Infection Control, Emergency Management, Safety, and General Thoughts

I saw pertussis (whooping cough) data this week that reflects both antivaccine sentiment as well as the possibility of COVID damaged immune systems leading to spread. All of the data used in these graphs is from the UK.

I wanted to find data on diseases that weren’t vaccine preventable to look more closely at the immune damage component. I hit the jackpot with some data for organisms I’m very familiar within my particular field of healthcare infection prevention.

I was concerned though that many people may not be used to a data visualization like this, so I decided to take the raw data and place it into a form people would be more familiar with, but more importantly, adding pre-pandemic and mid-pandemic trend lines to compare to each other. I omitted the data from 2020 since there were so many other variables coming into play, particularly social distancing and much more focus on hand hygiene, which both would skew data for that year more than others. I also attempted to balance the dumber of quarters on each side of 2020 and used the most current data available.

This data is all bloodstream infections (except for C. difficile) with these organisms, ie, invasive disease, not just a topical infection on the skin.

Staphylococcus aureus

This organism is commonly found on the skin and is responsible for about 25% of serious surgical site infections.

MSSA is methicillin sensitive S. Aureus and is distinguished from an antibiotic-resistant strain known as methicillin resistant S. Aureus.

What is particularly interesting about these is that while the rate of MSSA in the population didn’t increase much, MRSA had been trending downward until COVID. That is a puzzle I’m very interested in solving.

Klebsiella spp.

Klebsiella infections also did not appear to have an increasing rate of infection due to COVID. However, an upward trend isn’t good regardless given how this organism is commonly associated with respiratory tract, urinary tract, and wound infections.

Pseudomonas aeruginosa

Pseudomonas aeruginosa is an environmental pathogen found in soil and water. It can cause a number of different types of infections in humans. One concern is that the rate of infections with these organisms was trending downward but is now trending upward. Another emerging concern is a report by Howard et al. about a strain of this organism that has acquired a gene to encode an enzyme that will dissolve a type of plastic that is commonly used in healthcare settings. The organism can obtain ALL of its carbon needs from this plastic. It seems like a story straight from The Andromeda Strain by Michael Crighton.

Escherichia coli

E. coli is a common organism in the gastrointestinal tract. It is also associated with a number of different infections.

Clostridioides difficile (C. diff)

C. diff is an organism that resides in the gastrointestinal tract of about 2-5% of healthy adults. It forms spores, which allow it to survive in harsh environments and make it important to control in healthcare settings. We use the abbreviation CDI for C. diff infection in healthcare. This is another organism where infections had been decreasing before COVID, but now are increasing.

Obviously, none of this proves that COVID immune damage is the cause, but, we do know from multiple studies that COVID causes damage to the immune system, so it is a reasonable assumption that immune damage is playing a role. I have a number of studies quoted and linked here.

California will be used to illustrate unless otherwise stated.

Early on, it became very apparent that COVID surges were linked to variants. This is pretty obvious when looking at proportions of variants in relation to hospitalizations.

Many sources of data have faded in and out, particularly good case data. That has necessitated other metrics to understand COVID in a particular geography. Positivity, wastewater, and percentage of emergency department visits have become other good early indicators and have strong concurrence, such as seen across the entire US in this view.

The coefficient of determination, or R-squared values, also support their tight relationships.

• 0.89 Wastewater and ED visits
• 0.86 Wastewater and Positvity
• 0.70 ED visits and positivity

This is a good explanation of r-squared if you want to dive a little deeper into statistics.

Here are the percentages of different variants with the plots of wastewater, positivity, and percentage ED visits on top of them. I also have the ED visits multiplied by 10 as a means to better see the curves. I’ll use the numbers and letters at the top to explain.

The vertical black lines represent the start of different surges, primarily using the wastewater data, but they correlate with the others as well.

• Line 1 – This is the start of what is commonly known as the delta wave. Here are the three variants isolated.

The three delta variants are closely related as shown below. 21A is the parent to 21I and 21J. That is part of the reason that they comprised a single surge. One can also conclude that 21J had a much higher r-naught, or reproduction value, and quickly dominated the other two.

• Line 2 marks the start of 21K, the original omicron variant. Notice how quickly that became dominant and caused a rapid surge like 21J
• Line 3 and 4 are where things get interesting because of some competition between 21L and one of its descendants, 22C, both of which are quickly overtaken by another subvariant of 21L known as 22B, so once again, a closely related family for that surge.

• Lines 5 and 6 follow the traditional single variant surge pattern, with 22E and 23A respectively, which have very different lineages.

• Lines 7 and 8 get messy again with 23B, 23D, and 23 F competing with each other, 23F being a subvariant of 23D, but all of the same lineage. The lower surge in wastewater values suggests short term protection among these different variants by infection with one of the others since they are similar. It’s also worth noting that none of these hit the 50% of sample threshold, which I will come back to later.

• Line 9 starts another big surge based on wastewater due to 24A.
• Line A begins the current surge which started with 24E in the late summer. You can see another surge superimposed on it at Line B, due to 24F. These are very distinct lineages, hence there is very little protection from one when infected by the other.

Hopefully this helps clarify what drives surges. It’s not seasons or elections. It strictly has to do with variant lineages and variant reproduction rates. It also supports my argument that aside from very different lineages, surges are related to about a 50% dominance of a variant.

This data also suggests why some surges might be smaller or larger simply based on how closely the predominant variants are related. If they are a close lineage, one will provide some immunity…FOR A SHORT TIME, but that still doesn’t guarantee protection. It’s insane to get infected with the notion that will provide “natural” immunity. Getting vaccinated with the current booster offers the best protection. I just wish these were updated every 3-4 months based on dominant strains and made available at that cadence as well.

Note: Much of the data and data visualization comes from https://covariants.org/.

I made a statement yesterday on Twitter in response to the plane crash yesterday in South Korea.

While it is possible that a bird strike was the root cause and destroyed avionics, there are a few remaining questions. “‘At this point there are a lot more questions than we have answers. Why was the plane going so fast? Why were the flaps not open? Why was the landing gear not down?’ said Gregory Alegi, an aviation expert and former teacher at Italy’s air force academy.” Normally, a flight would circle and jettison fuel as to reduce the risk of explosion and fire, which also allows the airport the 20 minutes needed to deploy fire retardant foam and nets. This may have been skipped though if the strike led to fire or toxic fumes in the cabin

“Joo Jong-wan, a director at the transport ministry, said during a briefing, ‘Typically, engine failure and landing gear failure are not directly linked. Even if the landing gear doesn’t deploy automatically, there are manual overrides. The exact cause will need to be determined through an analysis of the flight data recorder.'”

The aircraft made one go around after the initial attempt at landing. On the second attempt, it contacted the runway at about the halfway point, which left no space for the aircraft to skid to a stop before the end of the runway. That raises another question as to why it didn’t land at the beginning of the runway.

This all could be bad luck that couldn’t be avoided. However, there is plenty of evidence of that COVID may interfere with transportation safety.

Aviation incidents are relatively rare, although it does seem like there have been many more the past few years. However, motor vehicle accidents (MVAs) provide us with a much larger data set that provides clues and make a good surrogate measure.

Aside from that, we already have evidence from aviation. Military Pilots Reported 1,700% More Medical Incidents During the Pandemic. The Pentagon Says They Just Had COVID.

Other research of concern has to do with brainwave patterns on EEGs. These changes were associated with concentration problems, fatigue, and reduced mental resilience, which could affect their ability to perform high-stakes tasks.

MVAs

First, we already know that other infections can increase MVA risks. “The result…suggests that subjects with latent toxoplasmosis had a 2.65 (C.I.95= 1.76–4.01) times higher risk of a traffic accident than the toxoplasmosis-negative subjects.”

This is MVA fatality rates. As you can see in every metric, they have been overall falling for some time. (Data source). That trend has a lot to do with both vehicle and roadway safety devices. Those have made the highways safer, so much of this is related to driver behavior.

The rate of decline as a population rate slowed in the 1990s, paralleling widespread adoption of cell phones and the subsequent distracted driving. A clear upward jump occurred in 2020.

It’s hard to distinguish what happened though related to the rates among the number of motor vehicles and miles driven due to the very high rates in the past. Zooming into that data shows the same increases in 2020, and the lowest points for both are higher than the peaks for the prior 10 years.

Earlier this year, I had used this data to look at rates in another way.

The black line is road miles, the light blue is air miles, and the red is MVA deaths per 100,000 population per 100,000 miles. The orange line is simply to make it easy to look at the year 2020 on all three. The drop in air and road miles is expected, but the big jump in mortality is telling.

Some may try to argue that the lockdowns resulted in more speeding on empty roads, but the data does not support this as a cause of MVA deaths since the easing of restrictions.

Now the highways are congested again, but the mortality hasn’t dropped. It’s another argument that COVID is driving up MVAs. It’s not just the mortality rate going up in 2020, but it should have stayed steady or more likely have gone down with less vehicles on the road.

There is also science to support the impacts of COVID on driver safety and behavior. de Paula et al have a study that supports this.

“We observed significant cognitive impairment only in the ROCF, a drawing task test used to assess visuospatial abilities, executive functions and memory. The deficits observed in the ROCF could not be explained by socio-demographic factors, ophthalmologic deficits or psychiatric symptoms, suggesting cognitive deficit secondary to SARS-CoV-2 infection. Other factors which may influence performance, such as motor coordination, spatial neglect, visual attention, semantic knowledge, intelligence and executive functions were not likely to explain the observed difficulties…

…Visuoconstructive deficits are usually defined as an atypical difficulty in using visual and spatial information to GUIDE COMPLEX BEHAVIORS like drawing, assembling objects or organizing multiple pieces of a more sophisticated stimuli…

…the PT must organize visual and spatial information in a planned manner…a processes that demand several more specific cognitive abilities related to PERCEIVING, PROCESSING, STORING, AND RECALLING VISUOSPATIAL INFORMATION, both regarding shape and position.”

“According to several traffic experts I spoke with, the explanation for the 2020 fatality spike is relatively straightforward: With fewer cars on the road during quarantine, traffic congestion was all but eliminated, which emboldened people to drive at lethal speeds…But why has the surge persisted and worsened this year, even as traffic has been picking back up and nearing pre-Covid-19 levels?”

It’s also a problem in other countries as well. However, look how much better the data looks AFTER the US is extracted from it. That’s not surprising given how poorly the US handled the pandemic.

Air travel is significantly safer than road travel, which makes it much harder to tease out data. This should make a pretty good argument that some of what we have been seeing with aircraft incidents stemming from pilot, mechanic, or air traffic controller error could easily be due to the impact of COVID on the brain. I have a number of studies on the neurological impacts of COVID here.

Addendum

Someone sent me a link to a brief study that says it all.

“Findings indicate an association between acute COVID-19 rates and increased car crashes with an OR of 1.5 (1.23-1.26 95%CI)…The OR of car crashes associated with COVID-19 was comparable to driving under the influence of alcohol at legal limits or driving with a seizure disorder…The study suggests that acute COVID-19, regardless of Long COVID status, is linked to an increased risk of car crashes presumably due to neurologic changes caused by SARS-CoV-2.”

I also have found some interesting data on road rage as well as hit and run.

Other stories:

https://www.1news.co.nz/2025/01/30/covid-brain-fog-likely-factor-in-trains-near-miss/

The data has become quite clear that the safety of our food supply has been endangered because of COVID. This is the number of FDA food recalls each month.

There was an average of 3.7 recalls per month prior to August 2021, which is when the problem became an obvious permanent feature of our food supply system. This could easily be due to the brain fog, bad decisions, and risk-taking behavior driven by COVID infections. Since that time, the numbers have increased to 24.6 per month.

This problem is likely to worsen with the new administration. “We can expect ‘deregulation, lax enforcement, reduced oversight and de-emphasization or even denial of certain frameworks.'”

That will be further compounded by the push to deport undocumented immigrants. 42% of farm workers in the US are undocumented, and that estimate is as high as 75% in California. The state provides over 30% of the country’s vegetables and over 75% of the fruits and nuts. These percentages are even higher during the winter.

What happens when the agricultural labor force is reduced? Shortcuts get taken and remaining workers become overburdened in an already difficult job, potentially coming to work when ill to maintain their employment. This can increase the risk to the food supply directly if a worker has an infection spread via the fecal-oral route of transmission, such as norovirus or cryptosporidium.

It seems a pretty safe bet that we can expect higher risk food at higher prices.

There is plenty to be said about the picks of the 47 administration, but I’ll stick to just the ones that are in my lane.

Robert F. Kennedy Jr. for Secretary of Health and Human Services

Anti-Vaccine Rhetoric

Kennedy has promoted the scientifically discredited belief that childhood vaccines cause autism.

• Debunked Study: The initial study that suggested a link between vaccines and autism was published in 1998. This study was later retracted due to serious flaws and ethical violations. The author, Andrew Wakefield, lost his medical license.
• Large-Scale Studies: Numerous large-scale studies have found no link between vaccines and autism. For example, a study published in JAMA in 2015 analyzed the health records of over 95,000 children and found no increased risk of autism associated with the MMR vaccine.
• CDC Findings: The Centers for Disease Control and Prevention (CDC) has conducted multiple studies that found no association between vaccines and autism. These studies also found no link between thimerosal, a mercury-based preservative used in some vaccines, and autism.
• Meta-Analysis: A meta-analysis of ten studies involving more than 1.2 million children reaffirmed that vaccines do not cause autism. In fact, immunization was associated with a decreased risk of developing autism.

The overwhelming consensus in the scientific community is that vaccines are safe and do not cause autism.

He questioned the safety of COVID-19 vaccines and made misleading claims about vaccine testing.

Controversial Statements: He has invoked Hitler and Nazi Germany when speaking out against vaccine mandates and using a metaphor that vaccinating children is like sex abuse in the Catholic church. Not only is that minimizing the impact of the harm from sexual abuse, but also minimizes the horrors of the Holocaust.

Misinformation: Kennedy has spread various conspiracy theories, including false claims about the origins of HIV and the safety of vaccines.

Personal Scandals: He has admitted to bizarre incidents, such as dumping a dead bear cub in Central Park, cutting the head off of a whale and taking it on the roof of his car, and has been accused of engaging in an online relationship with a political reporter despite being married. I visited the carcass of a dead whale two weeks ago and had ZERO desire to cut off its head, much less to take it somewhere on the roof of my car.

It’s pretty clear that all of this is a revenue and political scheme for him. Without those motives, most people would think he needs some professional help. He’s definitely not worthy of this position. Trump talked today about wanting RFK Jr. to investigate autism further, in spite of how much it has been studied. Even when given the information that the increase has to do with better detection, he still deflected, and even went as far as saying maybe chlorine in the water is causing it. It wasn’t that long ago that Trump was talking about injecting bleach for COVID. I can’t believe he is going to be in office again.

Dr. Jay Bhattacharya for the National Institutes of Health (NIH)

Bhattacharya is a professor of health policy at Stanford University and a proponent of natural immunity through infection.

Great Barrington Declaration: Bhattacharya co-authored the Great Barrington Declaration (GBD), which opposed lockdowns and advocated for “focused protection” of vulnerable populations. This stance was criticized by many public health experts who argued that it underestimated the risks of COVID-19 and could lead to higher mortality rates. There are many problems with the GBD.

• Unrealistic Assumptions: The declaration assumes that “focused protection” of vulnerable populations is feasible. In reality, it is extremely difficult to isolate vulnerable individuals completely from the rest of the population.
• Herd Immunity Misconception: It promotes the idea of achieving herd immunity through natural infection, which is risky and could lead to a high number of deaths and long-term health issues. The idea of getting a vascular disease known to cause damage to every organ system to provide immunity to that disease is insanity, especially when it would require repeat infections.
• Lack of Long-Term Immunity: The declaration does not account for the fact that immunity from natural infection may not be long-lasting, especially with the emergence of new variants. We knew this would not work very early in the pandemic due to the events that unfolded in Manaus, Brazil.
• Ethical Concerns: Many experts argue that allowing the virus to spread unchecked among the young and healthy is unethical and could overwhelm healthcare systems. Ethicists in the future will be reviewing this era as a case study around the notion of harming children to protect society.
  • “The true measure of any society can be found in how it treats its most vulnerable members.” – Mahatma Gandhi
• Public Health Impact: The declaration undermines public health measures such as mask-wearing, social distancing, and vaccination, which are proven to reduce the spread of the virus. Problems with the GBD are thoroughly covered by Dr. Jonathan Howard in an episode of his excellent podcast titled “The Great Barrington Declaration’s Doomed Herd Immunity Plan.”

Criticism of Lockdowns and Mask Mandates: Bhattacharya has been vocal against lockdowns and mask mandates, which put him at odds with many public health officials. His testimony in a Tennessee school mask mandate case was described as “troubling and problematic” by the judge. Imagine how bad things would have been during the delta and original omicron waves if these interventions would not have been in place.

Social Media Censorship: His views on COVID-19 policies led to his Twitter account being placed on a “Trends Blacklist” to prevent his tweets from appearing in trending topics.

Lack of Leadership Experience: Critics have pointed out that Bhattacharya lacks leadership experience in government or large organizations, which raises concerns about his ability to lead the National Institutes of Health (NIH).

He also supports letting 25% of the population die of disease, such as during the plague of Athens.

Dr. David Weldon for the Centers for Disease Control and Prevention (CDC)

Weldon is a former U.S. Representative and has a history of opposing vaccines, including claiming that thimerosal causes autism, which has been debunked long ago. He was in Congress from 1995-2009, so there’s a pretty good chance that he didn’t stay very current on medicine during that time, although he returned to private practice.

He is an internal medicine physician whose “interests include the management of hypertension, elevated cholesterol, diabetes, arthritis, cancer screening, preventive care and general illnesses of the elderly.” He lacks any specific skills in public health, infectious diseases, or epidemiology, which are core to leading the CDC. He’s likely to follow the antivaccine agenda of RFK Jr. closely.

Dr. Mehmet Oz (Dr. Oz) for the Centers for Medicare and Medicaid Services (CMS)

Mehmet Oz was likely a good cardiothoracic surgeon, but his troubles started when he was to kick off the 83rd annual American Association for Thoracic Surgery (AATS) conference. His presentation was based on a flawed study design and he was banned from speaking at the conference or publishing in their journal for two years.

He promotes and sells supplements though TV and other media channels, often without disclosing his financial ties. Typically, the supplement market is filled with grifters selling the modern version of snake oil and is unregulated. Even his colleagues think he is a quack, notable among them, Dr. Scott Atlas, who was a special advisor under Trump related to COVID, and a quack in his own regard.

Dr. Marty Makary for the Food and Drug Administration (FDA) Commissioner

Makary is a COVID misinformation spreader. Some examples include the effectiveness of masks, the risk of myocarditis from vaccines, and the benefits of natural immunity. He argued that the US would reach herd immunity by April 2021, hence opposing vaccine mandates, lockdowns, and universal masking. He seems to be part of the club that wants children diseased or dead.

There is plenty more to be found about Makary at Science Based Medicine. He is in no way suited to lead a government health agency.

We are in serious trouble with these five.

News this Week

This week marked a very concerning development in H5N1. A teenager in British Colombia is the first known case of H5N1 in Canada. It’s an odd coincidence that the province is adjacent to the first US state to have had a confirmed COVID case in 2020.

There are two things about this that are the most alarming. First, the teen didn’t have any underlying medical conditions. “The teen first went to the emergency department on Nov. 2 and was tested and sent home, but returned to hospital days later when symptoms worsened” and is now in critical condition. We don’t have any details other than presumptive pneumonia, but to me that suggests that they developed acute respiratory distress syndrome (ARDS) induced by a cytokine storm.

ARDS is a serious lung condition that occurs when fluid builds up in the tiny air sacs (alveoli) in the lungs, leading to critically low oxygen levels in the blood. This condition can develop rapidly and is often associated with severe illnesses or injuries, such as sepsis, pneumonia, COVID-19, or trauma.

This is what was happening with the Spanish Flu in 1918. “British military doctors conducting autopsies on soldiers killed by this second wave of the Spanish flu described the heavy damage to the lungs as akin to the effects of chemical warfare.”

There hasn’t been an update on the teen recently, which I suspect may mean no improvement.

The second alarming thing is the results of the sequencing of the virus from the teen. One thing about H5N1 so far has been that the virus has not been easily spread person to person. However, the virus from the teen had two key changes in the hemagglutinin gene. Hemagglutinin is a protein on the surface of certain viruses, including influenza, that binds to the sialic acid receptors on cells that it will infect. Think of it as the key that unlocks the door to gain entry into the cell. Those two substitutions are known to enhance binding to mammalian receptors, ie, it makes it much more easy to infect a person.

Why this Is Important

I tweeted this almost two years ago.

We are getting very close to human-to-human transmission. That risk will increase significantly as seasonal influenza comes into play. Influenza is a very sloppy replicator and will mix its genes as well as mop up genes from the environment.

People simply do not comprehend the scale of what could happen with H5N1.

Even if we took a more conservative mortality rate of 25%, that still means 600 million deaths worldwide. For another perspective on that number, it would be like everyone in the United States (except those in Massachusetts) dying…TWICE.

Those number also are assuming that everyone infected would get good healthcare. We don’t have that capacity, so the numbers would likely be much higher.

In addition, it also doesn’t reflect the mortality related to other causes as supply chains and services are disrupted.

There is another wild card today that didn’t exist in 1918 – immunocompromised people. If cytokine storms are the result of a healthy, overactive immune system, what happens at the other end of that spectrum among those with untreated HIV or are on immunosuppressants? Does that mean that they could amplify the virus and become superspreaders? I tweeted about this as well.

The COVID pandemic should have alerted us to how fragile supply chains are, but we continue to live in denial about that. Even domestic production is no panacea in the world of climate change. This was obvious due to the shortage of IV fluids as a result of the remainder of Hurricane Helene passing over North Carolina.

We live in a world of very complex systems. The more complex a system is, the more opportunities it has for failure. This problem was addressed very well in an article by Debora Mackenzie in the New Scientist in 2008. This is the one to read if you really want to have a grasp of this threat, but it is behind a paywall. I found the text of it here as well.

If you wonder how I sleep at night, lately, not very well.

Note: CDC had changed the structure of a data file this week, which made the percentage of ED visits break in my state files. I looked at trying to fix them all, but then realized that there will likely need to be a massive data overhaul in about a week since hospitals are required to report data again. This will require a complete rebuild of the file for each state, so I decided to just wait and see what kind of data is available next week.

Epidemic curves are simply a means to represent cases or deaths over time. For example, are the deaths from the Spanish Flu from different cities. Note at the peak in NYC, the mortality rate was running about 6%.

It’s also worth pointing out there there was a small wave in late June/July which can be more easily seen here.

That’s almost reminiscent of how smaller waves preceded both the delta and omicron waves from COVID, which also disproves the claim that viruses get milder over time. It’s also worth pointing out that once rapid tests came out, that cases really don’t paint an accurate picture of the burden of COVID in the US anymore, which is why I plot wastewater, positivity, and ED visits on the site.

Another way to analyze the impact of a disease is to view deaths by age group. Normally, influenza has a U-shaped curve, with most of the deaths occurring in the very young and very elderly, as represented by the dotted line on the graph below. During the Spanish Flu pandemic, there was a w-shaped curve (solid line), with a disproportionate amount of death in the young and healthy. In this case, the likely cause was a cytokine storm driven by the virus. Those with developed, healthy immune systems were at higher risk of this outcome as the immune system over-responded to the infection. In fact, the damage was so sever that the lung tissue from those victims looks like it had been exposed to chemical weapons.

A Brief Aside about COVID Mortality

Here’s a graph of COVID acute mortality in the US. COVID deaths are undercounted for a number of reasons, contrary to minimizers claims. Yes, a few get miscategorized, but that is the exception rather than the rule.

The red line on the right is what I want to emphasize and is my expectations for the future. COVID causes MANY chronic diseases as well as immune system disruption. The line represents the climb in chronic disease deaths from these sequelae. Acute COVID deaths will likely continue their normal wave patterns (unless we get a much better vaccine) built on top of these deaths. This of it as the x-axis curving up due to chronic disease deaths. Of course, these will likely be undercounted as COVID deaths as well. This is a VERY different pattern than what we see with seasonal influenza. It can cause other problems, but that generally happens within a few months of infection, such as a rise in acute myocardial infarction deaths, which are related to the inflammatory process of influenza. COVID is different in that it causes small clots in blood vessels, leading to focal tissue damage, death, and scar tissue from oxygen starvation, which will take a number of years to manifest.

A H5N1 Curve

People will notice a very obvious difference with a H5N1 pandemic compared to COVID if it starts and maintains the mortality (25-50%) we have seen in the past. In addition, it is spread more readily than COVID because it is also spread by contact and fomites, which suggests it will be much more transmissible.

That would result in a much higher and narrower wave of death. To illustrate that in comparison to COVID, something like this would not be surprising. That will cripple healthcare instantly and will make the supply chain problems we had since the start of the pandemic look like child’s play.

A recently published study on new onset diabetes in children within 6 months of COVID infection left me a bit stunned. At the six-month mark, the authors found children who had been infected had a 58% increased risk. It seemed worth explaining why this is so alarming.

There are 72.5 million children in the US. The baseline incidence of pediatric diabetes is 13.8 per 100,000 per year, or 72,500,000 x (13.8/100,000) = 10,005 new cases/year.

COVID seroprevalence studies suggest that 96.3% of children have been infected with COVID at least once, which equals 72,500,000 x 0.963 = 69,817,500 are at increased risk.

How do we calculate excess diabetes as a result of COVID in children? First, we need to calculate the rate due to COVID, which is only going to occur in the children infected with COVID. That rate is 0.58 x 13.8 per 100,000, or 8.004 per 100,000. That provides us with 69,817,500 x (8.004/100,000), or 5,588 new cases of diabetes among children per year, but that is a gross underestimate for many reasons.

First, the original study was only looking at risk within a few months of a COVID infection. That means that this risk figure is more akin to a point estimate than looking at lifetime risk. This is in part due to COVID being a vascular disease that causes microthrombi and focal tissue necrosis. I still suspect that most of the chronic disease burden from COVID infections will take a decade to become manifest.

Second, we also know that repeated infection increases the diabetes risk in adults by 70%, and we can use that number to estimate what happens in kids.

Let’s assume that half of the pediatric population in the US has been infected twice, which would be 34,908,750 facing this increased risk. The rate from repeat COVID infection would add 8.004 x 0.7 x 34,908,750, or an additional 8.004 x 0.7 x 34,908,750 / 100,000, or another 1,956 new cases of diabetes per year among those who were infected twice. The annual burden of diabetes from RECENT COVID infection then becomes 7,544 cases/year. It’s reasonable to assume that each subsequent infection increases that risk even further.

Here’s the real kicker. Type II diabetes really isn’t diagnosed until after the age of 40 in most people.

This further supports my argument than most of the disease burden of COVID is really many years off in the future. We have become so focused on the acute phase of the disease and are ignoring these other serious sequelae.

Similar calculations can be made with other diseases, but again, it would only be a small fraction of what is to come. This is but one example of why I have such a mix of emotions about COVID, ranging from anger, futility, and to depression. All of the numbers I just calculated are just the tip of the iceberg of what we are doing to future generations. We do not have the capacity to handle this scale of disease. We are handing future generations a dystopia of our own making between this, H5N1, and climate change. Those who have the power to make decisions to protect the public and fail to do so will not be remembered kindly by history.

A few people asked if I could share the letter I wrote to help someone get approved for disability from the Social Security Administration. I wrote to them and asked if it would be ok for me to share. Since it doesn’t contain any personally identifiable information, they approved.

Since I’m not a clinician, which likely would be important for dealing with the SSA, I wrote my thoughts on their medical history and tied it to their symptoms. It was simply a means to provide their primary care provider with some ammunition to help with their claim. Sadly, I would be surprised if more than about 5% of physicians understood the scale of COVID sequelae. The letter is below the line.

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I finally had a chance to review your records and pull together some of the research I have in my files. It sounds like it’s been a really rough time for you. I wish I could simply snap my fingers and make it go away.

With two known COVID infections, we know that your risks of multiple adverse outcomes increases as described by Bowe et al (2022). If you had asymptomatic infection(s) that went undiagnosed, these risks increase as well.

The hazard ratio (HR) in this graph shows the risk of those who have been reinfected compared to those who have not been infected. A 95% CI (the range in parentheses) is what is known as the confidence interval, which can be thought of as the range where 95% of the variation is due to the condition itself and not just due to statistical anomalies.

I’ll focus on a few of your complaints. Your risk of fatigue is 2.33 (2.14-2.54) times higher, mental health issues 2.14 (2.04-2.24) times higher, and neurological problems 1.60 (1.51-1.69) times higher compared to those infected just once.

It’s also clear that the risk of just one problem as a result of a COVID infection is about twice as high for those with two infections compared to those who have not been infected. You can see how each reinfection increases the risk compared to never being infected.

One of the mechanisms behind the neurological damage caused by COVID has been described. It has to do with the endothelial damage in capillaries during an infection. These capillaries cease to function and become what are known as string vessels, which are just the remnants of the capillaries that are no longer bringing blood to the local tissue, depriving brain cells of oxygen. The difference in the numbers of string vessels between controls and infected study animals is quite apparent with microscopy. The yellow arrows point to the string vessels.

This can easily explain some of the problems you are having. With the loss of capillaries, brain tissue can be deprived of oxygen and some cell death may occur.

One editorial in the NEJM specifically describes some of what you have been going through. “The cardinal features of long Covid include fatigue, dysautonomia (or postural orthostatic tachycardia syndrome), postexertional malaise, and cognitive difficulties that are colloquially referred to as ‘brain fog.'” That makes a pretty clear case for a disability claim.

The authors continue, stating “A recent analysis of the U.S. Current Population Survey showed that after the start of the Covid-19 pandemic, an additional one million U.S. residents of working age reported having “‘serious difficulty’ remembering, concentrating, or making decisions” than at any time in the preceding 15 years.” That would make it extremely hard for someone who has to memorize lines for their work.

In a very large (n=112,964) study on cognition and memory, the authors point out how different variants could have different impacts on cognition. Given that you were infected at least twice and based on the earlier study I provided, this would explain why a couple of different factors may have made memory and cognition harder for you.

The authors concluded “In this observational study, we found objectively measurable cognitive deficits that may persist for a year or more after Covid-19. We also found that participants with resolved persistent symptoms had small deficits in cognitive scores, as compared with the no–Covid-19 group, that were similar to those in participants with shorter-duration illness. Early periods of the pandemic, longer illness duration, and hospitalization had the strongest associations with global cognitive deficits. The implications of longer-term persistence of cognitive deficits and their clinical relevance remain unclear and warrant ongoing surveillance.”

I have some quotes from another study published in 2024 related to attention and memory difficulties on my website that I have copied here.

“Our findings revealed significant attention deficits in post-COVID patients across both neuropsychological measurements and experimental cognitive tasks, evidencing reduced performance in tasks involving interference resolution and selective and sustained attention.”

“Furthermore, our patient group exhibited significantly higher levels of state and trait anxiety, as well as depression scores, than the control group. Anxiety and depression are among the most common COVID-19 sequelae, reported both in hospitalized and non-hospitalized patients.”

This suggests that both cognitive function and emotions are adversely affected by COVID. Again, I would argue that multiple infections likely increases the chances of having these problems and may increase their severity.

We can go back even earlier into the pandemic to see that we knew these problems were on the horizon. In 2002, Xu et al published about the neurological consequences. These graphs are from that study.

I think this supports the letters that were written by the professionals supporting your case.

My particular area of expertise is in healthcare infection prevention. Given two known prior infections, it really behooves you to avoid getting a third. The insistence of the SSA that you be seen again really goes against your best health interest. You have provided them with plenty of clinical support for your claim and as I have shown, there is plenty of research support for it as well.

If they are not taking simple precautions of increased ventilation, air filtration, and respirator use in their offices, this puts you at further unnecessary risk.

Contents

• COVID
  • Psychological Defense Mechanisms
  • Studies
    • Self-reported body function and daily life activities 18 months after Covid-19: A nationwide cohort study
    • Changes in memory and cognition during the SARS-CoV-2 human challenge study

COVID

Psychological Defense Mechanisms

I have been thinking about the psychology of the COVID response in the context of Elisabeth Kübler-Ross and her stages of grief, but it didn’t seem to fit well. I came across a Tweet thread that provided some good examples of what is going on with people pushing back against being cautious. I’m copying the text of the entire thread here, particularly for those who don’t use Twitter with the permission of the author, Mike Hoerger, PhD MSCR MBA (@michael_hoerger).

As a clinical health psychologist, I notice that many people are using psychological defense mechanisms to downplay the risk of COVID. These are my Top 7 examples:

#1 – Denial – Pretending a problem does not exist to provide artificial relief from anxiety.

• “During COVID” or “During the pandemic” (past tense)
• “The pandemic is over”
• “Covid is mild”
• “It’s gotten milder”
• “Covid is now like a cold or the flu”
• “Masks don’t work anyway”
• “Covid is NOT airborne”
• “Pandemic of the unvaccinated”
• “Schools are safe”
• “Children don’t transmit COVID”
• “Covid is mild in young people”
• “Summer flu”
• “I’m sick but it’s not Covid”
• Taking a rapid test only once
• Using self-reported case estimates (25x underestimate) rather than wastewater-derived case estimation
• Using hospitalization capacity estimates to enact public health precautions (lagging indicator)
• Citing mortality estimates rather than excess mortality estimates.
• Citing excess mortality without adjusting for survivorship bias.

#2 – Projection – When someone takes what they are feeling and attempts to put it on someone else to artificially reduce their own anxiety.

• “Stop living in fear.” (the attacker is living in fear)
• “You can take your mask off.” (they are insecure about being unmasked themselves)
• “When are you going to stop masking?”
• “You can’t live in fear forever.”

#3 – Displacement – When someone takes their pandemic anxiety and redirects their discomfort toward someone or something else.

• Angry, seemingly inexplicable outbursts by co-workers, strangers, or family
• White affluent people caring less about the pandemic after learning that it disproportionately affects lower-socioeconomic status people of color
• Scapegoating based on vaccination status, masking behavior, etc.
• “Pandemic of the unvaccinated”
• Vax and relax
• “How many of them were vaccinated?” (troll comment on Covid deaths or long Covid)
• Redirecting anxiety about mitigating a highly-contagious airborne virus by encouraging people to do simple ineffective mitigation like handwashing
• “You do you” (complainers are the problem, not Covid)
• Telling people to get vaccinated or take other precautions against the flu or RSV but not mentioning Covid
• Parents artificially reducing their own anxiety by placing children in poorly mitigated environments
• Clinicians artificially reducing their own anxiety by placing patients in poorly mitigated environments
• Housework to distract from stress
• Peer pressure not to mask

#4 – Compartmentalization – Holding two conflicting ideas or behaviors, such as caution and incaution, rather than dealing with the anxiety evoked by considering the incautious behaviors more deeply (hypocrisy)

• Hospitals and clinicians claim to value health/safety but then don’t require universal precautions
• Public health officials claim to value evidence but then give non-evidence based advice (handwashing over masking), obscure or use low-value data over high-quality data (self-reported case counts over wastewater), etc.
• Getting a flu vaccine but not a Covid vaccine
• Interviewing long Covid experts who recommend masking in indoor public spaces but then going to Applebee’s
• Masking in one potentially risky setting (grocery store) but not masking in another similar or more-risky setting (classroom)
• Infectious disease conference where people are unmasked
• Long Covid and other patient-advocacy meetings where only half the people mask In-person only
• EDI events
• Not testing because it’s just family
• Mask breaks

#5 – Reaction formation – expressing artificial positive feelings when actually experiencing anxiety

• “It’s good I got my infection out of the way before the holidays”
• “I had Covid but it was mild”
• Anything quoted in Dr. Jonathan Howard’s book, “We Want Them Infected: How the Failed Quest for Herd Immunity Led Doctors to Embrace Anti-Vaccine Movement”
• Herd immunity (infections help)
• Hybrid immunity (infections help)
• “It’s okay because I was recently vaccinated”
• “Omicron is milder”
• “Textbook virus”
• “Building immunity”

#6 – Rationalization – Artificially reducing Covid anxiety through a weak justification.

• “I didn’t mask but I used nasal spray”
• “I don’t need to mask because I was recently vaccinated”
• “It finally got me.”
• “You’re going to get Covid again and again and again over your life.”
• “It’s not Covid because I don’t have a sore throat.”
• “It’s not Covid because I took a rapid test 3 days ago.”
• “It’s not Covid because I’m vaccinated.”
• “Airplanes have excellent ventilation.”
• “I’ve had Covid three times. It’s mild.”
• “Verily was cheaper.”
• “Nobody else is masking.”
• “Nobody else is testing.”
• “My roommates don’t take any precautions, so there’s no point in me either.”
• “I have a large family, so there’s no point in taking precautions.”
• Surgical masks (they are actual “procedure masks,” by the way)
• Various pseudo-scientific treatments used by the left and right
• Handwashing as the primary Covid public health recommendation
• Droplet transmission as a thing
• Public health guidance that begins with “data shows” (sic)
• Risk maps that never turn deep red
• 5 expired rapid tests
• “Masks recommended” instead of universal precautions
• “Seasonal”

#7 – Intellectualization – using extensive cognitive arguments to artificially circumvent Covid anxiety

• Unending threads to justify indoor dining
• Data-rich public health dashboards that use low-quality metrics and/or don’t change public health recommendations as risk increases
• The entire justification for “off-ramps”
• Oster, Wen, Prasad Schools denying air cleaners because it “could make children anxious”
• Schools not rapid testing this surge because it “could make children anxious”
• The mental gymnastics underlying the rationales for who can get vaccinated, how frequently, or with what brand
• Service workers told not to mask because it could make clients uncomfortable
• “What comorbidities did they have?”
• “The vulnerable will fall by the wayside”
• Musicians and others holding large indoor events
• 5-day isolation periods

Here’s a link to the full book, a newer edition than what I own. The information on defense mechanisms begins on textbook page 100. Please let me know if there’s a more accessible alt-text solution that you would prefer so I can do better next time.

Studies

Self-reported body function and daily life activities 18 months after Covid-19: A nationwide cohort study

Studies out of Sweden are particularly interesting because of the way that the minimizers tried to push the laissez-faire approach taken by the country. It hasn’t worked out so well. About 1/3 of the 11,935 people who had to take sick leave responded to a survey that was given 18 months after their first day of sick leave. The distribution is telling of the damage that was caused by the disease. “The reported prevalence of problems with daily life activities was 46%; 9.5% reported a small problem, 26% reported some problem and 10.3% reported a big problem.” Maybe letting it rip as suggested by those who signed the Great Barrington Declaration wasn’t such a good idea.

Changes in memory and cognition during the SARS-CoV-2 human challenge study

First, I will state that I do not think that this is an ethical study. Intentionally infecting young adult (18–30-year-old) volunteers is madness. I truly doubt that the volunteers who participated in this study really gave “informed” consent. I don’t think any rational person who is fully informed about this disease would consent to be infected.

“The main cognitive endpoint was a baseline-corrected global cognitive composite score (bcGCCS), defined as the baseline-corrected, standardised mean across all 11 tasks…

1. Motor Control–Measures visuomotor accuracy and reaction time
2. Object Memory (Immediate)–Measures short term precision recognition memory
3. Simple Reaction Time–Measures reaction time
4. Choice Reaction Time–Measures complex reaction time
5. 2D Manipulations–Measures mental manipulation of 2D visuospatial information
6. Four Towers–Measures mental manipulation of 3D visuospatial information
7. Spatial Span–Measures spatial working memory capacity
8. Target Detection–Measures attention and distractibility
9. Tower of London–Measures spatial planning
10. Verbal Analogies–Measures semantic reasoning
11. Object Memory (Delayed)–Measures medium term precision recognition memory”

There was a very important statement made in the middle of the study. “Notably, none of the volunteers reported subjective cognitive deficits.” This is a bit alarming in that people are not recognizing that they are impaired. It seems similar to how someone who has “only had a few drinks” may not realize that they are a danger driving on the road.

“In conclusion, this study confirmed that prospectively controlled infection with Wildtype SARS-CoV-2 is followed by objectively measurable reductions in cognitive task performance that can persist for at least a year. Immediate and delayed memory, and executive function were the most sensitive cognitive domains.”