, those with severe allergic reactions to a vaccine in the past, women who were pregnant or breastfeeding, and people with auto-immune disease. Only 5% of participants were 75 years old or older.

  • The design of the Moderna vaccine trial was very similar to that of the Pfizer one. No participants were over age 80.

All three trials had the problematic endpoint of a positive PCR test after one or more symptoms presented. It’s therefore only possible for the trials to give us an indication of whether or not the vaccines decrease the presence of COVID-19 symptoms. They cannot tell us if they prevent you from contracting the virus, and they also can’t tell us if they prevent you from spreading the disease to others. The trials only lasted 2–3 months beyond the second vaccine dose, so they also can’t tell us anything about long-term immunity.

Based on the design of the trials, it’s also worth noting that they can’t really tell us if the vaccines are either safe or effective for the most vulnerable. Recall that the median age of death is in the 80s, and the average decedent has four comorbidities. I would assume this vulnerable demographic would be the one targeted by the vaccines, but the trials were conducted almost entirely on young healthy people.

While they can’t tell us what we really want to know, they can tell us something: They do seem to decrease the incidence of symptomatic COVID-19 in young healthy people. If symptoms do present, they tend to be less severe. Moderna seems to be the best bet, followed by Pfizer, with Astra-Zeneca pulling up the rear.

A next question I have in evaluating not only the efficacy, but also the safety of the vaccines is what the side effects look like. Since we’ve established that the virus is of little to no concern to myself and my family, I need to be able to perform a thorough cost benefit analysis if I were to consider receiving one or vaccinating my children. Similarly, if I were an octogenarian with a few underlying health conditions, I would want to know what the odds were that a vaccine would help rather than hurt.

At first glance, the initial trial reports leave me a bit discomforted. An initial concern is the trials were not designed to find side effects. The selection criteria were such that any who were likely to have complications after receiving the vaccines weren’t included in the trials. Apparently this is a common tactic in drug trials, such that the drug can be made to look as good as possible. Even with the deck stacked against finding potential complications, the Astra-Zeneca vaccine seemingly caused two cases of transverse myelitis (which in such a small sample size raises a major red flag), and the Pfizer one increased the incidence of severe adverse events, but they failed to specify what those adverse events were. The Moderna vaccine didn’t wind up with any black eyes in the trials, so it seems to be the one to go with in terms of both efficacy and safety.

However, these initial trials were limited, and at this point the vaccines have been rolled out all over the world, so we should have substantially more data available to evaluate the potential risks. When any new vaccine is launched, we use the Vaccine Adverse Event Reporting System (VAERS) to catalogue any complications that arise that may be due to the vaccine. Ideally we should be able to query the database and get a glimpse of what the potential side effects of the three vaccines look like today. Unfortunately it looks like it takes about nine weeks between someone submitting a report of an adverse event and that data becoming available in the database. This means we don’t have a real time picture of the safety of the vaccines, and we’ll wind up responding too late to any trends that may arise in the data.

Despite the backlog in data processing, it looks like the vaccines have already accrued more than 120,000 adverse events, more than 12,000 serious adverse events, and more than 3,500 deaths. Typically a drug is pulled from the market after 50 unexplained deaths. The current death count is higher than for any other vaccine in history. This should be significant cause for concern.

Next question: Do the vaccines in fact stop the spread of the virus? We saw that the initial trials were not really designed to answer this question, and even then they indicated that the answer might be “no,” but now that we have months of data from around the world, what can we say? Unfortunately the answer is a resounding “no,” from the doctor often credited for inventing mRNA technology, which is the technology behind the Pfizer and Moderna vaccines. A recent study out of Massachusetts shows that 74% of individuals testing positive for the delta variant were fully vaccinated, either with two doses of the Pfizer or Moderna vaccine, or the single course of the Johnson & Johnson one. More recent reporting indicates 77% of new cases in Iceland are in those who are fully vaccinated, and in Israel the number is 86%. Honestly these vaccines are starting to sound less and less like vaccines.

Note

Just last week I heard the phrase that the “delta surge is largely a pandemic of the unvaccinated.” If someone can give me data to support that claim, I’d love to see it.

Follow-Up

On September 9th, I was pointed to this WebMD article claiming that “almost all US COVID-19 deaths [are] now in the unvaccinated.” The article mentions some numbers to back up the claim, but doesn’t give you sources for the raw data, instead referring you to an Associated Press article as the source of its information. The WebMD article also includes a few anecdotes intended to convince you that vaccination is the best thing for you, but they don’t contain information that would be useful in assessing them (e.g., age at time of death, number of comorbidities, etc.).

The WebMD article also includes a link to a Deadline article making the same claim, but specific to Los Angeles county. This article mentions some numbers from a statement from the LA Department of Public Health, speaking to cases, hospitalizations, and deaths between December, 2020, and June, 2021, but it doesn’t indicate how the data were collected and analyzed, and it doesn’t give you access to the raw data to analyze it for yourself (though one commenter requests it). It then refers to the same Associated Press article for the rest of its information.

As far as I can tell, the Associated Press article doesn’t cite a single source (neither via footnotes nor links), but says that the information comes from “an Associated Press analysis of available government data from May, [2021,]” and that they also “analyzed figures provided by the [CDC].” Without any links or citations, there’s no way to know what data they’re looking at, and without any specificity, there’s no way to know how they carried out their analysis. Both of these complications mean there is no way to evaluate the trustworthiness of the information provided. They do note, however, that “the CDC itself has not estimated what percentage of hospitalizations and deaths are in fully vaccinated people, citing limitations in the data.”

Aside from the complete lack of transparency, the Associated Press article also suffers from a number of rhetorical problems. Like the WebMD article, it too includes anecdotal evidence without giving you full information to properly evaluate what the anecdotes do and do not show. Amplifying the anecdotal evidence are strong uses of appeals to emotion. The article also associates a dramatic drop in COVID-19-attributed deaths after January, 2021, to vaccinations, but offers no explanation of similar drops after both April and August, 2020. Finally, it uses imprecise language to say one thing but imply another. For instance, “cases, hospitalizations, and deaths are rising,” seems to be used to imply the situation is dire and due to people refusing vaccination. How much are they rising? How does today compare to last year? Are they rising based on what we’d expect from the seasonality of the virus? The article fails to answer any such questions that could allow us to effectively evaluate the information being presented.

It seems these articles are referencing people the authors consider to be trustworthy experts, and the authors are asking you to accept the claims made by these experts on faith. However, the authors and their experts provide no empirical evidence to support their claims, so you, if you have a data-driven, scientific mind, have no way of evaluating the truth or falsehood of the claims made. If you believe them, you do so solely on faith; if you doubt them, you have solid reason to, until any raw data is provided.

For what it’s worth, I went looking but couldn’t find data that tracked cases, hospitalizations, or deaths with vaccination status, either from the CDC or from Our World in Data. Again, if someone can show me the data to support these claims, I’ll happily take a look.

The next thing I’m curious about is whether or not the vaccines are necessary if you’ve already recovered from COVID-19. We’re being told that everyone needs to be vaccinated, but past experience tells us recovering from a virus should produce a similar immunity, so is that the case here? I’ll run through the evidence briefly, but check out this article if you want a longer explanation of the results. A study from April, 2021, shows immunity from prior infection to be at least as effective as the best vaccines in preventing reinfection. Another study from June shows no reinfections at all in the cohort studied that had previously recovered from COVID-19, so it sounds like prior infection provides all the immunity you need.

Final question, and then we’ll draw some conclusions: For anyone who hasn’t yet had COVID-19, are there any alternatives to the vaccines that offer either comparable protection or safe and effective treatment for the disease? In fact, there are a few straightforward measures you can take to decrease your risk of experiencing a severe infection. We saw earlier the importance vitamin D plays in your ability to fight off viruses, this one included. It therefore stands to reason that other preventative measures such as vitamin C, zinc, a healthy diet, fresh air, sunshine, and exercise would help you stack the deck in your favor. Beyond that, though, are there any options for when you get sick?

A first candidate that jumps out is hydroxychloroquine (HCQ), which is typically used to treat malaria and auto-immune diseases, like lupus and rheumatoid arthritis. It was developed in 1946, so we have plenty of experience with it. A systematic review of HCQ use on COVID-19 patients concluded

HCQ was found to be consistently effective against COVID-19 when provided early in the outpatient setting. It was also found to be overall effective in inpatient studies. No unbiased study found worse outcomes with HCQ use. No mortality or serious safety adverse events were found.

Another contender is ivermectin, which is typically used to treat parasitic infestations. It hasn’t been around as long as HCQ, but we still have 40+ years of experience with it. In May of this year, this meta-analysis of the studies of ivermectin use on COVID-19 patients showed a substantial reduction in the relative risk of dying, with some inconclusive indication that it might decrease the time for symptom resolution as well.

Note

If you’d like more information about COVID-19 treatment options not involving one of the available vaccines, see this treatment protocol and the research supporting it.

Note

As we enter into a time of public unease regarding the ethical considerations of vaccine mandates, this article on liberty of conscience, though lengthy, will be well worth your time.

What Can We Conclude?

This has been quite the whirlwind tour of the various pandemic countermeasures we’ve employed in the last year and a half. Let’s try to summarize what we’ve found and draw some conclusions.

Masks were not historically recommended for the general populace for pandemics of low to moderate severity, which our prior analysis indicates applies to COVID-19. Prior guidance aside, it appears the imposition of mask mandates has had no impact on the daily case and death data. This may be because the virus spreads via aerosols, in addition to droplets, and the majority of aerosols are not captured by masks, and instead wind up filling a room within minutes. Numerous studies indicate masks have no effect on viral spread, either for COVID-19 or in general, and some studies even indicate they don’t alter the chances of post-operative infection in surgical settings. There are a number of studies arguing for the efficacy of masks, but many tend to be mathematical modeling analyses of questionable value, and they typically exhibit poor methodology, drawing conclusions that contradict the data.

Given all this evidence, it seems clear that the CDC’s changing guidance on masking over the course of the pandemic hasn’t been motivated by evidence-based medicine. One has to wonder why there’s continued pressure to use them when they don’t do what they’re supposed to do.

Historically lockdown measures such as contact tracing, quarantining exposed individuals, entry and exit screening, and border closures were not recommended for a pandemic, regardless of severity. For some reason we abandoned well-established guidance and instead imposed various levels of lockdown around the world; however, these restrictions can be seen to have had no impact on the daily case and death rates. On the local scale, strict adherence to quarantine, masking, social distancing, one way traffic in buildings, etc., still leads to spread of COVID-19. A number of studies have been conducted looking for the impact non-pharmaceutical interventions (NPIs) have had on the spread of the disease, but the studies consistently show no correlation whatsoever between the more restrictive NPIs and mortality. (Washing your hands, however, is still good for you.)

Though it seemed justified early on in the pandemic to point to Czechia as an example of a hard lockdown conquering the virus, you could immediately counter by pointing to the UK with a similarly hard lockdown and some of the worst case rates in the world at the time. Also time has shown that the countries we might’ve initially thought had beaten the virus like Czechia simply hadn’t received it yet; they were hit hard later on. Given all the data available from the last 18 months, one has to wonder why cities, states, and countries the world over are now returning to various degrees of lockdown when that does nothing to slow the spread or prevent deaths.

The rush to get COVID-19 vaccines to market as quickly as possible raises a number of questions about the safety and efficacy of the vaccines. The initial trials designed to earn them the emergency use authorization suffer from poor design, and in some cases execution. They can really only tell us how well the vaccines reduce COVID-19 symptoms in young healthy people, while we’d like to know if they’re safe and effective for the most vulnerable (70+ with one or more underlying conditions). In terms of side effects, the Astra-Zeneca vaccine possibly causing transverse myelitis, and the Pfizer one increasing the incidence of unspecified severe adverse events, are concerning. Beyond that, the Vaccine Adverse Event Reporting System (VAERS) data being lagged by nine weeks mean we won’t be able to respond promptly to trends developing in the side effect data, and at this point we’ve already seen more than 3,500 deaths associated with the vaccines, meaning they should’ve been pulled from circulation ages ago.

On top of all these concerns, it appears the vaccines don’t actually stop you from either contracting COVID-19 or spreading it to others. The good news, though, is having recovered from the disease provides you with equal or better immunity, so in many cases the vaccines simply aren’t needed. And if you want to combat the virus without one of the vaccines, hydroxychloroquine (HCQ) and ivermectim have proven themselves safe and effective treatments. One has to wonder why, in the context of limited vaccines and a press for global herd immunity as soon as possible, we’re pressuring everyone in the world to get vaccinated when it appears it’s largely unnecessary, and if treatment becomes necessary, we’ve had safe, effective, cheap, generic treatments like HCQ and ivermectin on hand since before the pandemic began.

Note

“Coercing” might be a better word than “pressuring,” given what I’ve heard in the past week of people losing their jobs, being fined $200/month, being restricted from air and rail travel, etc., for not getting vaccinated.

Bottom line: Masks don’t protect me from you or you from me. Lockdowns don’t have any impact on case rate or mortality. The available vaccines only appear to be effective therapeutics, but with significant risk involved. Alternative treatments are available with negligible risk. Given this summary of the efficacy of the countermeasures we’ve employed in combatting the pandemic over the last 18 months, here are some questions for you to wrestle with:

  • Why do you continue to use various countermeasures if they’ve proven themselves ineffective?

  • How long will you continue?

  • When will we reach the point when “enough is enough”?

  • If there doesn’t seem to be any harm to them, should you just keep going with the flow?

The Consequences of Countermeasures

At this point we’ve shown it’s completely reasonable to conclude that the danger of COVID-19 has been grossly exaggerated, and there’s more than enough evidence to conclude that the countermeasures we’ve employed over the last year and a half haven’t had their desired effect. However, we’re still being told we must do whatever is necessary to stop the virus, and it doesn’t look like cities and countries the world over will be abandoning non-pharmaceutical interventions (NPIs) any time soon. Something we were deeply concerned about in March of 2020 was what the short- and long-term consequences of any such countermeasures would be, but it was exceedingly difficult then to get people to try to consider the ramifications, as the world was gripped by fear of the potential severity of the pandemic. Now, a year and a half later, we can attempt to assess how any such consequences have played out.

Overview

As we examine the ramifications of the various masking, lockdown, and vaccination policies that have been put in place around the world, we’ll be looking at the evidence in terms of both the medical and then the societal consequences. To begin, though, it will be worthwhile to get a broad overview by starting with excess mortality data. If you’ve been following along with the data in the earlier parts of this analysis, excess mortality is a concept you’ve been exposed to, though we haven’t defined it yet. In brief, it is the number of deaths in a given area in a given time period over (or under, if it turns out to be negative) what can reasonably be expected for the number of deaths in that area in that time period, where that estimate for expected deaths is calculated based on prior years’ mortality data, accounting for changes in the age and health of the population. The reason we look to excess mortality data first is it’s really the only hard measure by which we can compare the impact of the pandemic itself to the impact of our response to it.

So what do the data show? First it’s important to realize that we don’t have all the data available yet, as it’s generally not available in real time, and we haven’t returned to normal yet, but at this point the numbers are in for 2020, so we can see what they have to say. All told, the US saw about 300,000 excess deaths in 2020, with two-thirds of them attributed to COVID-19. That means we’re looking at about 100,000 deaths that we didn’t expect for which we’re trying to find an explanation. What’s both confusing and distressing about the data from the US is the demographics that saw the largest percentage increases in excess mortality were those who were Hispanic or Latino, and those in the 25–44 age bracket, meaning certain ethnicities and younger adults were impacted more significantly than others by our response to the pandemic. Additional research backs this up, and also adds that men experienced more excess death than women in the US. A study in Canada noticed similar patterns.

To get an idea of whether or not this excess mortality is likely due to the NPIs we’ve put in place, it’s worth comparing countries with more restrictive NPIs (e.g., US, UK) to those with less restrictive NPIs (e.g., the Nordic countries). Indeed such a comparison shows countries with less severe lockdown measures to have generally lower excess mortality on a percentage basis than those with more significant lockdowns. The pattern is noticeable across all age groups, but is particularly pronounced in the younger demographics. A Stanford doctor has claimed that “lockdowns are the biggest health mistake we’ve ever made,” and our initial look at excess mortality data suggests he may be right.

Note

If you’d like another perspective on the death count attributable to lockdowns, this article is well worth your time. If you’d like to do your own data mining to draw your own conclusions, these resources will likely be of use to you:

Thus far we’ve only looked at observational data, which I strongly prefer, but before we leave the overview I’m actually going to point you to a modeling study for your consideration. You’ve heard a number of times my skepticism when it comes to using mathematical modeling as a basis for public policy decision-making, particularly when the models prove themselves inaccurate as real-world data becomes available, but that doesn’t mean I discount them altogether. When considered appropriately within the broader context, they can give us useful food for thought when weighing alternatives, with the understanding that at the end of the day they are merely extrapolations. This particular one was trying to estimate the impact of school closures on the years of life lost, and concluded that keeping schools open may have resulted in fewer years of life lost in the long run. The excess mortality data we looked at above indicates there are short-term consequences to our pandemic response that we’ve already realized and will continue to realize if we keep more restrictive NPIs in place. This modeling study suggests there may be longer-term consequences that may only unfold over the next few generations.

But where are all these additional deaths coming from?

Medical Consequences

A first place to look is to the medical literature to see if there have been any changes in what we typically expect for various illnesses. We’ll first examine whatever we can in terms of death data, as that’s a concrete measure, and then wrap up with any other consequences we find in the medical arena.

Deaths

A first category that stands out is cardiovascular diseases. One study reports an 8% increase in overall cardiovascular mortality, with 35% more deaths occurring in the home, and 32% more occurring in extended care homes, than would be expected. The most frequent causes were stroke, acute coronary syndrome, and heart failure. Another study noted a peculiar decrease in the number of hospitalizations for acute myocardial infarction (AMI, or heart attack), along with a substantial increase in the risk-adjusted mortality rate. Another study specific to stroke victims detected the median time from the onset of symptoms to arrival in the hospital more than doubled from about two and a half hours to more than six. In the case of stroke, getting someone to a hospital as soon as possible is absolutely critical to the chances of recovery. Though the studies don’t give a direct cause for these changes in behavior and outcomes, it seems we can reasonably infer that individuals were waiting longer after the onset of symptoms to seek medical help, resulting in worse outcomes overall, including excess deaths.

Leaving cardiovascular diseases behind, we see similar patterns when it comes to cancer. In March, 2020, the CDC issued guidance to health care providers around the country for non-COVID-19-related care, with the goals of slowing the spread, appropriately allocating PPE, etc. These guidelines contributed to the number of routine in-person cancer screenings plummeting, which in turn contributed to the number of new diagnoses of cancer dropping nearly 50% from early March to mid-April, 2020. This sharp decline is indicative of cases that would’ve been caught earlier, were it not for our reaction to the pandemic. Since with cancer the earlier the diagnosis, the better the prognosis, our countermeasures have led to degraded outcomes for cancer patients.

The next diseases we’ll turn to are Alzheimer’s and dementia, which saw a 10% increase in excess mortality between March and August of 2020. The degrading conditions of patients stem from the strategy of isolation we’ve adopted, ostensibly for their own safety. “Doctors have reported increased falls, pulmonary infections, depression and sudden frailty in patients who have been stable for years.” This shouldn’t come as a surprise to us, as we’ve known for ages that social and mental stimulation are some of the few tools we have available to slow the progression of the disease; taking them away will naturally lead to rapid degeneration and a hastened death. Throughout this analysis I’ve attempted to stick dispassionately to the data and medical and other reporting, and to steer clear of making value judgements, but in this case I cannot. In addition to the raw data, the article linked above also gives you an idea of what the human component looks like in all our efforts to protect the most vulnerable. The way we as a society have treated the elderly is downright evil, and constitutes elder abuse of the most heinous variety.

In addition to all of the above, we noted earlier that the vaccines are resulting in death more often than is reasonable. And while in our last area of analysis we noted the ineffectiveness of face masks, it turns out there are also a number of risks associated with them as well. In some cases that means mild difficulty breathing or skin irritation, in others there are severe psychosocial consequences (which we’ll revisit down below), and in a small handful of cases mask wearing seems to have resulted in death.

Note

It may be worth your time to read over the Great Barrington Declaration, which was written by infectious disease epidemiologists and public health scientists, recommending an approach of “focused protection”. It has garnered over 850,000 signatures.

Other Impacts

In addition to the immediate death toll that has already been realized (and will likely continue to be, if we don’t do anything), there are likely also a handful of other ramifications that will play themselves out over the coming years. One of those is it appears in our efforts to prepare for and combat COVID-19, measles vaccination programs were halted in 26 countries around the world, meaning 94 million children were at risk of missing their vaccinations for a disease that largely kills children under the age of five. In 2019 we saw just shy of 900,000 cases of the measles around the world. Using cohort life tables, which insurance companies use to predict how long someone will live, given their age, this analysis of years of life lost due to COVID-19 estimates that if a mere 0.1% of those who have been denied their measles vaccine wind up dying, that will equal the estimated number of years of life lost to COVID-19 itself. Granted, that’s speculation, but since we know the danger of measles and have a safe and effective preventative for it, why should we gamble in such a way, particularly since COVID-19 does not pose near the same threat, and our protective measures that led to the halt of the measles vaccinations have proven themselves ineffective?

Societal Consequences

Now that we’ve looked at the problems caused with a variety of medical issues, let’s turn our attention to any other factors that might be negatively impacting the world. Again, we’ll first examine whatever might be contributing directly to the overall excess death we looked at in the beginning, and then follow that up with any other bad side effects our response to the pandemic may have caused.

Deaths

Before we get into how things played out, let’s take a look at some projections first. One study estimated between 8,000 and 200,000 all-cause excess deaths attributed to COVID-19-related unemployment during the first year of the pandemic, with the most likely estimate being 30,000. Another study predicted between 27,000 and 154,000 deaths of despair (alcohol and drug misuse, and suicide) based on unemployment and economic projections, with 75,000 being the most likely estimate. It did note, however, that “when considering the negative impact of isolation and uncertainty, a higher estimate may be more accurate.” I mention these modeling studies not to try to give an accurate prediction of how things would turn out, but rather to point out that people tried to warn us of the consequences if we continued on the course we were headed on early in the pandemic.

Let’s see what kind of studies are available. One paper indicates there’s been an increase in suicide during the pandemic, spurred by “feelings of uncertainty, sleep disturbances, anxiety, distress, and depression.” The authors also caution that the psychological and financial costs may result in long-term psychological conditions. Another indicates a substantial increase in alcohol use, which likely contributes to the worsening case rates for anxiety, depression, and suicide. The most substantial change was in heavy drinking, with a 41% increase over the baseline. Yet another report indicates the drug overdose deaths were rapidly accelerating in the early days of the pandemic.

Perhaps one of the more surprising results is 2020 saw the highest number of motor vehicle deaths in 13 years, and the year-to-year spike of 24% was the highest we’ve seen in almost a century. “That doesn’t make sense,” you might think. “Nobody was driving last year.” Indeed, the overall number of miles driven was down by an estimated 13–16%, but somehow with emptier roads we wound up with more fatalities. It appears this is due to a substantial increase in riskier driving behavior, with drugs, alcohol, and excessive speed leading to more collisions and more deadly ones. These changes in driver behavior seem to correlate with the lockdown measures that went into effect in the second quarter of 2020.

Other Impacts

In addition to the side effects of our decisions that contributed directly to the excess death toll, there are also a number of other issues that arise that contribute to the overall deterioration of society. One of our concerns when the world decided to shut down was what that would do to children living in unsafe home environments. If the home is already unsafe, due to substance abuse or any number of things, and you add to that the stress and anxiety brought on by the pandemic, business closures and job losses, and mandatory stay-at-home orders, how much more dangerous does that make the home environment? While I wasn’t able to find a direct answer to that question, there was a study that was tangentially related, which found a fifteen-fold increase in abusive head trauma (AHT, which includes “shaken baby syndrome”) in infants during the first month of lockdown measures. I hope to see more studies on the correlation between lockdowns and the safety of the home environment in the future.

Another question we had early on was what masks do to communication within society. Humans have enough issues communicating effectively as it is; what happens when everyone hides half their faces? The answer is it gets much harder, but I’m sure I didn’t need to tell you that. Masks hide a good deal of non-verbal communication, which can make it more difficult to understand tone and intent. When the little gestures like “social smiling” disappear, that has a significant impact on the health of society. While the authors suggest using more gestures can do something to make up for the deficit, given what we know about the danger of the virus and the efficacy of masks, you’re probably better off just removing them.

Now let’s turn for a moment to economic impacts. In March and April of 2020, the number of active business owners in the US plummeted by 3.3 million (22%). The US has never seen a drop that significant in a twelve-month period, let alone two. This in turn contributed to the substantial unemployment shock, which then contributed to the various problems listed above. The unemployment shock was predicted to result in ~800,000 additional deaths over the next 15 years, but keep in mind, that’s an extrapolation; we’ll have to wait and see what really happens.

On the religious front, lockdown measures in particular, and the stress of the pandemic and our response to it in general, have led to increased persecution of Christians in various parts of the world. There was a 60% increase in the number of Christians killed for their faith compared to 2019. Though not all of that increase is attributable to our pandemic response, Christians being denied COVID-19-related aid in numerous countries in Africa and Asia is. In sub-Saharan Africa, Islamist militant groups took advantage of lockdowns and governments weakened by the crisis to ratchet up the level of violence. This sort of persecution of religious minorities was already happening around the world, but the way we responded to the pandemic gave aggressors an opening to “kick it up a notch.”

And now the final societal side effect from our response to the pandemic: world hunger. Last year, from late spring through the summer, there were a handful of reports predicting significant increases in world hunger throughout the pandemic. The 2020 State of Food Security and Nutrition in the World report from the United Nations estimated an additional 120 million people would be facing food scarcity, who would not have otherwise were it not for the NPIs we’d put in place. Other reporting predicted 12,000 deaths per day from starvation, more than we were expected to see from the virus. At the time this was generally seen as alarmist reporting, and the developing story saw surprisingly little coverage through the rest of 2020 and early 2021. At this point, though, we have the data on hand to see that some of the worst fears have indeed come to pass. The UN’s 2021 report has just been released, and it shows the single biggest year-to-year increase in global hunger in decades, with 161 million more people experiencing it than in 2019. It’s estimated that about three-quarters of that increase (118 million) is due to the hard policies of lockdowns and related measures and the single-minded focus on the virus.

What Can We Conclude?

This has probably been a lot to absorb. Let’s take a moment to summarize what we’ve learned.

A sizeable portion of the excess deaths (at least a third, probably more) are not directly attributable to COVID-19, but are instead attributable to our response to it. The unaccounted for excess deaths seem to be particularly prevalent in the younger demographics. A comparison across countries indicates less restrictive NPIs correlate with lower excess mortality and more restrictive NPIs correlate with higher excess mortality; that is, the more we’ve tried to forcibly stamp out COVID-19 (and failed miserably, as our prior analysis suggests), the more we’ve contributed to the deaths of others.

In trying to determine where all the excess deaths are coming from, we find that cardiovascular mortality is up overall, with significantly more deaths happening in homes and assisted living facilities. Stroke victims were taking more than twice as long to make it to the hospital, significantly impacting the chances of recovery. All this means people have been waiting longer than they otherwise would have before seeking treatment, leading to disastrous consequences. Cancer screenings plummeted, due to new guidance for non-COVID-19-related care, leading to substantial increases in missed diagnoses. We saw a 10% rise in excess mortality for Alzheimer’s and dementia patients, as all the forced isolation measures put in place for the patients’ safety directly contributed to their rapid deterioration while their loved ones watched from a distance. It seems our attempts to protect the elderly and frail have instead contributed to their demise.

The COVID-19 vaccines themselves have contributed to a significant number of deaths, and at this point it looks like masks have contributed to a handful as well. Measles vaccination programs that were halted so countries could prepare for and respond to COVID-19 could easily wind up contributing to more years of life lost than this pandemic does.

In addition to the medical issues, we’ve seen increases in suicide, heavy drinking, and drug overdoses. Counter-intuitively, 2020 saw the highest number of motor vehicle deaths in 13 years. Though there were fewer people on the road, those who were driving were engaging in riskier behavior, likely motivated by the stress of the pandemic response, and compounded by the substance abuse problems.

In addition to the direct contributions to the non-COVID-19 death toll, there have also been a number of less tangible impacts on society. Shaken baby syndrome saw a significant increase, likely due to the various stresses added to life by our response to the pandemic. Communication was impaired by masks, leading to a degradation of social graces and an increased tension in social interactions. Small business were hit harder than they ever have been before, contributing to an unemployment shock that we’ll likely still be feeling the aftermath of over a decade later. All of the instability around the world set the stage for an increased persecution of Christians, both through execution, and through COVID-19 aid distribution programs.

Finally, an additional 118 million people faced food scarcity last year than would have otherwise were it not for our self-imposed pandemic countermeasures. It’s hard for people in rich, Western nations to wrap our heads around what’s meant by global hunger. Try going without food for the next three days—pretend you can’t simply open the refrigerator to sate your hunger, and you’re not sure when your next meal will be—and then imagine that for a third of the population of the United States.

Bottom line: For decision-makers to set policy, whether they’re in local or national government or private businesses or other organizations, without a balanced consideration of the consequences such policies may have, is unethical. We knew the majority of these consequences were coming ahead of time, and we ignored them. Instead we decided what’s best for the world was a single-minded focus on stamping out the virus, no matter what it takes, and no matter who suffers in the process. Our behavior has been reprehensible.

If you’re anything like me, wading through all of the above has likely left you with a profound sense of grief. Don’t squander that. Wrestle with the following questions:

  • Why is all of the above so troubling?

  • Given the myriad ways things have gone so wrong, is there something at the root of what’s wrong with the world?

  • Is there any way to fix all this?

What Does All This Mean?

At this point, we can answer the questions that launched our investigation with reasonable certainty:

  1. The danger posed by the disease has been grossly exaggerated.

  2. The various countermeasures we have employed—specifically masks, lockdowns, and vaccines—have proven themselves ineffective.

  3. The consequences of those countermeasures have been too costly, and will continue to be if we don’t do something.

What does all this mean? I’m afraid it means you’re being lied to. I’m not going to speculate here as to the “why”, and I’m going to try to assume the best of intentions in any given individual, but the near-constant stream of reporting you’ve been fed over the last year and a half speaking to the grave dangers of the pandemic: those are lies. The woman at the store who gets irate with you because you not wearing a mask puts her in danger: that’s a lie. The community organization that switches to online-only meetings because it will keep everyone safe: that’s a lie. The employer requiring you to be vaccinated to keep your job because that’s the only way we make it through this pandemic: that’s a lie. The implicit assumption that any negative side effects that come from our decisions don’t matter, because the danger of the virus is definitely worse: that’s a lie.

How should you respond in light of all this? I won’t prescribe anything; that’s for you to decide. As for me and my household, we will no longer be complying with any government or business requests to wear masks or socially distance, and we will not be getting any of the available COVID-19 vaccines. To do so would be to tacitly agree that the situation is as dangerous as reported, that the countermeasures work to slow the spread and prevent death, and that the consequences of the countermeasures don’t matter. That we cannot do.

We do not do this for the sake of being troublemakers, but because our consciences no longer allow us to comply, given all that we have learned in the last year and a half. In hindsight, I think we should have taken this stand much sooner. We are aware that taking such a stand will likely lead to confrontation, and we will endeavor to handle such situations with grace and compassion. We hope they will be opportunities to begin an open dialogue on all of these points.

Last spring someone pointed me to this excerpt from “On Living in an Atomic Age” (1948), by C.S. Lewis, in Present Concerns: Journalistic Essays, and told me to replace any references to the atomic bomb with the coronavirus, as I’ve done below. I find it a fitting way to conclude.

In one way we think a great deal too much of the [virus]. “How are we to live in [a pandemic] age?” I am tempted to reply: “Why, as you would have lived in the sixteenth century when the plague visited London almost every year, or as you would have lived in a Viking age when raiders from Scandinavia might land and cut your throat any night; or indeed, as you are already living in an age of cancer, an age of syphilis, an age of paralysis, an age of air raids, an age of railway accidents, an age of motor accidents.”

In other words, do not let us begin by exaggerating the novelty of our situation. Believe me, dear sir or madam, you and all whom you love were already sentenced to death before the [coronavirus] was invented: and quite a high percentage of us were going to die in unpleasant ways. We had, indeed, one very great advantage over our ancestors—anesthetics; but we have that still. It is perfectly ridiculous to go about whimpering and drawing long faces because the scientists have added one more chance of painful and premature death to a world which already bristled with such chances and in which death itself was not a chance at all, but a certainty.

This is the first point to be made: and the first action to be taken is to pull ourselves together. If we are all going to be destroyed by [a pandemic], let that [virus] when it comes find us doing sensible and human things—praying, working, teaching, reading, listening to music, bathing the children, playing tennis, chatting to our friends over a pint and a game of darts—not huddled together like frightened sheep and thinking about [viruses]. They may break our bodies (a microbe can do that) but they need not dominate our minds.

We are not currently living as we are meant to. As Aleksandr Solzhenitsyn said the day before he was exiled to the West, “Live not by lies.” Live instead in accordance with the truth of reality.

Disclaimer

These pages represent about 55 hours of research and writing on my part. I think that should be more than sufficient for a project such as this, but it does mean I didn’t have time to find and read every piece of evidence that may have bearing on these issues. If I’ve missed something, or if new results come to light after this piece is published, that may call into question one or more of the conclusions I’ve drawn, and I’ll be happy to revisit them with the new data.

References

  1. https://adc.bmj.com/content/106/3/e14

  2. https://advance.sagepub.com/articles/preprint/Comment_on_Flaxman_et_al_2020_The_illusory_effects_of_non-pharmaceutical_interventions_on_COVID-19_in_Europe/12479987

  3. https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021GH000413

  4. https://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2020.306095

  5. https://apnews.com/article/coronavirus-pandemic-health-941fcf43d9731c76c16e7354f5d5e187

  6. https://apps.who.int/iris/rest/bitstreams/1291156/retrieve

  7. https://beyond.britannica.com/what-is-excess-mortality-and-how-is-it-calculated

  8. https://bmjopen.bmj.com/content/bmjopen/5/4/e006577.full.pdf

  9. https://childrenshealthdefense.org/news/if-covid-fatalities-were-90-2-lower-how-would-you-feel-about-schools-reopening/

  10. https://covid.cdc.gov/covid-data-tracker/#datatracker-home

  11. https://dailynews.ascopubs.org/do/10.1200/ADN.20.200416/full/

  12. https://dailysceptic.org/2021/02/27/latest-news-298/#the-more-stringent-the-lockdown-the-higher-the-covid-death-toll

  13. https://dailysceptic.org/replying-to-christopher-snowdon-again/

  14. https://deadline.com/2021/06/99-p4rcent-covid-deaths-los-angeles-unvaccinated-1234781402/

  15. https://elemental.medium.com/i-see-you-but-i-dont-how-masks-alter-human-connection-fbf2e21dd748

  16. https://en.wikipedia.org/wiki/N95_respirator

  17. https://en.wikipedia.org/wiki/Transverse_myelitis

  18. https://evidence.nihr.ac.uk/themedreview/living-with-covid19/

  19. https://factcheck.afp.com/doctor-expired-license-falsely-claims-masks-dont-work

  20. https://fallacyinlogic.com/anecdotal-fallacy-definition-and-examples/

  21. https://founders.org/2021/08/13/vaccine-mandates-and-the-christians-liberty-of-conscience-from-2021-to-1721-and-back-again/

  22. https://gbdeclaration.org/

  23. https://github.com/TheEconomist/covid-19-excess-deaths-tracker

  24. https://globalnews.ca/news/8122807/canada-election-covid-19-madatory-vaccination/

  25. https://heart.bmj.com/content/107/2/113

  26. https://jamanetwork.com/journals/jamacardiology/fullarticle/2769293?guestAccessKey=4425a07e-573b-45ec-9a16-82e32ecf762f&utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_content=tfl&utm_term=080720

  27. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2770975

  28. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2772834?utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_term=111220

  29. https://journals.healio.com/doi/10.3928/00485713-20201105-01

  30. https://onlinelibrary.wiley.com/doi/10.1111/eci.13423

  31. https://onlinelibrary.wiley.com/doi/full/10.1111/eci.13484

  32. https://ourworldindata.org/coronavirus

  33. https://ourworldindata.org/grapher/biweekly-confirmed-covid-19-cases?tab=chart&time=earliest..latest

  34. https://ourworldindata.org/grapher/biweekly-covid-deaths?tab=chart&time=earliest..latest

  35. https://ourworldindata.org/grapher/covid-stringency-index?tab=chart&country=AUT~BEL~CZE~DNK~FIN~FRA~DEU~ITA~LVA~LTU~NOR~POL~PRT~SVN~ESP~SWE~CHE~GBR~USA

  36. https://ourworldindata.org/grapher/excess-mortality-p-scores-by-age?country=SWE~NOR~USA~FIN~GBR~DNK

  37. https://oxfamilibrary.openrepository.com/bitstream/handle/10546/621023/mb-the-hunger-virus-090720-en.pdf

  38. https://paulyowell.substack.com/p/the-nordics-and-the-baltics

  39. https://rightsfreedoms.wordpress.com/2021/08/07/dr-malone-cdcs-own-data-shows-masks-vaccines-dont-stop-covid-junk-science-is-driving-authoritarianism/

  40. https://sebastianrushworth.com/2020/11/06/how-accurate-are-the-covid-tests/

  41. https://sebastianrushworth.com/2020/11/17/what-is-long-covid/

  42. https://sebastianrushworth.com/2020/11/29/how-many-years-of-life-are-lost-to-covid/

  43. https://sebastianrushworth.com/2021/01/10/are-the-covid-vaccines-safe-and-effective/

  44. https://sebastianrushworth.com/2021/04/17/is-the-astra-zeneca-vaccine-killing-people/

  45. https://sebastianrushworth.com/2021/05/09/update-on-ivermectin-for-covid-19/

  46. https://sebastianrushworth.com/2021/07/13/does-it-make-sense-to-vaccinate-those-who-have-had-covid/

  47. https://sebastianrushworth.com/2021/07/19/do-drug-trials-underestimate-side-effects/

  48. https://sma.org/post-viral-syndrome/

  49. https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0240287/1/pone.0240287.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210827%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20210827T202406Z&X-Goog-Expires=86400&X-Goog-SignedHeaders=host&X-Goog-Signature=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

  50. https://stovouno.org/2020/11/12/there-is-no-covid-test-and-the-casedemic-is-a-shameless-scam/

  51. https://swprs.org/covid19-lethality-how-not-to-do-it

  52. https://swprs.org/covid-just-a-casedemic/

  53. https://swprs.org/face-masks-evidence/

  54. https://swprs.org/on-the-treatment-of-covid-19/

  55. https://tamhunt.medium.com/lockdown-policies-have-vastly-exacerbated-global-hunger-b878b25e85d

  56. https://thefatemperor.com/scientific-analyses-and-papers-on-lockdown-effectiveness/

  57. https://thefatemperor.com/wp-content/uploads/2020/11/WHO-Pandemic-Guidelines-2019.pdf

  58. https://undercurrents723949620.wordpress.com/2021/05/13/why-were-not-hearing-about-covid-vaccine-side-effects/

  59. https://vaersanalysis.info/2021/06/23/what-is-the-backlog-in-terms-of-time-for-the-publishing-of-vaers-records-for-covid-19-vaccines/

  60. https://vaers.hhs.gov/

  61. https://videopress.com/embed/4egEyh2b?hd=1&loop=0&autoPlay=0&permalink=1

  62. https://wallethub.com/edu/states-coronavirus-restrictions/73818

  63. https://watermark.silverchair.com/ciaa939.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAsAwggK8BgkqhkiG9w0BBwagggKtMIICqQIBADCCAqIGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMJ8N9Iqq39Si2OXZeAgEQgIICcyryY8OT3U5SwIqAF4NqwieFQ0hGJKCQPws0ayakFJ6QWacOvbDNCacKO25bI8R-qdDltbJYAzTa9DQ1MNOytgoMWdnfC5wniKdb7BKja4sP-T2koSw-GAhGIUmfvt8FpNOAIr3c_yGgGX7IOtWhBFcTGse43cynw6TsEbB5AToRjlJcDKyzCg-vtBbc7CGfCH62cuBkn3gomxnboGIsXTcFElX5ePGDcQVqqPmtwbvNFCs6pBDeOgrYT48d_UUZ3OXFBaBhVQqBP80a-Z1aIhnBhn4CUJbiDeArl5x0GS44R0gEpvhWvcUaU4Z8GckEgiiEXELb9hrj-FelhEpbRhCRkmf9aoLLaMFIghfsKzoPu0LAOecHq1l3U_4qylxkIvGAUEktcG5Z9HZUIOu2i8fqMeZzGsNayJKFD6_eKNc5vFsqooU0gHC6wTQ_9oMsuXgWNt2jS36sDk5aH1n9PYTC_IsHj9oA2nF2H0Sm5ukahbXI2GLG8RRpKMmUxamQc_huCx5SenPyCh1LnoYRn36vOqYsSTv3CbahnrOEyH_cumGVvYt6Zv9_zy5QA7yeRwY_3EmFwxXz15VYHAy7YduFvA8_Zwg4eH97dcKGYYIyLEjRTo1W5i7KIu6ho8BYZy5F_eUzseks3QIfQiJKyMD0B5lsknNRLMi9ews49wxV4FtBHkWzmrBf5rerFDsD2ra5jVULGZ9KldyvOv4zURM0FJgubnym576FZoAZmLWwsA_1vrRyTtw3WPAJ23vI3hFfKPb5HrILbbpEzb6w7yCjbTJNckKdTPCB6YgtR0Z4RyoSZ2XMshACh11JuMsrxFn0iQ

  64. https://wellbeingtrust.org/areas-of-focus/policy-and-advocacy/reports/projected-deaths-of-despair-during-covid-19/

  65. https://www150.statcan.gc.ca/n1/en/daily-quotidien/210208/dq210208c-eng.pdf?st=FUoSbNT4

  66. https://www.acpjournals.org/doi/full/10.7326/M20-6817

  67. https://www.aier.org/article/lockdowns-do-not-control-the-coronavirus-the-evidence/

  68. https://www.americanthinker.com/articles/2020/09/its_a_covid_casedemic_not_a_pandemic.html

  69. https://www.caranddriver.com/news/a34240145/2019-2020-traffic-deaths-coronavirus/

  70. https://www.cdc.gov/media/releases/2020/p1218-overdose-deaths-covid-19.html

  71. https://www.cdc.gov/mmwr/volumes/69/wr/mm6942e2.htm

  72. https://www.cdc.gov/mmwr/volumes/70/wr/pdfs/mm7031e2-H.pdf

  73. https://www.cdc.gov/nchs/data/misc/hb_cod.pdf

  74. https://www.cdc.gov/nchs/data/misc/hb_me.pdf

  75. https://www.cdc.gov/nchs/data/nvss/coronavirus/Alert-2-New-ICD-code-introduced-for-COVID-19-deaths.pdf

  76. https://www.cdc.gov/nchs/nvss/vsrr/COVID19/index.htm

  77. https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm#Comorbidities

  78. https://www.cebm.net/covid-19/infectious-positive-pcr-test-result-covid-19

  79. https://www.cebm.net/covid-19/masking-lack-of-evidence-with-politics/

  80. https://www.cidrap.umn.edu/news-perspective/2020/04/commentary-masks-all-covid-19-not-based-sound-data

  81. https://www.city-journal.org/death-and-lockdowns?wallit_nosession=1

  82. https://www.city-journal.org/do-masks-work-a-review-of-the-evidence?wallit_nosession=1

  83. https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD006207.pub5/epdf/abstract

  84. https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD013574.pub2/full

  85. https://www.ecdc.europa.eu/sites/default/files/documents/covid-19-face-masks-community-first-update.pdf

  86. https://www.frontiersin.org/articles/10.3389/fpubh.2020.604339/full

  87. https://www.ijidonline.com/action/showPdf?pii=S1201-9712%2820%2932180-9

  88. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf

  89. https://www.lifesitenews.com/news/47-studies-confirm-inefectiveness-of-masks-for-covid-and-32-more-confirm-their-negative-health-effects/

  90. https://www.medrxiv.org/content/10.1101/2020.04.11.20062133v1.full.pdf

  91. https://www.medrxiv.org/content/10.1101/2020.10.19.20214494v2.full.pdf

  92. https://www.medrxiv.org/content/10.1101/2020.12.28.20248936v1.full.pdf

  93. https://www.medrxiv.org/content/10.1101/2021.06.01.21258176v3.full.pdf

  94. https://www.nber.org/system/files/working_papers/w27309/w27309.pdf

  95. https://www.nber.org/system/files/working_papers/w28304/w28304.pdf

  96. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2493952/pdf/annrcse01509-0009.pdf

  97. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338130/

  98. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534595/pdf/main.pdf

  99. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965847/

  100. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164734/

  101. https://wwwnc.cdc.gov/eid/article/26/5/pdfs/19-0994.pdf

  102. https://www.nejm.org/doi/full/10.1056/NEJMoa2029717

  103. https://www.nejm.org/doi/full/10.1056/NEJMp2006372

  104. https://www.nejm.org/doi/pdf/10.1056/NEJMoa2034577?articleTools=true

  105. https://www.nejm.org/doi/pdf/10.1056/NEJMoa2035389?articleTools=true

  106. https://www.newsweek.com/stanford-doctor-calls-lockdowns-biggest-public-health-mistake-weve-ever-made-1574540

  107. https://www.nsc.org/newsroom/motor-vehicle-deaths-2020-estimated-to-be-highest

  108. https://www.rt.com/op-ed/530567-cdc-fauci-covid-mask-guidance-history/

  109. https://www.sciencedirect.com/science/article/abs/pii/S0033350620304467?via%3Dihub

  110. https://www.scribd.com/document/490005936/The-Transmission-of-Epidemic-Influenza-by-R-Edgar-Hope-Simpson-1992-257pp-pdf

  111. https://www.spiegel.de/international/world/reconstruction-of-a-mass-hysteria-the-swine-flu-panic-of-2009-a-682613-amp.html

  112. https://www.theepochtimes.com/mkt_morningbrief/whos-really-being-hospitalized_3963392.html?utm_source=morningbriefnoe&utm_medium=email2&utm_campaign=mb-2021-09-02&mktids=103e4a8a3568d4bc6067c7183d607118&est=G681s9gkkIWKa0AW%2F%2BH0qtJMw0XtRAx%2BM4D08osLTy4Q8blcVSJ30sNiIb5SnZh6yH3z

  113. https://www.theepochtimes.com/unvaccinated-delta-staff-to-pay-200-monthly-health-surcharge_3964980.html

  114. https://www.theguardian.com/global-development/2020/nov/13/measles-cases-900000-worldwide-in-2019

  115. https://www.theguardian.com/world/2021/jan/13/christian-persecution-rises-as-people-refused-aid-in-covid-crisis-report

  116. https://www.thelancet.com/action/showPdf?pii=S0140-6736%2820%2932661-1

  117. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736

  118. https://www.thieme-connect.com/products/ejournals/pdf/10.1055/a-1174-6591.pdf

  119. https://www.usmortality.com/

  120. https://www.washingtonpost.com/health/2020/09/16/coronavirus-dementia-alzheimers-deaths/?arc404=true

  121. https://www.webmd.com/vaccines/covid-19-vaccine/news/20210629/almost-all-us-covid-19-deaths-now-in-the-unvaccinated

  122. https://www.youtube.com/embed/_XCE1lZwASc

  123. https://www.zerohedge.com/covid-19/why-cdc-quietly-abandoning-pcr-test-covid

  124. https://z3news.com/w/why-masks-are-a-charade/

  125. http://www.fao.org/3/ca9692en/ca9692en.pdf

  126. http://www.fao.org/3/cb4474en/cb4474en.pdf