Coronavirus news & views

Masks Redux

"You’ve got to be very careful if you don’t know where you are going, because you might not get there."

—Yogi Berra

As cases of COVID-19 ascend in areas of the US, some schools are reverting to requiring masks. Of course this is accompanied by renewed claims that they are ineffective. In fact, Florida governor Ron DeSantis issued an executive order barring local school districts from requiring their students to wear masks, claiming that there was no evidence that masks prevent infection in schools. That claim has been levied over and over by many politicians, talking heads, pundits, and assorted Facebook “experts.” But, they are flat wrong. There are multiple lines of evidence from a variety of disciplines—including materials science, infectious diseases, pediatrics and epidemiology—showing that masks can help protect children and teachers from getting COVID in schools. Some of that evidence has already been presented in these pages, and I now add to that body of evidence, more  data recently summarized in Scientific American.

1. For starters, laboratory experiments show that masks block the respiratory droplets and aerosols that transmit SARS-CoV-2, the virus that causes COVID. In one test, an engineering team at the University of Wisconsin–Madison used a machine in a classroom setting to pump out particles the same size as those that carry the virus from an infected person. The researchers placed several CPR dummies with or without masks around the room and measured the degree to which the aerosols penetrated the masks. They reported that a surgical mask reduced the chances of penetration by 382 times when compared to the maskless mannequins.
2. Then, in the real world, not a laboratory setting, several epidemiological studies also concluded that masks in schools work. Researchers at the ABC Science Collaborative in North Carolina collected data from more than a million K–12 students and staff members from schools across that state, which mandated masking in schools from August 2020 until July 2021. The scientists reported little in-school transmission when the mask mandates were in place during the fall, winter or summer months. During this time, in-school transmission remained low as COVID cases fluctuated outside the schools. With mask mandates, rates of within-school spread were as low as one percent.
3. Masks, combined with other prevention efforts, also reduce the risk that students might bring home the virus to parents or other relatives. An online survey of 2.1 million Americans by researchers at Johns Hopkins University showed a 38 percent increased risk of COVID-related illness in households with a child attending school in person. That risk went down, however, as the number of school-based mitigation measures, including mask mandates went up.
4. Studies done in wider communities beyond schools give the strongest real-world evidence that masks stop COVID’s spread. An international team of researchers conducted a randomized controlled trial involving nearly 350,000 people across 600 villages in rural Bangladesh. Half of the villages got free cloth or surgical masks and a promotional campaign encouraging their use. The other half did not. The researchers found that the mask intervention significantly curbed coronavirus transmission.

Bottom line:  The effectiveness of masks in schools is supported by many different studies and analyses that show similar results. There are more than a dozen studies beyond those cited here, that all point to the same conclusion:

Masks work.

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What Happened To The Flu And Other Respiratory Diseases?

A NYC based travel blogger who travels a lot used to get a respiratory infection whenever she flew. That stopped when the airline mask mandates went into effect. The mandates, of course, were designed to hinder the spread of the CoV-2 virus that causes COVID, but it makes sense that if masks and other physical (that is, non-medical) mandates worked to mitigate COVID, then we would see a decrease in other contagious respiratory diseases after the mandates were, well…mandated.

We did.

The mandates worked, despite persistent claims of some to the contrary. This particular blog subject was stimulated by a radio talk show where a couple of nonscientist talking heads announced that there was no scientific proof that the masks or other mandates prevented disease. I previously posted in these pages evidence that masks, in particular, do indeed work to retard the spread of disease (see here, here, here, and here). In this post, I present further data on how the mandates significantly reduced the incidence of other infectious respiratory diseases around the world. If the measures can reduce flu, then you can bet that they also reduced COVID-19.

Note, however, that this is not necessarily an endorsement for returning to the measures. Your humble scribe didn’t much like his glasses fogging up, or having to make two trips from the car to the store because he forgot his mask. But, let’s argue the issue based on its merits and not from false premises based on incorrect claims.

After South Korea implemented various hygiene and social distancing measures in response to COVID, they saw the 2019-20 flu season end an astounding 12 weeks earlier than the previous year. Epidemiological surveillance data bolstered by clinical diagnostic testing showed that infection from several different pathogenic respiratory viruses (including adenovirus, bocavirus, metapneumovirus, rhinovirus, flu, parainfluenza, and respiratory syncytial virus) dropped to nearly 0% just five weeks into 2020!

In the United States, the incidence of infection by influenza, respiratory adenovirus, rhinovirus, enterovirus, RSV, non-COVID coronaviruses, metapneumovirus, and parainfluenza viruses all decreased in March 2020, soon after implementation of mandates. Similar results were seen in Japan.

More dramatically, since pandemic mitigation measures were put in place, there has been a 99% global reduction of infections from both influenza types A and B compared to prior years. In particular, one of two flu B substrains has not been isolated in the world since August 2021 suggesting that this variant is now extinct. The overall genetic diversity of influenza viruses has also dramatically diminished indicating that other flu sub-types (or clades) have disappeared around the world since the pandemic mandates were put in place.

And this reduction of respiratory infectious disease does not only hold for those caused by viruses. Another study looked at surveillance data from 26 countries across 6 continents for several bacterial diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for disease due to Streptococcus agalactiae, a non-respiratory pathogen, were also collected from nine laboratories for comparison. All countries experienced a significant and sustained reduction in respiratory bacterial diseases in early 2020 (Jan 1 to May 31), coinciding with the introduction of non-medical COVID containment measures in each country. By contrast, the incidence of disease due to S agalactiae (which is not transmitted by the respiratory route) did not differ significantly from the 2 previous years.

Clearly, the mandates significantly reduced the incidence of respiratory infections by non-COVID viruses and bacteria. They worked. So, why did we still have COVID infections after the mandates went into place? The mandates reduced, not eliminated these diseases, so infections still happened. Since we did not have historical COVID infection data from previous years to compare with, the effects of the current mandates on the incidence of COVID are not as clear cut as they are with other diseases for which we do have historical data for comparison. But, as I wrote before (see above), it is clear that places in the US and around the world that used masks and other protective measures saw reduced incidence of COVID compared to similar places that did not.

Bottom line: The studies mentioned here regarding non-COVID infectious diseases fully support data previously posted in these pages that the mandates, including masks, are effective non-medical tools for controlling infectious respiratory diseases.

Don’t let anyone tell you differently.

Lingering Post-COVID Vascular Risks

George Burns once opined that “the secret of a good sermon is to have a good beginning and a good ending; and to have the two as close together as possible.” The same might be said for blogs. If so, this is a pretty good blog post.

We have known for some time that patients with COVID-19 are at risk for dangerous blood clots (also called deep vein thrombosis, or DVT), pulmonary embolism, and bleeding. Findings reported this month in the British Medical Journal reveal that this risk continues several months after COVID recovery.

The study compared more than one million people in Sweden who had COVID-19 to a control group of more than 4 million people who did not. The overall risks for each problem were low, but still elevated for up to six months following COVID. According to the report, DVT occurred in 0.04% of patients who had had COVID and in just 0.01% of control patients during the same time. Pulmonary embolism occurred in 0.17% of post-COVID patients and in 0.004% of control patients. And bleeding events occurred in 0.10% of patients who had recovered from COVID, while only 0.04% of control patients had such a problem.

While the risks of blood clots and bleeding were highest in patients whose COVID had been more severe, those who had had mild COVID still showed an elevated risk.

Bottom line: You are not out of the woods after you recover from COVID. Significant problems can arise a few months later.

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“Mater Artium Necessitas”

So said William Horman, 16^th century Headmaster of the Eton school. Translated, he posited, “The mother of invention is necessity.”

And necessity these days means environmental screening for SARS-CoV-2. Room air samplers have been developed and used to detect airborne virus RNA in large settings, such as hospitals and other large buildings people frequent. In fact active environmental air samplers have been used outdoors to detect airborne DNA and RNA as a way to survey animal populations in the wild. These are fairly large, immobile, active air samplers that require electricity to power them and crews to maintain them. While useful, environmental samplers are limited by their power requirements, lack of mobility, cost, and maintenance needs.

So, the mother of invention led to a portable, passive, personal air sampler that can be worn on one’s collar tool as described in a recent paper. It was reported to be quite effective for detecting ambient exposure to aerosol and droplet CoV-2 in the air.

The device uses a polydimethylsiloxane (PDMS)-based passive air sampler, which previously has been used to capture hydrophobic chemical contaminants and other nonpolar compounds, such as lipid-enveloped viruses that stick to the polymeric surface. After laboratory testing under controlled conditions that determined the unit could detect sub-infectious levels of virus exposure, samplers were passed out to select community members across Connecticut to surveil personal CoV-2 exposure. The study reported that 21% of wearers working in indoor restaurant settings, and 9% working in homeless shelters were exposed to 4-112 copies of CoV-2 per cubic meter of air. No exposure was reported for healthcare workers or “community members” who did not work in putative high-risk environments. The authors surmised that the lack of exposure by healthcare workers was due to the strict sterilization and hygiene procedures used in clinics and hospitals.

While the monitors did a good job sampling ambient air in real time, the need to later analyze the sample by RT-PCR for the presence of viral particles means that the results are not obtained in real time. This is a bit of a drawback to the current personal samplers.

Bottom line. These PDMS-based passive samplers may serve as a useful exposure assessment tool for airborne viral exposure in real-world high-risk settings and allow early detection of potential cases and guidance on infection control. More broadly, this also could be used to monitor the presence of other biological scourges in public places and serve as early warning devices for biological warfare threats.

Necessity is indeed the mother of invention.

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Still More Evidence For An Animal Origin Of The Virus

Conspiracy buffs won’t like this, but compelling new evidence presented in three papers, which include photographic and DNA data, has pretty much nailed down the origin of the SARS-CoV-2 virus. It began in a wet market animal not in the lab eight miles away as the conspiracists have conjectured. This new data comes from an international team of scientists which concluded that the coronavirus twice jumped from  caged wild animals into people at the Huanan Seafood Wholesale Market in Wuhan. These data correlate nicely with previous geo-epidemiological data showing the market, not the lab, to be the infection nidus with later infections radiating out from there.

Despite the Chinese’s government denial that live animals were sold in the Wuhan market, the new studies provide photographic evidence of wild animals sitting in stacked cages in the market in late 2019, in or near stalls where scientists found SARS-CoV-2 virus on a number of surfaces, including on cages, carts and machines that process animals after they are slaughtered at the market. This, along with a new genetic analysis pinpoints a specific stall at the market where the virus passed from an animal into people. These data also estimate the time when not just one but two zoonotic spillovers occurred, once in late November or early December and then again few weeks later. This coincides almost exactly with the timing of the outbreak of disease at and around the market.

The two initial infection events involved slightly different versions of the SARS-CoV-2 virus. The fact that they were related is evidence that the virus had spread and mutated in animals in the market before it infected humans.

A leader of two of the studies was U of Arizona professor, Michael Worobey, a viral pandemic sleuth who has been at the forefront of the search for the origins of the bug responsible for the current pandemic. His lead in the research is significant since, back in May, 2021, Worobey, along with 17 other scientists, called for investigation into the lab-leak theory. His latest research overturned that conjecture. This new evidence adds to previous evidence for an animal/market origin of the virus presented earlier in these pages here and here.

Final thought. It is sobering to think how these two simple infection events that occurred in November and December of 2019 in a Chinese market triggered something that has now caused six million deaths and untold misery around the world. And it is not finished with us.

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Son Of Omicron

“A rose is a rose is a rose.” –Gertrude Stein

Omicron is Omicron is Omicron (except when it becomes something different).

Two-plus years into the pandemic, many Americans are ready to declare the COVID crisis over. But, we have been at this juncture before—at the end of the very first surge (remember “flattening the curve?”), and again as Delta faded. Each time, a new virus variant came roaring back. Why should it be different now?

There are reports of two new sons of Omicron circulating in the world. The original Omicron, or BA.1 has spawned BA.2 and BA.3. While little is known about BA.3 at this time, very early indications are that BA.2 represents an even more infectious variant of Omicron, and it is spreading around the world and the US. This variant of a variant seems to be about 30% more infectious than Omicron BA.1. It quickly overtook BA.1 in South Africa and other countries and has caused a second Omicron surge in Denmark. BA.2 has been detected in 74 countries, and has become dominant in at least 10 of them: Bangladesh, Brunei, China, Denmark, Guam, India, Montenegro, Nepal, Pakistan and the Philippines, according to the World Health Organization's weekly epidemiological report.

In the US, BA.2 has been reported in 47 states and accounts for ~4% of all new infections according to the CDC, and it appears to be doubling fast. Samuel Scarpino, director of pathogen surveillance at the Rockefeller Foundation says that if infections double again to 8%, we will be in another exponential growth phase, or the fifth wave of the pandemic. In other words, BA.2 seems to be quickly backfilling the vacuum left as BA.1 peters out.

While BA.2 clearly arose from BA.1, it carries dozens of additional gene changes, making BA.2 as distinct from BA.1 as the Alpha, Beta, Gamma and Delta variants were from each other. This suggests that BA.2 might soon be given its own unique Greek letter designation.

What does BA.2 augur? While vaccination and prior infection still appear to protect fairly well against BA.2, this variant still seems more adept at skirting the immune system then the original Omicron. An early report also shows that vaccine induced antibodies often fail to neutralize BA.2 in tissue culture, and that the virus better replicates than BA.1 in nasal epithelial cell cultures. Nevertheless, those who have been vaccinated and boosted are 74% less likely to become ill from BA.2.

Hopefully, this reduced immunity will still be enough to provide an immunological redoubt against extensive spread of BA.2. The best thing that could happen is that as we become increasingly immunized by vaccine and infection, it might be enough to continue the drop in BA.1 Omicron infections, and check any surge from the new BA.2 variant. This is speculation at this point, and one thing we have learned over the last 2+ years is that the virus does not often respond as expected.

Then there is this: Very preliminary laboratory data hint that BA.2 might cause more severe disease than BA.1, and it appears capable of foiling some of the key weapons we have against COVID-19. In initial lab studies, a Japanese team reported that BA.2 has structural features that might make it as virulent as Delta was. This prediction of increased virulence was supported by hamster infection experiments, but this has yet to be confirmed or refuted in real-life epidemiological studies. Rest assured, those studies are underway, so we will see.

BA.2 also is almost completely resistant to some COVID treatments, such as sotrovimab, a monoclonal antibody therapy that is currently used against Omicron.

Bottom line: During the Spanish flu, as people wearied of the social restrictions designed to prevent the spread of the virus (there were no vaccines or drugs for flu then), many pushed back against the restrictions, which led to premature relaxation of the mandates. Cities like Denver and Philadelphia, which lifted their mandates early paid a hefty price. Other cities like St. Louis, which took a more cautious approach were relatively unscathed. Let’s hope that we are not relaxing and entering a “control phase” too quickly.

What’s ahead of us is not COVID’s end, but might be the start of a phase in which we continue to invest in measures to continue to shrink the virus’s burden. Success in this is not entirely up to us. The virus will have a say too. Our future will depend both on the virus’s continued and unpredictable evolution and on our responses, both immunological and social. The goal is to get ahead of any new variants with wide spread immunity and a growing formulary of antibody and drug treatments, and, yes, this might also require renewed mandates.

A detailed report  looking at past suspected coronavirus pandemics (e.g., the Russian “flu”of 1889, which was probably a coronavirus) published last August in the journal Microbial Biotechnology, suggested plausible scenarios in which elevated levels of COVID-19 deaths could last another five years or longer. This of course depends on what happens to and after BA.2.

It probably is not quite time to relax all mask mandates or let up on the push to vaccinate.

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COVID And Heart Disease—It’s All Relative

A new COVID study recently reported in Nature got the attention of your aging scrivener. It reported that COVID-19 increases risk for cardiovascular disease for at least a year after infection.  This was a large study of US veterans that found that the risk of having a heart attack, stroke or several other cardiovascular events was higher for those who had COVID-19 the year prior compared to those who weren’t infected. The risk was highest for those who had been hospitalized but was still elevated for those not admitted.

But when you read about elevated risk in the news or especially on social media, what does it mean? Hint: the media usually will not tell you this.

In order to understand the significance of such risk, we need to know both the relative and absolute risks. Relative risk is what we often see reported in alarming headlines—for example in this case, the risk of a heart attack was reported to be 63% higher in those who had had COVID-19. That is relative risk and it sounds pretty bad, right? Relative risk tells us that a risk is higher in one group than in another, but it doesn’t tell us the whole story. To put relative risk in perspective, we also need to know the absolute risk of the bad thing happening.

For example: let’s say that in a group of 100,000 “normal” people, one is expected to develop a rare cancer. But in people who were recently x-rayed, two people in 100,000 develop the cancer. The headlines would scream that x-rays caused a 100% increase of the cancer. The risk doubled after being x-rayed. Pretty chilling. Yet, the absolute risk in this example is extremely small—only one extra person out of 100,000 who are x-rayed gets the cancer.

Compare that to a situation where 10,000 out of 100,000 typically develop this cancer and x-rays again double the risk. That means 20,000 out of 100,000 people getting x-rays will get the cancer. In the two scenarios, the relative risk is identical—x-rays are associated with a doubling of cancer cases—a 100% increase in cancer risk. But in the second example, the absolute risk is much, much greater. Instead of causing cancer in only one out of 100,000 people (0.001%) as in the first example, the second example has x-rays causing cancer in 10,000 of every 100,000 people, or 10%.

Going back to the study in Nature, remember having COVID led to a 63% increased chance of having a heart attack. The data showed that the absolute risk of heart attack was 4.67/1000 for uninfected people compared to 7.59/1000 for those who had COVID-19 in the previous year. So, in absolute risk terms, an extra 3 people out of 1000 had a heart attack after having COVID-19. That puts the 63% increased relative risk in perspective.

Now that relative vs absolute risk have been explained, we are still left with the question of whether these extra three heart attacks are concerning. Like many other things, it depends how you look at it.

With tens of millions of people getting infected with COVID-19, an increase of three heart attacks for every thousand people can add up fast. Looking at the population level, this could lead to a noticeable rise in cardiovascular disease burden and lead health experts to begin planning for a wave of heart attacks. But, looking at the individual level, most COVID infected peoples’ risk of having a heart attack in the next year is pretty low. So, if you have COVID, you do not need to begin planning your funeral.

Bottom line: These alarming headlines need to be understood in terms of relative vs absolute risk and then looked at in terms of the effect on the population vs on the individual. Way too often during this pandemic, I have seen folks abusing both. For example, how often do you hear people saying that COVID is overblown because <1% die from it. This totally ignores the absolute risk (how many deaths is that) and focuses only on the individual effect while totally ignoring the population level effect (1% of 100 million is a lot of people).

It is all relatively absolute and absolutely relative.

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Another Unexpected Pandemic Consequence: Undiagnosed Cancer

In these pages, your humble bloggeur (that would be me) has written about several unusual consequences of the COVID-19 pandemic. Most of these were on the ironically funny side, such as farmed fish being too large for restaurant plates, rattlesnakes climbing in plane landing gears, and the ketchup packet shortage. But, not all of these odd aftermaths of the pandemic are humorous. The topic of this post is very unfunny.

It seems that as healthcare providers were swamped with COVID cases, or were at reduced capacity because staff became ill, or because service slowed in order to prevent CoV-2 spread, many people have missed routine medical care for non-COVID problems. It is feared that this will create a crisis in coming years involving increased diagnosis of cancers that were caught later than usual. As we deal with the fourth wave of COVID-19 caused by the Omicron variant, we are learning that the pandemic dramatically disrupted routine health screenings for cancer and other chronic diseases. Some now predict that the next crisis that could overwhelm the US health system will be a surge in advanced chronic diseases like cancer that went undiagnosed and untreated for too long.

Screenings for several major cancers and new cancer diagnoses fell significantly during 2020, according to a study published in December 2021 in the journal Cancer. This was not because there was less cancer in the world. It was because fewer patients were seeing their doctors.

A co-author of the Cancer study, and who is a professor at the University of Maryland School of Medicine, said that we have never before seen screening rates drop so dramatically in such a short time.

In one case, a Hispanic man in his 40s first noticed rectal bleeding in early 2020 that his doctor said was probably due to hemorrhoids. The man was unable to get a timely colonoscopy to rule out cancer because the local hospitals were overwhelmed with COVID-19 patients, and he also feared catching COVID if he went to a hospital swamped with COVID patients. Eighteen months later, he finally got a colonoscopy, which revealed advanced rectal cancer. Those 18 months likely were the difference between being cured by a simple polyp removal vs dealing with a cancer that had metastasized throughout his body.

At this point, nobody knows how many cases like this are out there. We will find out.  

This patient, as thousands of others like him, had the misfortune to notice symptoms that needed followup amid the biggest disruption of medical care in US history. In 2020, while hospitals curtailed services in order to prepare for the COVID surge, the number of colonoscopies plummeted 93 percent. By the end of the year, there had been 133,231 fewer colonoscopies performed compared to 2019. There also were 62,793 fewer chest CT scans, 49,334 fewer fecal blood tests, and prostate biopsies dropped 25%.

This drop in screenings has created a huge backlog that will take months to clear. A gastroenterologist at a small community hospital in the Middle-of-No-Where, Kansas was recruited by a larger hospital in Kansas City to do nothing but colonoscopies from 7 in the morning to “whenever at night.” They had a backlog of 1000 patients—a certain percentage of whom have cancer already growing in their colons while waiting to be told they had colon cancer. And that backlog begets a fresh one of new patients who also need to be scoped because they just noticed something like rectal bleeding, but will have to wait for those who have already been waiting.

This backlog creates a subtle form of medical rationing. It forces doctors to make hard choices about which patients to prioritize. "Lucky" are the serious patients who are moved to the head of the line. Not so lucky are those whose colonoscopies or mammograms or biopsies are then further delayed.

I would rather deal with rattlesnakes in my plane's landing gear or forgo mustard on my brat (which would be pushing the limit) than delay a needed medical test or procedure. It seems that your humble bloggeur (me again) has been caught in the backlog. I am scheduled to have an enlarged parathyroid gland removed next week, but COVID can still derail that. I won’t be certain that the surgery will happen until the day before I am to be operated on and that depends, in part, on everyone, including me, being COVID-free, and the OR not being diverted for use as a COVID ICU. If it proceeds as scheduled, I will have waited several months since the initial diagnosis for the surgery. An additional routine diagnostic test I need in order to determine how the fractious organ might have affected my bone health was scheduled six months out. Six months for a routine scan?

Harry Became Severely Disabled After The Vaccine

Does the crowing of a rooster cause the sun to rise?

Harry: A follower of this blog, recently wrote to me about the experience of his senior friend, Harry. With permission, I relay the story here and add some thoughts.

Harry was 80 years old and living a healthy, robust life. He did his own home improvement projects, he was mobile and drove everywhere--he lived an active life. His only health concern was a bit of a problem with high blood pressure (who doesn’t at his age?) that was well controlled with a statin drug.

But, soon after his third shot (booster), his shoulder in the non-injection arm began stiffening. After that, one side of his groin became very painful and the pain migrated to the other side and then began shooting into his legs. Within weeks, he was unable to walk, relying on a walker or wheelchair. He became home-bound. His painful arm is now useless—he needs to hoist it with his other hand to get dressed. Same with both legs. Harry gets by each day on pain meds, but he is reluctant to take a higher dosage to fully control the pain as it makes him too groggy, so he only sleeps an hour or two at night due to the pain, then catnaps in his recliner throughout the day.

This sudden and quick decline began about a month after his booster shot so he was convinced his new maladies were a consequence of the vaccine.

VAERS: Harry’s case is the sort of case that is reported to the CDC’s Vaccine Adverse Effects Reporting Site or VAERS. When someone begins experiencing untoward health problems soon after vaccination they or their doc can easily report it on the VAERS site, which has served as an early warning system for identifying rare side effects of vaccines since 1990. Thousands of people have reported post-vaccination symptoms, and the site is accessible to anyone. Hence, there is a CDC database listing thousands of reports of health problems following COVID vaccination that you can pull up after a few clicks.

The CDC uses this uncorroborated raw anecdotal information to look for patterns that could point to previously unknown side effects of vaccines. This is common practice for all medicines after they have been approved for use. Data from clinical trials that form the basis for approval or rejection of a new medicine or vaccine only include results from ~40,000 test subjects. That is enough to discover very significant and fairly common side effects. But, after the medicine gets on the market, patient data still are collected in order to see if there are serious side effects that only appear in, say, one out of 250,000 people and that would not be found during the clinical trial on just 40,000 subjects. Remember the COX-2 anti-inflammatory drugs that were widely used in the 90s but were pulled because they were found to cause rare, but serious cardiovascular problems? This was found by collecting post-approval data from a few million people who had taken the drugs. Evaluating data collected after a medicine is on the market is referred to as post-market or Phase IV research. This is what the CDC uses the VAERS database for.

The CDC then digs into the raw VAERS reports to make sense of them. They first confirm the reports and then to see if they are just correlations or causative. Scientists look at further health data on the patients, and look for similar recurring problems in other patients. This also means that the raw data reported on the VAERS site are just that—raw. The raw data you can see on the site have not been confirmed or determined to have actually arisen from a vaccine side effect. In fact, the VAERS web site carries this clear disclaimer:

“VAERS reports alone cannot be used to determine if a vaccine caused or contributed to an adverse event or illness. The reports may contain information that is incomplete, inaccurate, coincidental, or unverifiable. In large part, reports to VAERS are voluntary, which means they are subject to biases. This creates specific limitations on how the data can be used scientifically. Data from VAERS reports should always be interpreted with these limitations in mind.”

The task for the CDC then is to separate health complaints that are just coincidental (i.e., that would have happened anyway without the vaccine) from those that are causal (i.e., that were caused by the vaccine). The fact alone that someone vomited a day after being vaccinated cannot be taken as proof that the vaccine caused the vomiting. There is a big difference between correlation, i.e., when two unrelated things happen together, vs causation when one thing leads to the other thing.

But, this is what the vaccine naysayers are doing—they look at the VAERS site and believe that all those raw reports are causative reports showing that the vaccines harm people. In other words, they completely ignore (or do not even read) the CDC disclaimer that the VAERS data are very incomplete and require further investigation before any conclusions can be drawn. When you hear someone on social media, TV, or the radio claim that tens of thousands of people have been seriously hurt by the vaccines, they are basing that claim on an incompetent (and possibly dishonest) use of the raw, uncorroborated VAERS data. I know this because every time I ask someone to back up their claim that the vaccines have injured tens of thousands of people, they eventually cite the VAERS database. When I quiz them further, most clearly have not even looked at the complicated VAERS web site, but are reporting second hand what they have heard elsewhere.

The truth is that few of the VAERS reports have been confirmed to be related to vaccination. Furthermore, the side effects mostly are of the “sore arm” variety, while serious health effects are vanishingly rare. Only about 200 people have actually died from the vaccines. All this compares to the almost 900,000 deaths (and counting) from COVID, and the ~20 million (and counting) cases of long term debilitation from long COVID. Remember, both the deaths and long COVID are prevented by the vaccines.

Back to Harry: Harry developed his debilitating conditions shortly after his third shot and attributed his woes to the vaccine. That is a temporal correlation—the debilitation happened shortly after the vaccine. But, is there anything that proves the vaccine caused Harry’s debilitation?  Well, a deep dive into Harry’s medical condition, like the CDC does into the data in its VAERS data, proves the vaccine did not cause Harry’s condition.

Sadly, a couple of days ago my blog friend told me that recent scans showed a mass on Harry’s lung. He has end-stage lung cancer that has spread to his pelvic bones and shoulder causing severe bone lesions and the pain. He will soon die from untreatable advanced cancer. It seems that Harry has a 50+ history as a smoker. But, he, as well as folks who abuse the VAERS system, totally ignore that kind of history and jump on the less-likely correlation between vaccination and diminishing health as proving a cause and effect relationship between the two. In doing this, people must assume that there could be no other causative factor for any malady that appears shortly after vaccination. Harry himself, ignored his long history of smoking, which is, by far, the leading cause of lung cancer, while the vaccines have been associated with zero cases of cancer.

This is a sad example of the mental gymnastics anti-vaxers resort to in order to confirm their bias against the vaccine. Real data be damned once they see a simple correlation that fits their bias.

Bottom line: Just as the vaccine did not cause Harry’s cancer, the crowing of the rooster does not cause the sun to rise. Both are correlations of events only temporally, not causally related.

Do not buy into the claims that the VAERS shows that people are suffering by the thousands from the vaccines. It is not true.

The Long Haul, Part 4: The Cost of Long COVID In Terms Of Individual Health And Quality Of Life

Surviving COVID-19 is one thing, recovering is another.

My frustration with those who would minimize the impact of COVID-19 is reaching an apex. I constantly have to deal with their baseless rationalizations that “it is just a cold,” or “it only kills 0.01% of people” (actually the number is 2% around the world), etc. And I constantly reply to these iconoclasts that COVID has become, by far, the leading killer in the US. I also explain over and over that treating simple mortality percentage as the only relevant statistic to consider is falderal. For example, the Spanish flu also killed “only” 2% of those infected, but in just 24 weeks, that virus killed more people around the world than were killed in WWI AND WWII together! The percent figure is meaningless without considering the percent of what. Why do they continue to ignore the devisor and, hence, the total number of deaths?

A small percentage of a very large number is, in fact, another large number.

Those who wish to downplay the significance of the pandemic only focus on this mortality percent, but mortality is NEVER the whole story for any pandemic. A serious person will also consider the morbidity caused by the disease. In fact, the major CDC publication on health in the US is called the Morbidity and Mortality Weekly Report. Notice that it considers both morbidity and mortality, and further notice that morbidity is listed first in the title. I have made three prior posts in this series on Long COVID, about the significant lasting morbidity of COVID-19. You can see these posts here, here, and here. In those posts, I shared data showing that some ~10-30% of COVID survivors suffer serious health problems that last months.

In those posts, I mentioned the cases of a young, healthy MD, and of a young, healthy journalist, both of whom struggled with long COVID, and how it affected their careers and cost them thousands of dollars in out-of-pocket expenses for the dozens of tests and doctors they needed. In an article in Maclean’s magazine, a reporter interviewed many Canadian long COVID patients and heard how their lives have been turned upside down. They reported that they are unable to live like they used to and care for their families, do anything mildly strenuous, or even cook their meals. They spend long stretches of time in bed. Many of those interviewed had not returned to work several weeks after recovering from the acute disease.

Anecdotes like these have been repeated millions of times around a world that, according to the Johns Hopkins University COVID tracker, has seen more than 330 million cases of COVID (and this is a significant undercount since many countries do not record these data well). Research has corroborated these anecdotes.

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Common long-term symptoms include debilitating fatigue; respiratory problems; and “brain fog.”  Other common symptoms include compromised function of the heart, and kidneys, which sometimes require transplantation. Wide-spread clotting problems can cause significant illness and even limb amputation. There also are frequent neurological and neuropsychiatric symptoms as highlighted in Part 3 of this series. Surprising manifestations continue to emerge, such as new-onset diabetes.

Lung scarring often occurs in patients who experienced COVID-caused acute respiratory distress syndrome (ARDS), a common problem seen in acute COVID patients who required ICU care. ARDS is a serious respiratory problem that can be caused by different respiratory viruses and other things. About a third of patients with ARDS arising from any cause were unemployed 5-years later because of their lung damage. It is fully expected that patients with COVID-related ARDS will be found to fare similarly.

There also is the dysfunctional immune response common in many moderate to severe COVID cases that can cause long-term multi-organ damage, particularly in the liver and kidneys. It can also disrupt coagulation control of the blood, sometimes leading to amputations, mostly in patients in their 30s and 40s. It was reported that amputations due to vascular problems have doubled since the CoV-2 virus arrived. Compromised coagulation control in COVID patients can also precipitate adverse cardiovascular events such as heart failure, or hemiplegia due to strokes. Data from the COVID Infection Survey on long-COVID suggest that the risk of major adverse cardiovascular events and long-term illness is about ten times higher in COVID patients (even after mild COVID) compared to non-COVID matched controls. A Dutch study found that 31% of COVID ICU patients suffered thrombotic complications. These problems can unexpectedly pop up in people who had completely recovered from COVID.

A global survey tallied 205 different symptoms across 10 different organ systems that can persist after COVID infection has cleared. Typically, these manifold long COVID symptoms do not appear in isolation, but in multi-symptom clusters. A long hauler typically has several of these problems at a time.

While it is estimated that overall, 10-30% of COVID patients become long haulers, reports on the number of people suffering long COVID vary widely. Depending on the report, anywhere from 30-90% of COVID survivors suffer long term health problems. And even at the lower end of that range, 30% of over 330 million people world-wide who have been infected is a very large number. It represents an enormous personal toll in terms of lost health and diminished quality of life. Some of these reports are summarized below.

• Half of 70,000 hospitalized UK COVID-19 patients experienced long-term complications, according to a study published in July. Complications occurred regardless of age group: For instance, 25% of adults aged 19-29 developed complications, as did 33% of those aged 30-39. Complications affecting the kidneys and respiratory system, liver injury, anemia, and arrhythmia were the most common.
• Many COVID-19 survivors require extensive and prolonged rehabilitation. An European study found about one-third of 1,837 non-hospitalized COVID patients (i.e., those with mild disease) needed a caregiver three months after their symptoms started.
• In April the CDC reported in its Morbidity and Mortality Weekly Report that 69 percent of nonhospitalized adult COVID patients in Georgia required
• one or more outpatient visits 28 to 180 days after their diagnosis.
• A study published last February in the Journal of the American Medical Association found that roughly one-third of 177 people who had mild COVID disease not requiring hospitalization reported persistent symptoms and a decline in quality of life up to nine months after illness.
• 70% of people hospitalized for COVID-19 in the UK had not fully recovered five months after hospital discharge. They averaged nine long COVID symptoms requiring continued medical care.
• A study in South Korea found that 90% of patients who recovered from acute COVID experienced long-term side effects.
• According to a report in the journal, Lancet, 75% of people hospitalized with COVID-19 in Wuhan early in the pandemic, reported continued problems with fatigue, weakness, sleep problems, anxiety and depression six months after being diagnosed with the disease. More than half also had persistent lung abnormalities.

Data like these have been commonly reported around the world, pointing to a more chronic and expensive health problem than seen with the flu or common cold, which often is caused by different coronaviruses. A July 2021 article in Scientific American talked about how all of this indicates that long COVID will cause a “tsunami of disability” that will affect individual lives as well as create enormous strain on the health system. Consider the numbers: More than 60 million Americans (this is an underestimate since many COVID cases are not reported) have been infected with the CoV-2 virus. Therefore, if only 30% of these suffer long COVID, we are talking about 20 million long haulers and counting.

The related health care and disability costs of all of this are also still being calculated. How many “long haulers” will not be able to return to work for months, or at all? How many will need short-term disability payments, and how many will become permanently dependent on disability programs? As increasing numbers of younger people become infected, will we see a generation of chronically ill? This then moves us to consider the economic and financial cost of long COVID, which will be the topic of the next installation in this series.

Stay tuned.

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