Sep 27, 2021

SARS-CoV-2 Origins, Immunology, and Treatments. Here’s What We Really Know About “The Science™” (PART II)

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In Part I of this series we discussed the basics of immunology, the structure and pathophysiology of the SARS-CoV-2 virus, and controversy surrounding the origins of the virus (lab grown or natural evolution?).

In Part II, we will discuss the following:
At the conclusion of this series, you, the reader, will be one of the most informed people on the pandemic in any given room.

Part I review:

Basics of immunology

  • The immune system has two defensive strategies: the innate and adaptive responses. Innate immunity is described as “antigen-independent,” referring to its non-specific mechanism of action. Contrastingly, the adaptive immune system, which is “antigen-dependent,” referring to its ability to recognize specific antigens present on foreign pathogens. Exposure of antigens to the adaptive immune system creates a “memory” effect, allowing the system to mount a stronger response upon subsequent exposure to the same antigen.
  • The innate immune system relies on many cell types to mount a quick response, such as phagocytes (macrophages and neutrophils), natural killer (NK) cells, lymphocytes (T cells), and other white blood cells (eosinophils, basophils, and mast cells). Importantly, it also interacts with and activates the adaptive immune system via “antigen presentation” performed by dendritic cells and macrophages.
  • Once activated, T cells differentiate into cytotoxic T cells (CD8+ cells) or T-helper cells (CD4+ cells). Cytotoxic T cells are equipped with a T cell receptor (TCR) that recognizes a singular, specific antigen present on the surface of pathogen-infected cells. B cells are responsible for producing antibodies that target the antigens through direct interaction with the pathogen.
  • Antibody-mediated immunity is very important during the early stages of an infection when the pathogen has infected (relatively) few human cells, but a complete immune response relies on the activity of cytotoxic CD8+ T cells that can target and eliminate infected human cells without antibody targeting.

SARS-CoV-2 physiology and origins

  • SARS-CoV-2 has four main structural proteins: spike (S) glycoprotein, small envelope (E) glycoprotein, membrane (M) glycoprotein, and nucleocapsid (N) protein. The S protein is further divided into two subunits: S1 contains the receptor binding domain (RBD) that is unique for the ACE2 receptor, and S2 is important for the fusion of the viral membrane with the host cells.
  • SARS-CoV-2 enters the cell through the binding of its S protein with ACE2 receptor, a receptor that functions as a bridge between the exterior of a cell and the interior cytoplasm (where the molecular machinery needed for RNA replication is located). The ACE2 receptor is highly concentrated in the lungs, which is why COVID-19 is primarily an upper respiratory disease that hinders lung function and impairs oxygen transport.
  • The RBD of the S protein is the most variable part of the coronavirus genome, with the rest of the genome exhibiting ~96% similarity between SARS-CoV-2 and the bat coronavirus RaTG13. There are six amino acids within the RBD that are critical for binding to the ACE2 receptor.
  • Genomic analysis of the S protein’s subunits, S1 and S2, revealed the presence of a unique ("furin") cleavage site that is absent in related coronaviruses, which pops up in avian influenza viruses due to rapid replication and transmission.
  • A declassified report from the National Intelligence Committee states that the origins of the virus are most likely natural, although it is possible that the research at the Wuhan Institute of Virology resulted in a mutated SARS strain. The theory that the virus leaked from the Wuhan lab is supported by several independent academic groups. The Lawrence Livermore National Laboratory report (May 2020) provided early evidence of the lab leak hypothesis and was made available to Capitol Hill during a time when that notion was still politically taboo.

And so it began...

January 9th will forever be remembered as a day infected with infamy. With 59 reported cases of a mysterious flu-like virus reported internationally, the WHO announced a new form of coronavirus that stemmed from the Wuhan district in China. Epidemiologists issued travel precautions and recommended screening at airports. The CDC acted quickly, requiring screening for coronavirus at three of the most heavily trafficked airports: JFK International, San Francisco International, and Los Angeles International. Not fast enough. The CDC confirmed the first US coronavirus case on January 21 in a resident of Washington state who had returned form Wuhan on January 15. PCR testing confirmed the infection, and the CDC began the process of contact tracing to identify other potential infections before they spread. By January 23, 2020, the entire Wuhan district was under quarantine and Chinese scientists had confirmed coronavirus transmission in humans, with 4 deaths and over 200 cases in China. Ironically, the WHO was still hesitant to declare the looming pandemic a public health emergency.

The emergence of COVID-19, the upper respiratory disease that results from SARS-CoV-2 transmission, could not have come at a more turbulent time in the United States. Social tensions reigned high due to a controversial presidential election and racial issues. The thinly veiled social fabric was already torn to shreds. It is no surprise that the pandemic evolved into a highly politicized, bi-partisan issue.

By February 10th, the COVID-19 death toll in China surpassed that of the SARS outbreak 17 years ago (908 v. 774), and over 10,000 cases and 200 deaths were reported worldwide. On March 11th, the World Health Organization (WHO) declared COVID-19 an international pandemic. All eyes were on the Trump Administration, the Wuhan district, Big Pharma, and the CDC.

Trump acted quickly by declaring COVID-19 a national emergency, freeing up billions of dollars in federal funding to fight the spread of the disease. On March 26, the Senate signed the CARES act that provided $2T to hospitals, businesses, and local governments. The next day, the House of Representatives approved the act, which provided direct payments to Americans and expansion of unemployment insurance. In a misguided attempt to quell mounting fear, Trump endorsed the use of hydroxychloroquine, an FDA-approved antiviral for malaria, as a first-line treatment for SARS-CoV-2 infection. The University of Minnesota launched a clinical trial on post-exposure treatment for SARS-CoV-2 on March 17, 2020, which ultimately led to the FDA issuing an Emergency Use Authorization (EUA) for hydroxychloroquine on March 30th. The American Heart Association, the American College of Cardiology, and the Heart Rhythm Society issued a joint guidance that noted severe heart complications caused by the antiviral, leading to the FDA rescinding the authorization within 1 month of approval (the FDA has been under immense scrutiny as of late).

A viable treatment for COVID-19 remained elusive (and remains elusive due to emerging variants), and the nation and the world would remain in various states of lockdown for the foreseeable future. The events that transpired in the next year and a half would have a lasting impact on the public’s perception of Big Pharma, the FDA, and the WHO. They would also leave an indelible smudge on our faith in the government and trust in our fellow citizens.

Evolution of a pandemic


Pandemic news flow has dominated all media outlets and social feeds for the better part of two years, and it has been difficult to see the forest for all the trees. A framework within which to identify, categorize, and analyze policy enactment, pandemic statistics, and scientific breakthroughs is needed to better understand the evolution of the pandemic and our influence over its trajectory. MedicalGold has developed a series of timelines, separated by year, to visualize our pandemic response.

Note: "CA" is Canada
Note: "CA" is Canada

Note the extremely high death-to-case ratio in the United States during the early days of the pandemic. At this point it is common knowledge that the hospitalization and death statistics were inflated due to triaging any patient that had a mild cold into the COVID ward. Co-morbidities were completely ignored, and a 70 yr. old patient who died of a heart attack could easily count as a COVID death statistic. A solid hypothesis is that many un-related deaths due to comorbidities were reported as COVID-related, but the case numbers remained low due to lack of testing options (remember, the first saliva-based test was approved in May 2020, and RT-PCR testing was in its infancy). Taken together, these two factors end up skewing the ratio to make it appear that the US populace was being decimated in droves.

Let’s face it, COVID-19 has been a huge revenue generator for all players in the healthcare system (except for the insurance payers, of course). An analysis published in April of 2020 by The Kaiser Family Foundation found that, for less severe hospitalizations, the average Medicare payment for respiratory infections and inflammations with major comorbidities or complications was $13,297 (2017). For more severe hospitalizations, the average Medicare payment for a respiratory system diagnosis with ventilator support for greater than 96 hours was $40,218. Note: Each of these average payments were increased by 20% to account for the add-on to Medicare inpatient reimbursement for patients with COVID-19 that was included in the CARES Act [1].  But could there be something nefarious afoot? Are hospitals incentivized to “upcode” patients to COVID-19 status for monetary benefit?

Let’s do some math.


  • Hospitalizations are mostly comprised of patients 65 and older.
  • The vast majority of patients 65 and older are insured through Medicare, not a plan subsidized by an employer, nor a self-plan.
  • The Medicare reimbursement rates cited by the Kaiser analysis haven’t changed since 2017.

Analysis of the data provided by The World in Data (source below) produces the following statistics:

To-date, hospitals have been reimbursed $6.5B, a far cry from the $13-41B estimated by The Kaiser Foundation. Keep in mind that this assumes that all the hospitalizations and ICU visits were reimbursed by Medicare, and the actual figure must be lower. It is unlikely that hospitals are intentionally mis-coding patients to inflate COVID statistics.

Note: "CA" is Canada

What’s interesting about the USA’s vaccination uptake is that it doesn’t move as you’d expect from the major catalysts, namely the emergence of the delta variant in late March 2021, full approval granted to the Pfizer vaccine in August, Moderna’s submission for full approval, and Pfizer’s recent announcement of positive results in children under 12. Vaccination rate may be waning, but Big Pharma is preparing to manufacture hundreds of millions of booster shots that will be administered over the next few years.

Updated 10/4/2021

This latest Coronavirus is likely to be a seasonal occurrence, like influenza, and Big Pharma is going to make a killing by developing booster shots every year (we will get into the economics in the next article in this series). We should expect to see a gradual increase in the percentage of the vaccinated population, unless there are major breakthroughs in antiviral or anti-inflammatory therapies that obviate the need for a vaccine prophylactic. Update: 10/4/2021 - Merck just released positive Phase III data for their COVID antiviral pill, an enzyme inhibitor that blocks the replication of the virus within human cells (we will discuss this further in the next article).

Data sources

Credit: data made available by Our World in Data

Accessible here:

  • Confirmed cases and deaths: our data comes from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). We discuss how and when JHU collects and publishes this data here. The cases & deaths dataset is updated daily. Note: the number of cases or deaths reported by any institution—including JHU, the WHO, the ECDC and others—on a given day does not necessarily represent the actual number on that date. This is because of the long reporting chain that exists between a new case/death and its inclusion in statistics. This also means that negative values in cases and deaths can sometimes appear when a country corrects historical data, because it had previously overestimated the number of cases/deaths. Alternatively, large changes can sometimes (although rarely) be made to a country's entire time series if JHU decides (and has access to the necessary data) to correct values retrospectively.
  • Hospitalizations and intensive care unit (ICU) admissions: our data comes from the European Centre for Disease Prevention and Control (ECDC) for a select number of European countries; and government sources for the United Kingdom, the United States, Canada, Israel, Algeria, and Switzerland.
  • Testing for COVID-19: this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. The testing dataset is updated around twice a week.
  • Vaccinations against COVID-19: this data is collected by the Our World in Data team from official reports.
  • Other variables: this data is collected from a variety of sources (United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). More information is available in our codebook.

What’s driving the pandemic?

The million-dollar question. What we really mean is “what risk factors and characteristics of people, nations, treatments, and policies are significantly contributing to COVID-19 cases and deaths?” A global pandemic is a statistician’s dream. This is a Big Data problem that begs a Big Data solution.

MedicalGold is sitting on a gold mine of data curated by Johns Hopkins University, collected from over 200 countries, and featuring epidemiological data (cases, deaths, hospitalizations, reproduction rate), vaccination statistics (number of doses, fully vaccinated people), government policy responses (based on a 9-point stringency index), and 50 other variables of interest. The trick is to identify those variables that best predict the spread of the virus. In statistical terms, the goal is to identify those variables that capture the most variance in the data. We intend to continue to analyze the data in real-time and publish additional analysis.

Stay tuned in to this ongoing effort by subscribing to our free content and news feed.

“Follow The Science™”

6 feet of separation

Let’s be honest, no one really knows why six feet is the magic number. This may be due to an antiquated understanding of pathogen transmission in moisture (see section below), but the arbitrary nature of social distancing guidelines is beautifully illustrated by the CDC’s guidance (March 2021) aimed at school children. As if by magic, six feet miraculously morphed into three. Regardless, the reasoning was never effectively communicated to the public.

When the first mask and social distancing mandates were announced, “the science” was in its infancy and governments scrambled to do something. Decisive action does, however, accomplish two important things: 1) it makes the government look like they have a handle on the problem, and 2) it gives people the impression that they have some level of control (for the exact same reason that people are afraid of flying, though the risk of death is substantially lower than in a car). Ironically, the same people that became social distancing fanatics would eagerly give up their control once the vaccines rolled out.  A similar psycho-social phenomenon appeared when the first masking guidelines were issued by the CDC in early 2020. An army of cloth-swabbed zealots would be observed (and ridiculed) jogging down the street, driving alone in their cars, and meticulously doffing their textile-armor between sips of coffee.

The physics of a sneeze…

…one of life’s great mysteries. Until recently, scientists believed that exhaled moisture traveled as droplets through space in adherence to Newton’s laws, following a parabolic arc until they settled on the ground. This current understanding of disease transmission hasn’t been updated since the 1897, when Carl Flügge, a German bacteriologist, developed the original model of “droplet transmission.” Dr. Flügge dichotomized droplets into “large” and “small” based upon their evaporation and settling rates [2]. Small droplets evaporate faster than they settle, resulting in a cloud of droplet nuclei containing the solid residual material within. When exhaled from the moist lungs into the cool ambient air, small droplets quickly evaporate and release their nuclei as aerosols. Large droplets, which are thought to travel short distances in isolated trajectories due to gravity’s pull and their relative size, can harbor pathogens that are much smaller in size (for reference, SARS-CoV-2 is 0.1 micrometers in diameter). To date, the CDC has used rather arbitrary cutoffs (5-10 micrometer diameter) to distinguish large from small droplets. The issue with this model is that droplets are not released in isolation, and consideration must be given to the aerodynamic effects of the turbulent gas cloud that is expelled with them. There is an obvious need for an updated model that removes some of this ambiguity and uses advances in science to examine pathogen transmission in fluids.

Enter Lydia Bourouiba, a fluid dynamicist, and head of the Fluid Dynamics of Disease Transmission Laboratory at MIT. Dr. Bourouiba has been revolutionizing the prevailing disease transmission model ever since the SARS outbreak in 2003 [3].  Her work has elucidated the gas phase of exhalation, which is composed of high-momentum, turbulent movement of droplets capable of containing infections agents. Earlier studies never considered anything other than the liquid phase (i.e., droplets) of a cough or sneeze. Ultimately, the physical properties of the gas cloud (e.g., momentum) determines the dispersal pattern of different size droplets and is initially caused by the momentum of exhalation, then later influenced by the ambient airflow (e.g., from an air conditioning unit). Lydia’s research has shown that pathogen-bearing droplets are dispersed over much greater distances than if they were projected in isolation, as single large droplets, without a turbulent gas cloud providing the momentum. She found that the gaseous payload could extend pathogens 23-27 feet, depending on ambient conditions such as temperature, humidity, and airflow) [2]. Clearly, the CDC’s understanding of pathogen transmission via exhalation is outdated, and a 3-6 feet distancing mandate woefully underestimates that capabilities of a sneeze.

Dr. Bourouiba discusses her work in this interview in Knowable Magazine

To mask or not to mask?

The question is not can they work, but do they work for practical purposes. Masks have been used as a standard for disease control since the 1910 Manchurian plague, when Malayan Dr, Wu Lien-The invented the cloth mask that would be used to control pathogen spread for the remainder of the 20th century. Unfortunately, only a handful of randomized controlled trials (RCTs) have been conducted to date, and only one observational study has examined the impact of masks on secondary transmission of SARS-CoV-2 (in Beijing households). The Beijing study found that secondary transmission of the virus between the primary was reduced by 79% before the primary case developed symptoms. Importantly, wearing a mask after the primary infected family member started showing symptoms was not significantly effective [4]. A systematic review of 12 RCTs and 25 observational studies identified a mild protective effect of 19%, but that reduction in secondary illness was only evident when both household members and the infected wore the mask. The evidence from observational studies appears to be stronger. The preprint study (i.e., not yet peer-reviewed)  concluded that: [5]

“The evidence is not sufficiently strong to support widespread use of facemasks as a protective measure against COVID-19. However, there is enough evidence to support the use of facemasks for short periods of time by particularly vulnerable individuals when in transient higher risk situations. Further high quality trials are needed to assess when wearing a facemask in the community is most likely to be protective.”

The mechanism of action of multi-layer cloth masks (like N95) has been explored by several independent scientific groups. In a preprint publication entitled “Face Coverings and Respiratory Droplet Dispersion,” researchers were able to evaluate the effectiveness of surgical masks (multi-layer) and single-layer cotton masks by measuring fluorescent droplet dispersion ejected from human participants and a mask-bound manikin. The results were clear. Wearing a mask reduces the number of droplets over a 2-meter trajectory by > 1000x [6]. In the early days of the pandemic, we saw all sorts of home-made textiles reconfigured into face coverings (my favorite is a woolen knit shield). Can a cloth bandana offer the same protection as a surgical mask? The answer has been known for years, yet somehow public health officials failed to communicate this simple fact. A 2013 study published to Disaster Medicine and Public Health Preparedness determined that home-made masks were 3x less effective at blocking the transmission of bacterial and viral particles [7].

Face Coverings and Respiratory Tract Droplet Dispersion

Interestingly, scientists and mask manufacturers know relatively little about the microscopic structure of multi-layer cotton masks, like N95. Understanding that the masks have a real-world benefit is great but knowing why they work is just as important. Logically, pore size plays a major role in retaining viral particles (keep in mind that the diameter of SARS-CoV-2 is 0.1 micrometers, or 100 nanometers). Other factors, such as the surface charge density of the fibers, fibre diameter and thickness, and environmental conditions (e.g., air velocity, temperature, and humidity), also affect the filtration mechanism. The physical microstructure of masks can be examined by X-ray tomography, resulting in some beautiful and intriguing images (see below). Researchers examining the microstructures of three common masks (reusable, surgical and N95) to determine their porosity determined that the N95 mask displays the lowest porosity (65%). Basically, higher porosity allows air in and out and thus will have higher breathability [8]. The peak pore diameter for the N95 masks is 30 micrometers, two orders of magnitude greater than the virus itself. However, the viral particles are transmitted in exhaled droplets, which range from 40 micrometers to 1 millimeter.

Microstructure analysis and image-based modelling of face masks for COVID-19 virus protection

Obsession with R

A single statistical measure dominated the public consciousness in the early days of the pandemic: R (or in specific circumstances referred to as R0, “R-naught”). Epidemiologists use R, also known as the “reproduction number,” as a measure of infectivity to model disease outbreak. Conceptually, this metric is simple; R0 indicates the average number of people each diseased person can infect. This simplicity might have caused undue attention to this single variable, and might not be as useful to understand the trajectory of the pandemic as government officials might think. In Spring of 2020, British Prime Minister Boris Johnson and German Chancellor Angela Merkel made public announcements regarding R and public policy. The prevailing wisdom was that an R under 1 meant that the pandemic was slowing, and an R greater than 1 meant that the pandemic was growing exponentially. And while mathematically true, this figure alone is insufficient to forecast the evolution of the pandemic.

“Epidemiologists are quite keen on downplaying R, but the politicians seem to have embraced it with enthusiasm. We’re concerned that we’ve created a monster. R does not tell us what we need to know to manage this.”
~Mark Woolhouse, an infectious-diseases expert at the University of Edinburgh in the United Kingdom, who is a member of a modelling group that advises the British government on the pandemic [9]

It is important to understand that R is a function of the duration of infectivity after the primary patient is infected, the probability of secondary transmission to a susceptible individual, and the contact rate between individuals. Since these variables can be difficult to estimate directly, R is often calculated by epidemiologists retrospectively, but is sometimes predicted using mathematical models based on several assumptions. For reference, the WHO estimated that the R0 of SARS-CoV-2 was between 1.2-2.4 in January 2020 [10], but another study found that the average person spreads the virus to 2-3 people on average [11]. A systematic review of COVID-19 epidemiology confirmed this range in 13 out of 20 estimates [12].  Logic dictates that as the population gains herd immunity via prior infection or vaccination then the transmissibility of the disease should decrease, and most likely in exponential fashion. Scientists refer to this transmissibility coefficient as Re, or the “effective R,” when the size of the susceptible population begins to change. As you can see in the plot below, the R value plummeted in both the USA and Canada once businesses shut down and quarantines went into effect in late March 2020. The rate of infectivity appears to have settled in between 0.75 and 1.5, with an average value of 1.04 in the USA and 1.03 in Canada. Not too bad. So why is the pandemic raging on in these countries, despite strict mask mandates, travel restrictions, and school closings?

Credit: data made available by Our World in Data | Accessible here:

Hyper-fixating on R is dangerous. This myopic approach to gauging how policy influences the severity of the pandemic ignores some of R’s drawbacks. Typically, R is a lagging indicator, gleaned from testing and hospitalization data as it is reported. It is not a satisfactory real-time measure. As mentioned before, employing statistical models to overcome this limitation simply adds a different type of uncertainty to the formula. Researchers rely on contact surveys to estimate one of the key variables in the R calculation. These surveys are not instantaneous nor terribly reliable (the most accurate contact tracing data would come from cell phones. Hello Big Brother). Furthermore, R is calculated as an average across a country, and is biased by outliers in specific geographies and subsets of the population. Examples include a regional outbreak in Germany’s meat-processing plant at Gütersloh in North Rhine-Westphalia, and Britain’s unusually high R that is influenced by the number of infected individuals in nursing homes. Neither of these niches represent the general population. Ultimately, social distancing and quarantine policies must consider the total number of infected people, not just R. Government’s are primed to overreact, and keeping a country shut down when it has low case numbers but a high estimate of R could cause more damage than the virus ever could [9].

The COVID-ian cult & vaccine zealots

The COVID-19 pandemic is as an intriguing social phenomenon as an epidemiological event. In the United States, “The Science” continues to be interpreted through a bipartisan lens. Nothing could be more polarizing than the vaccines themselves. Ultra-conservatives were quick to denounce the hasty approval of the Big 3 (Pfizer, Moderna, and J&J) vaccines, but now that full approval has been granted, the Biden administration and leftist groups are back on the offensive demanding forced vaccination policies. Alternative treatments, like monoclonal antibodies and ivermectin, have been politicized as well, reduced to inferior solutions with no scientific basis (which is not true, and will be addressed in the next article in this series). Governor Ron De Santis of Florida made a heroic effort to provide widespread, free access to monoclonal antibody therapies to COVID-19 patients [13]. De Santis’ critics bemoaned his “don’t tread on me” approach to healthcare and basic human rights, but they would eat their words when the Biden administration decided that antibodies work so well that they were going to stop providing them to Florida and redistribute around the country [14]. It’s almost as if  providing people with vaccine and treatment options will allow them to seek out the best treatment for themselves. Strange, I know.

Biden's message to the public on September 9th is self-contradictory, first stating that this is a pandemic of the unvaccinated (likely true) that is being enabled by elected officials that are ordering "mobile morgues" (referring to De Santis' monoclonal antibody clinics) to treat patients...

"And to make matters worse, there are elected officials actively working to undermine the fight against COVID-19.  Instead of encouraging people to get vaccinated and mask up, they’re ordering mobile morgues for the unvaccinated dying from COVID in their communities.  This is totally unacceptable."
~ Joe Biden

... and then promising to increase the amount of available antibodies by 50% [14]...

Additionally, we’re increasing the availability of new medicines recommended by real doctors, not conspir- — conspiracy theorists.  The monoclonal antibody treatments have been shown to reduce the risk of hospitalization by up to 70 percent for unvaccinated people at risk of developing sefe- — severe disease. We’ve already distributed 1.4 million courses of these treatments to save lives and reduce the strain on hospitals.  Tonight, I’m announcing we will increase the average pace of shipment across the country of free monoclonal antibody treatments by another 50 percent.
~ Joe Biden

The booster shot debacle

The recent authorization of Pfizer-BioNTech booster shots captures the illogical and Kafkaesque decision making by the White House and associated government agencies. Biden's original promise to start offering booster shots to all Americans by September 20 was made months before any data supported the safety and efficacy of a third dose. This is not the first time that the White House waffled on "The Science." The administration undercut the CDC regarding their recommendation for mandatory vaccination of teachers to reopen schools, and have now retraced their steps [15]. It would be one thing if the science had somehow deviated in the last 7 months... but there has never been a point in time when scientists believed that teachers are magically immune from infection. Remember back in May when the administration recommended that vaccinated people do not need masks? That quickly changed. So it is no surprise that the government has fully endorsed boosters without any good evidence suggesting that they are both safe and effective. Fauci's defense of Biden's incompetence is both hilarious and alarming...

“Remember, [Biden’s] not there at every single Zoom call, at every single decision. But he set the standard, and he made it clear that he wants everyone in this administration, including the medical team, to make sure that science drives the guidelines. That science drives the decisions. That science drives the policy. He has been unequivocal.”
~ Fauci told STAT in an interview

So the President of the United States isn't tuned in to the latest developments of the biggest global disaster the WHO has ever seen? Makes sense. Forget Zoom calls, it can be difficult for Joe to get enough rest in the White House. [16]

"It is very hard to get comfortable," Biden said during a recent CNN town hall, adding he likes to be able to walk out in his bathrobe and grab breakfast for himself.
"It's a very important part of who he is, and keeps him grounded," said Ted Kaufman, a longtime friend [of Biden].

OK, enough with the dark comedy.

The FDA's Advisory Committee on Immunization Practices (ACIP) was set to convene on September 23 to discuss the eligibility requirements for the third dose of Pfizer-BioNTech. Well, this meeting was preempted by the FDAs Emergency Use Authorization (EUA) for the booster delivered a day before (9/22/2021). In a swift move, the booster was given EUA for adults 65+, individuals 18-64 yrs. that have high-risk occupations (such as healthcare workers), and individuals 18-64 yrs. that are likely to be exposed (such as nursing home residents) [17]. The Agency failed to mention how pharmacists, the medical practitioners administering the majority of vaccines, would even verify these eligibility requirements. Finally, the ACIP panel convened to provide a final recommendation to the CDC, whos director, Rachel Wallensky, would provide the final guidance to the White House.

On September 23, the ACIP recommended that a small portion of adults should be eligible for the booster, with the most support (unanimous) for adults 65+ yrs, those living in nursing homes, and people aged 50 to 64 with medical conditions that raise the risk of severe Covid infection (13 to 2 in favor). There was weaker support (9 to 6 in favor) for people aged 18 to 49 with underlying medical conditions. The only demographic that was shot down by the panel (9 to 6 not in favor) was for individuals aged 18 to 49 yrs that are at heightened risk due to their living conditions or occupation, such as health workers and the homeless or those that work in homeless shelters. Wallensky ultimately undercut the last portion of the ACIP's recommendation and offered guidance to the White House in support of vaccination for virtually all adult Americans that may be at risk for COVID infection, due to either underlying medical or high-risk living/working conditions [18]. Wallensky's guidance aligns with the EUA already granted by the FDA. Note that this recommendation is only for the Pfizer-BioNTech vaccine, and recipients of the boosters must have received two doses of the Pfizer-BioNTech at least 6 months prior to the booster. The other vaccines will need to be independently assessed.

The World Health Organization is not happy, and justifiably so.

“Providing U.S. residents a third shot is akin to “handing out extra lifejackets to people who already have life jackets … while we’re leaving other people to drown.”
~ World Health Organization representative

In the next installment of this series, we will dig into the details of the vaccine research and development programs, the clinical trial data that has been published, and some of the things that the media is (perhaps intentionally) failing to cover.

There’s much more to this story than masks, quarantines, and vaccines.

Stay tuned.


[1] Estimated Cost of Treating the Uninsured Hospitalized with COVID-19 (2020) [Link]

[2] Bourouiba L. Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19. JAMA. 2020;323(18):1837–1838. doi:10.1001/jama.2020.4756 [Link]

[3] Bourouiba L. (2021). Fluid Dynamics of Respiratory Infectious Diseases. Annual review of biomedical engineering, 23, 547–577. [Link]

[4] Wang Y, Tian H, Zhang L, et al. Reduction of secondary transmission of SARS-CoV-2 in households by face mask use, disinfection and social distancing: a cohort study in Beijing, China. BMJ Global Health 2020;5:e002794 [Link]

[5] Facemasks and similar barriers to prevent respiratory illness such as COVID-19: A rapid systematic review (preprint) [Link]

[6] Face Coverings and Respiratory Tract Droplet Dispersion (preprint) [Link]

[7] Davies, A., Thompson, K. A., Giri, K., Kafatos, G., Walker, J., & Bennett, A. (2013). Testing the efficacy of homemade masks: would they protect in an influenza pandemic?. Disaster medicine and public health preparedness, 7(4), 413–418. [Link]

[8] Du, W., Iacoviello, F., Fernandez, T. et al. Microstructure analysis and image-based modelling of face masks for COVID-19 virus protection. Commun Mater2, 69 (2021). [Link]

[9] A guide to R — the pandemic’s misunderstood metric (Nature News Feature, July 2020) [Link]

[10] Achaiah, N. C., Subbarajasetty, S. B., & Shetty, R. M. (2020). R0 and Re of COVID-19: Can We Predict When the Pandemic Outbreak will be Contained?. Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine, 24(11), 1125–1127. [Link]

[11] del Rio C, Malani PN. COVID-19—New Insights on a Rapidly Changing Epidemic. JAMA. 2020;323(14):1339–1340. doi:10.1001/jama.2020.3072 [Link]

[12] Park, M., Cook, A. R., Lim, J. T., Sun, Y., & Dickens, B. L. (2020). A Systematic Review of COVID-19 Epidemiology Based on Current Evidence. Journal of clinical medicine, 9(4), 967. [Link]

[13] Governor DeSantis Calls for Biden Administration to Restore Monoclonal Antibody Supply to Florida [Link]

[14] Remarks by President Biden on Fighting the COVID-⁠19 Pandemic [Link]

[15] Biden pledged to ‘follow the science.’ But experts say he’s sometimes fallen short (STAT News, paywall, Sept 1, 2021) [Link]

[16] Dela-Where He'd Rather Be: Come The Weekend, Biden Leaves D.C. (NPR, August 7, 2021) [Link]

[17] FDA Authorizes Booster Dose of Pfizer-BioNTech COVID-19 Vaccine for Certain Populations [Link]

[18] Pfizer-BioNTech COVID-19 Vaccine Booster Shot (CDC website, updated September 24, 2021) [Link]


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