Category: Epidemiology

Last week, a little-noticed milestone in the U.S. COVID pandemic occurred – it is the first week that the number of new cases of COVID exceeded the number of vaccine doses administered since the vaccines became available to the general public. It seems that America is ready to be done with COVID and move on. The good news is that both the number of cases and the number of deaths is falling. The bad news is that they are still very high – it’s just that we have developed a national desensitization to the COVID numbers. Last week, 226,618 Americans were diagnosed with COVID, that is enough people to fill Yankee Stadium five times over. In addition, 22,422 people were hospitalized with COVID and 2,290 people died of COVID. To put that in perspective, last week, 4 times more people were admitted with COVID and 10 times more people died of COVID than were admitted and died of H1N1 influenza during the peak week of the 2009 H1N1 influenza outbreak in the U.S. In other words, the best days of COVID are still worse than the worst days of H1N1 influenza. So, what will the COVID picture look like in the next year? We can learn a lot from the epidemiology of other viruses.

 

What we can learn from non-COVID seasonal coronaviruses

Coronaviruses have been infecting humans for as long as there have been humans. There are dozens of different coronavirus species that each have a preferred animal it infects. For humans, there are four seasonal coronavirus strains cause cold symptoms: 229E, NL63, OC43, and HKU1. These coronaviruses are common and cause 15-30% of all common colds. These viruses recur predictably every year as reported by the Public Health Agency of Canada:

There is a striking seasonality to coronavirus infections with most infections occurring in the winter. The graph below shows the average number of coronavirus infections reported by the Public Health Agency of Canada over a 10-year period:

Future COVID seasonality

For the purpose of simplicity, I will use “COVID” (the name of the disease) as synonymous with “SARS-CoV2” (the name of the virus) in this post. At some point in the future, COVID will most likely go the way of other coronaviruses and assume the same seasonal variation with a baseline year-round rate and a rate surge in the winter. We have already seen signs that COVID has a predilection for the winter months in the case rates during the first 3 years of the pandemic. The graph below shows the number of COVID deaths per 100,000 per week in orange and the number of cases per week in blue.

This graph demonstrates that the death rate for COVID peaks about three weeks after the case rate peaks, consistent with the finding that most people who die from the infection do so about 3 weeks after initial diagnosis. There has been a peak in deaths every January (red dashed lines)  followed by a second, smaller peak in deaths every summer (black dashed lines).

Assuming that COVID becomes a seasonal infection, how long will it take to become primarily seasonal? Any answer to this question is speculative but it will likely be several more years before the seasonal epidemiology of COVID resembles that of other coronavirus infections. Until then, it is likely that there will be a moderate or low baseline level of COVID year-round with case numbers increasing in the winter. The main determinant to becoming seasonal is population immunity.

By now, most Americans have either been vaccinated against COVID or have had a COVID infection or both. The result is that most Americans have some degree of immunity. But what we know from the usual seasonal coronaviruses is that immunity fades and it is common for people to get reinfected with the same coronavirus strain. One study found that up to 21% of people get reinfected with the same strain of non-COVID coronavirus within 6 months of the initial infection. Going forward, having immunity from a previous COVID infection or a previous COVID vaccine will not entirely protect a person from getting a future COVID infection. But immunity can reduce the severity of infection, reduce death rates, and reduce transmission. For the population as a whole, compared to people vaccinated with a bivalent booster, unvaccinated people are 3 times more likely to be diagnosed with COVID, 16 times more likely to be hospitalized with COVID, and 10 times more likely to die from COVID. These numbers likely underestimate the protectiveness of vaccines since people most vulnerable to COVID have been the most likely to get the bivalent booster. As an example, people age 65-79 who are are unvaccinated are 14 times more likely to die of COVID than people age 65-79 who are vaccinated with a bivalent booster.

Unfortunately, we seem to have developed a national aversion (or at last indifference) to vaccination. Currently, 92% of adults have received at least one dose of a COVID vaccine but only 79% received a full primary series. Worse, only 20% of adults have received a bivalent booster. The sooner we can overcome our culture of vaccine hesitancy, the sooner we can overcome the consistent high number of non-seasonal COVID cases.

Future COVID mortality rates

Over the past 3 years, one out of every 300 Americans have died of COVID. It is difficult to know the exact mortality rate of COVID infections because we do not know exactly how many Americans have been infected with COVID. Using case numbers reported to the CDC, the average mortality rate since the beginning of the pandemic is 1.63%. This likely overestimates the true mortality rate because many people who get infected either do not get tested at all or do home tests that are not reported to the CDC.  The mortality rate has varied considerably over the past 3 years. In the graph below, the case numbers reported to the CDC are in blue and the mortality rate of infection is in red.

It is quite striking that when the case numbers are high, the mortality rate is low and vice versa. On possible explanation for this curious finding is that when new, more infectious COVID variants emerge, many non-vulnerable people (children and young adults) get infected with these variants at school and in workplaces causing a surge in case numbers. Because these people are often younger or have some degree of immunity from previous infection, they are less likely to die. Over the following several weeks, they then infect vulnerable people who are more likely to die: the elderly, the nursing home residents, and those with chronic diseases. This possible explanation is purely conjecture, however.

Another way of estimating the mortality rate of COVID in the U.S. is to use data from the Commercial Laboratory Seroprevalence Survey. This survey estimated the number of Americans who have had COVID based on COVID antibody tests performed on left-over blood from commercial lab tests. Notably, the antibodies tested for would be produced by COVID infection but not by COVID vaccination. An advantage of using data from this survey is that it picks up those people who either did not get tested for COVID because they had mild or asymptomatic infections and those who did home COVID tests that were not reported to the CDC. As of February 2022, 57.7% of samples contained antibodies against COVID. If we assume that this is reflective of the U.S. population as a whole, then as of February 2022, 57.7% of Americans had been infected by COVID – that translates to 192,306,920 people. At that time, the total number of people reported to have died of COVID was 939,875. Using these numbers, the mortality rate of COVID infection calculates to be 0.5%

From these analyses, it appears that the COVID mortality rate has most likely been somewhere between 0.5% and 1.5% over the course of the pandemic. In the future, the COVID mortality rate will hopefully be lower as more Americans have immunity from repeated infections and from booster vaccinations. However, it is a near certainty that some number of people will continue to die of COVID infections in future years. Decades of experience with influenza has shown us that neither natural immunity (from past infections) nor vaccination immunity prevents all deaths from influenza. There will always be deaths in vulnerable populations such as the elderly, the immunocompromised, the obese, and the diabetic. In these individuals, immunity can reduce but not eliminate the chance of dying from infection.

COVID is a new infection for the human race. A useful lesson from history about new infections is from the European settlement of North and South America in the 15th and 16th centuries. The indigenous peoples of the Americas had never been exposed to infections such as smallpox, a disease that is highly contagious but preferentially kills adults. When the first Europeans arrived, they brought with them these diseases that then rapidly spread throughout the continents. It is estimated that within a few decades of Columbus’s first landing, about 90% of indigenous people had died of infections such as smallpox. After burning through native populations, the smallpox mortality among these populations settled into a lower baseline number. If COVID behaves like smallpox, then it is likely that once COVID burns through the world’s human population that it will settle into a lower steady state mortality rate.

Future COVID hospitalizations

Early in the pandemic, U.S. hospitals were overrun by COVID patients. With no effective treatments, many patients died rapidly and survivors often required prolonged ICU care, lingering in the hospital for weeks. With better treatments and better population immunity, more patients are surviving their COVID hospitalization and they are improving faster, resulting in shorter hospital stays. However, COVID is still resulting in a relatively large number of hospital admissions. The graph below shows new COVID hospitalizations in orange and COVID deaths in blue as reported by the CDC. During the January 2021 surge, 1 person died for every 3 COVID hospital admissions. That ratio has improved so currently, 1 person dies for every 10 COVID hospital admissions.

During the January 2021 COVID surge, the CDC reported that 19% of all U.S adult hospital beds were occupied by COVID patients and 31% of all U.S. adult ICU beds were occupied by COVID patients. A year later, during the January 2022 surge, COVID patients accounted for 23% of adult hospital beds and 31% of adult ICU beds. These two surges put an enormous strain on our country’s hospital resources, particularly our intensive care units. Last week, 3.4% of both adult inpatient and ICU beds as well as 1.5% of both pediatric inpatient and ICU beds are occupied by COVID patients.

Although it is unlikely that we will see the overwhelming spikes in COVID hospitalizations such as we saw in January 2021 and January 2022, it is likely that we will continue to see seasonal fluctuations in hospital utilization as COVID assumes a more seasonal pattern. Because of this, hospitals should start planning now to ensure sufficient hospital beds and staffing for an anticipated spike in COVID admissions next winter. During the most recent COVID surge in January 2023, COVID patients occupied 6.5% of both adult hospital beds and adult ICU beds. Children with COVID occupied 2.4% of pediatric hospital beds and 2.3% of pediatric ICU beds. To be conservative, hospitals should plan on a similar increase in hospital bed and ICU demand next winter.

Future COVID treatments

Experience with other human infections has shown us that science makes incremental advances in treatment resulting in incremental improvement in mortality rates. Examples include tuberculosis, hepatitis C, and HIV. In each of these infections, the earliest treatments were marginally effective but as pharmacologic research advanced, subsequent treatments were better and better. The result is that now, most people infected with these pathogens can either be cured or kept in indefinite remission with current medications.

Over the past three years, we have also seen steady improvement in COVID treatments ranging from the ineffective (azithromycin) to the ludicrous (ivermectin) to the somewhat effective (Molnupiravir) to the highly effective (Paxlovid). If advances in COVID treatment is anything like hepatitis C, HIV, and TB, then we will likely have even better COVID treatments in the future.

Wild cards

Evolution shows that all living things mutate as they reproduce. COVID has been no exception with new variants emerging that are more infectious than the previous variants. The greater the total number of viruses present on earth at any given time, the greater the likelihood of a new variant developing. As worldwide natural and vaccine immunity increases, it is likely that the rate of new variant emergence will slow. This should give vaccine producers more time to create vaccines effective against those new variants, thus improving our ability to stay one step ahead of COVID. Nevertheless, that other variants will arise in the future is a certainty.

One of the reasons that we cannot eliminate COVID from the planet is that it can infect other animals. So far, COVID has been demonstrated to infect more than 30 different kinds of animals. The disease is not as severe or life-threatening as it is in humans but now other animals can serve as viral reservoirs. Even if we could eliminate all human infections today, humans would just get reinfected from deer, pigs, and dogs tomorrow.

Not only will the human race face new COVID variants but we will also likely see new coronaviruses make the jump from other species to ours. This has already happened recently with the coronaviruses that cause MERS (camels) and SARS (bats). There are many, many different coronavirus species with each species affecting different animals. Thus there are different coronavirus species that have been found in cats, dogs, pigs, camels, bats, cows, and chickens. Mutations in any of these coronavirus species can allow them to become infectious to other animals, including humans. The new mRNA vaccine technology now gives us the ability to rapidly develop and distribute vaccines against new coronavirus species that do cross from animals to humans. One challenge is that new vaccines against new viruses require clinical trials to determine vaccine effectiveness and safety. These trials take time and require a large number of subjects. Ideally, we need ways to rapidly predict efficacy and safety without the months required to perform clinical trials.

A future with COVID

It seems clear by now that COVID is not going to go away in the future. It is unrealistic to think that COVID case numbers will steadily go down until COVID drops off the face of the Earth. It will more likely just become one of the many respiratory viruses that humans regularly get infected with. It is likely that there will be a year-round baseline rate and seasonal rate surges. However, we have the ability to control COVID case numbers and case severity by optimizing immunity and by continued research into new medications.

March 6, 2023

I am in an increasingly small minority of Americans who still wear face masks in public indoor areas. And I feel increasingly self-conscious when I’m the only person wearing a mask. But should I feel that way?

I realized that something had changed when I attended the annual American College of Chest Physicians meeting in Nashville last week. When I preregistered a few months ago, I had to attest online that I agreed to wear a mask at all times while attending convention events. When got to the meeting last week, the instructions had changed to “masks are recommended”. In the meeting rooms, I kept track – overall, only 5% of attendees wore a mask. I’m used to this percentage of mask-wearers at the grocery store but at the meeting were hundreds of the country’s pulmonary and critical care physicians who are more intimately familiar with the danger and transmissibility of COVID-19 than any other segment of the U.S. population. Except while delivering a lecture, I wore an N-95 mask the entire time but could not help to think “Does everyone think I’m weird?“.

During the first year of the pandemic, I spend endless hours caring for critically ill COVID patients in our ICU. I intubated them, performed bronchoscopy on them, and pronounced them dead. Back then, everyone wore a mask – in the hospital, in the grocery store, in the airport. And masks worked. Unlike the majority of Americans, I have made it this far through the pandemic without getting infected. I was even part of a CDC prospective study of high-risk healthcare workers and had to get serial blood antibody tests to determine if I got infected caring for COVID patients. All of the tests were negative. When vaccines became available in December 2020, I got my first vaccination at 7:00 AM the first day they were available. And I’ve gotten all 3 booster vaccinations in the first week that they were offered. Other than being 64-years-old, I have no risk factors for severe COVID. So, you’d think I’d be ready to go back to life as it used to be, without face masks.

The thing is, I just don’t want to get COVID.

Yes, I realize that the chances of me dying if I get infected are pretty slim. But they are not zero and besides, there are a lot of other unpleasant complications of COVID that I’d just as soon avoid.

Just because you’re vaccinated doesn’t mean COVID can’t kill you

The COVID vaccines we now have are great. But like most vaccines, they are not perfect. Data from the CDC shows that in August 2022, people who had the primary vaccine series plus 2 or more boosters were 12-times less likely to die of COVID than unvaccinated people. But still, 1 out of every 200,000 Americans died of COVID that month despite being fully vaccinated and boosted. To put that in perspective, if you are vaccinated, you are still 1,500-times more likely to die of COVID than to win the Powerball lottery.

A relative commented to me recently that “COVID is no worse than the flu“. Unfortunately, it is actually worse… much worse. In a typical season, about 25,000 Americans die from influenza. In 2021, 463,000 Americans died from COVID. In other words, Americans were 18-times more likely to die of COVID than die of influenza. And that was despite strict social distancing, masking, school closures, and work-from-home initiatives in 2021. This graph shows the annual deaths from influenza (blue) compared to deaths from COVID (gold).

COVID causes assorted badness other than death

Last month, I was surf fishing in North Carolina. I got to talking to a fellow fisherman who as a chiropractor in his late 60’s who had a bout of COVID shortly after returning from a trip to Ireland. He was fully vaccinated and boosted but still felt wiped out for several days. Weeks later, he still could not taste or smell anything. Personally, I like to taste and smell. I like to be able to tell the difference between a pice of unseasoned tofu and a medium-rare lamb chop. I enjoy a Mendocino pinot noir a lot more than a bottle of Two-Buck Chuck. I don’t want to give those things up. A study from JAMA this summer found that 56% of people infected with COVID have some loss of taste and smell at the time of initial infection. Of those affected, 12% still had loss of taste and smell 2 years after infection. Although the newer variants of COVID are less likely to affect taste or smell than the original COVID, 44% of those infected with Delta and 17% of those infected with Omicron had loss of taste and smell.

Patients experiencing long COVID symptoms have now become common in primary care practices. A study from this month’s JAMA looked at 1.2 million people infected with COVID and found that 6.2% of people have long COVID symptoms – persistent fatigue in 3.2%, persistent respiratory symptoms in 3.7%, and cognitive dysfunction in 2.2%. The average duration of long COVID symptoms was 9 months in those who required hospitalization for their COVID infection and 4 months for those who did not require hospitalization. However, 15% of people with long COVID had symptoms lasting more than 1 year. It seems to me that wearing a mask is a small price to pay in order to avoid fatigue, shortness of breath, and brain fog.

Although vaccination greatly reduces the chance of severe COVID requiring hospitalization or ICU care, breakthrough infections are common in vaccinated people as well as those with immunity from previous infection. A study in the New England Journal of Medicine found that breakthrough infections in vaccinated people typically caused fever, muscle aches, loss of taste/smell, and cough. These symptoms lasted more than 14 days in 31% of people and 23% of people had to take off more than 10 days of work due to symptoms. In short, it is no fun to have a breakthrough COVID infection even though you will probably survive it.

The CDC’s COVID dashboard indicates that the number of COVID cases in the U.S. is falling – only 260,000 new infections were reported last week – down from 5.6 million new cases nine months ago during the third week of January 2022. However, the current prevalence numbers underestimate the true number of new covid infections because many people either choose to not be tested or test themselves using over-the-counter COVID home tests. Either way, these cases do not get reported to local public health departments and are thus not included in the CDC’s data. The bottom line is that tens of thousands of Americans are still getting COVID infections every day.

The social pressures to wear masks

The psychology of masking and unmasking is complex and was nicely described in an essay by blogger JTO, PhD. The various psychological concepts that contribute to people disliking masked people when they themselves are not wearing masks include cognitive dissonance, confirmation bias, psychological reactance, and hostile attribution bias. The net effect of these is strong peer pressure to conform when those around you are not wearing masks.

Social psychologist Dr. Wendy Treynor has proposed a theory of peer pressure called “identity shift effect”. According to this hypothesis, a person’s internal harmony is disrupted a person fails to conform to a group standard resulting in a threat of social rejection. In order to eliminate this threat, the person changes their behavior to conform to the group but in doing so, causes internal conflict because that person has now violated their own code of conduct. To eliminate this internal conflict, the person undergoes an “identity shift” and adopts the group’s standards as their own, thereby eliminating internal conflict and restoring internal harmony. The net result is that the person adopts a new attitude.

For example, if you go to a restaurant wearing jeans because you don’t like getting dressed up and everyone else in restaurant is wearing an evening dress or a suit, you will experience a great deal of psychologic disharmony. The next time you go to the restaurant, you wear a dress or a suit in order to avoid the disharmonious feelings, even though in the past, you didn’t like wearing formal attire.

As human beings, we strive to be accepted by groups of other people. Even non-conformists are often trying to conform to the behavior of other non-conformists to prove that they are just as much of a non-conformist as the other non-conformists.

When you wear a face mask in a store full of unmasked customers or in a church full of unmasked parishioners, you start thinking: “Do they think I’m weak?” or “Do they think I’m a coward?” or “Do they think I’m the one who is contagious?” Fortunately, wearing a mask is not as much of a violation of social norms as wearing a MAGA hat to an ACLU convention or wearing a Cincinnati Bengals jersey in a Pittsburgh sports bar. But nevertheless, there is increasing peer pressure to take one’s mask off.

The advantage of being old

One of the wonderful things that happens when you retire is that you now have the luxury of doing what you want to do rather than what everyone else is doing. Even so, I find myself sometimes apologizing for wearing a mask when no one else is. I’ll sometimes offer up excuses such as “Sorry, I worry too much because I’m a senior citizen” or “I’m going to visit my pregnant daughter and don’t want to risk exposing her“. Most people who I pass in a store or airport just think I’m weird. But I can live with that because I plan to enjoy a healthy life for many more years. Life is just too short to waste days or weeks of it being sick. So, I’m OK with being weird.

October 28, 2022

There are two ways to become immune to COVID-19: either from previous infection (natural immunity) or from vaccination. But is one better than the other? Many people believe that anything “natural” is better than “artificial” and consequently some pundits, influencers, and bloggers advocate for for natural immunity over vaccination immunity. The COVID Nationwide Antibody Surveillance Survey reported that by February 2022, 58% of Americans had been infected with COVID-19 and thus have some degree of natural immunity. The most recent CDC vaccination data shows that 80% of Americans have received at least 1 dose of a COVID vaccine and 68% have received 2 doses with resultant vaccination immunity. Therefore, most Americans have some degree of immunity one way or the other. Employers and governments are now grappling with whether to mandate vaccination or proof of previous infection as workers return to in-person workplaces.

 

Immunology 101

At the risk of oversimplification, there are two main components of our immune systems – cellular and humoral. Cellular immunity involves T-lymphocyte cells that help fight infection. Humoral immunity involves immunoglobulins (antibodies) that help fight and prevent infection; immunoglobulins are produced by B-lymphocytes. There are five types of immunoglobulins but the three types that are most important for preventing viral infection are IgG, IgM, and IgA. All three of these types of antibodies can be found in the bloodstream but mostly IgA is found on the surface of respiratory cells, such as in the mucus that lines the airways and nasal passages.

When a person gets infected with a virus, the virus uses special molecules on its surface that can bind to cells and then slip inside those cells. These surface molecules are like keys that open the cells allowing the virus to get in. Once inside of a cell, the virus takes over the cell and causes the cell to start to manufacture thousands of copies of the virus (its like what happened to people in the movie Alien). The cell then dies and releases all of the newly manufactured viruses that can then infect more cells.

Once infected with a virus, the body’s immunologic response is to create antibodies to pieces of the virus. Antibodies first start to be produced by B-lymphocytes 5-7 days after an infection with the first antibodies being IgM. Within days to weeks, some of the B-lymphocytes switch to making IgG plus IgM antibodies and the levels of IgM antibodies quickly fall. Over time, the quantity of IgG antibodies in the bloodstream also gradually falls but when the body is re-infected with the same virus, memory B-lymphocytes that had previously been “taught” to make specific antibodies against that virus can ramp up production very quickly resulting in high IgG levels in 1-2 days.

Antibodies fight viral infections in three ways. First, they bind to molecules on the surface of viruses that attach to cells. This is like covering up the “key” so that the virus cannot attach to and get inside of cells. Second, when antibody-coated viruses do get inside of a cell, that cell uses the antibodies as a signal to the rest of the immune system that it is infected, causing other immune cells to attack and kill the cell before it can produce new viruses. Third, when viruses are coated with antibodies, immune cells called macrophages recognize them and “eat” the viruses. The macrophages then digest the viruses and destroy them.

Respiratory viruses, like COVID-19, are first inhaled into the nose and respiratory tract where they get stuck in the mucus that lines those passages. The viruses then infect airway cells and eventually get into the bloodstream where they are carried throughout the body and can infect cells in the heart, liver, brain, muscles, etc. IgA in the mucus of the airways (mucosal immunity) is the first line of defense when a person inhales COVID-19 viruses. IgG in the bloodstream (systemic immunity) is the next line of defense once the COVID-19 virus gets past the airway cells and invades the body.

Antibodies do not always prevent viruses from getting into the body, they just prevent viruses from getting out of control. Since the memory B-cells take 1-2 days to ramp up antibody production, the virus will have a 1-2 day head start to begin to infect cells and reproduce. However, in those first 1-2 days of infection, there are not too many viruses in the body and so a person usually has no symptoms early on (this is the incubation period). Thus neither natural nor vaccination immunity necessarily prevents viruses from getting into the body, they primarily prevent the infection from becoming severe and hopefully prevent you from dying of the infection. In this sense, a viral infection is similar to a mouse infestation in your house – mouse traps in your kitchen can stop the mice from reproducing and eating all of the food in your house but they won’t prevent the mice from getting into the house in the first place.

Because antibodies do not usually prevent viruses from getting into the body and starting to initially reproduce, people with either natural or vaccination immunity can still be contagious to others in those first few days after a virus gets into their body, even though they have no symptoms. The good news is that the number of viruses in the air that they exhale is low and the lower the number of viruses in the air, the less likely it is that someone else breathing that air will become infected.

When a person is infected with COVID, B-lymphocytes in the airways are stimulated to produce anti-COVID IgA antibodies that is released into the airway mucus. Once the COVID virus gets into the bloodstream, blood B-lymphocytes are stimulated to make anti-COVID IgA, IgM and IgG antibodies that are released into the blood. These antibodies recognize different molecules on the surface of the virus and because there are lots of different surface molecules, there are lots of different types of IgA, IgM, and IgG antibodies produced. In other words, COVID-19 infection results in many different types of IgG antibodies. This is different than vaccination immunity.

When a person is vaccinated against COVID, the vaccine is injected into the muscles and then the vaccine gets into the bloodstream. As a result, most of the B-lymphocytes that get stimulated are bloodstream lymphocytes and not airway lymphocytes. These are the lymphocytes are mainly responsible for producing IgM and IgG. B-lymphocytes in the blood also produce some IgA that stays in the blood but since the airway B-lymphocytes are not stimulated, very little airway mucus IgA gets made. Vaccination immunity to COVID also differs from natural immunity because of the types of IgG that are produced. The original Anti-COVID vaccines only produce antibodies against one part of the “spike protein” which is a the molecule on the surface of the virus that the virus uses to attach to cells. If the virus mutates and the spike protein molecule changes shape (as happened with the Omicron variant), then the antibodies produced from vaccination immunity may not recognize this new shape and may be less effective. The new booster COVID vaccines are bivalent and produce antibodies against a part of the spike protein on the original COVID virus and also against a part of the spike protein on the newer Omicron variant.

Natural COVID immunity

Natural immunity to COVID refers to immunity caused by previous infection by COVID. Some people (for example, quarterback Aaron Rodgers) falsely claim “natural immunity” from homeopathic treatments but this is NOT natural immunity. The only ways to develop immunity to COVID is to either have previously been infected by COVID or be vaccinated against it. Because of the different ways that natural immunity and vaccination immunity affect the body’s immune system, both forms of immunity have advantages and disadvantages.

Advantages of natural immunity:

1. Bloodstream IgG production. Human B-lymphocytes have been making IgG in response to infection by various viruses for hundreds of thousands of years and our B-lymphocytes have gotten very good at it.
2. More types of IgG antibodies. Because infection with COVID results in many different types of antibodies against many different parts of the surface molecules of the virus, there is a better chance that some of those antibodies will still work against the virus if a new variant arises with a different shape to just one of the surface molecules. A January 2022 study in the MMWR found that prior to the emergence of the Delta variant, people who were vaccinated were less likely to become infected than people who had previously had a COVID infection but after Delta emerged, those with a previous COVID infection were better protected against future infection than those who were vaccinated. Similarly, a study published two months ago found that previously vaccinated people were 13-times more likely to have a breakthrough infection with the Delta variant than previously infected but unvaccinated people.
3. More mucosal IgA antibodies. Because the COVID virus first stimulates airway B-lymphocytes, those lymphocytes can “learn” to make anti-COVID IgA that gets into the mucus of the nose and airways. Since mucus IgA is the first line of defense, if a person gets re-infected with COVID at a later time, that mucosal IgA can kill off the viruses before they can get into the bloodstream.

Disadvantages of natural immunity:

1. Lower levels of IgG antibodies. Our immune systems are like muscles, they work best when they continue to train. The more you repstimulate the humoral immune system, the stronger it gets. A COVID-19 infection results in a one-time stimulation to the immune system and this can result in lower antibody levels than in a person whose immune system is stimulated by 2 doses of a vaccine followed by booster doses. Some people produce little or no antibodies after infection. A study from September 2021 found that only 64% of people with severe COVID infections causing ARDS had detectable IgG or IgA antibodies after they recovered from infection.
2. You only get natural immunity if you survive the infection. More than 1 million Americans have died of COVID infection. These people’s immune systems never got a chance to make antibodies for long-term protection. Even for those who survived the initial infection, the results of the infection are usually feeling really, really bad for a few days and often having long-term loss of taste and smell. Furthermore, long-COVID symptoms occur in one out of every five people infected. Thus, the cost of natural infection is very high.

Vaccination immunity

Because of the different way that COVID infection and COVID vaccination affect the immune system, there are different advantages and disadvantages with vaccination immunity.

Advantages of vaccination immunity:

1. Bloodstream IgG production. All vaccines work by teaching the body’s immune system to make antibodies and the COVID vaccines are no different.
2. High levels of IgG antibodies. The initial vaccination consists of 2 dose of the vaccine, given 3 weeks apart. This results in the humoral immune system being stimulated twice, as opposed to actual infection with COVID which only stimulates the immune system once. Getting booster vaccinations results in a third, fourth, and fifth time that the immune system gets stimulated. This “trains” the immune system to get very good at producing anti-COVID antibodies. A study from July 2022 found that antibody levels after mRNA vaccine administration were higher and lasted longer than antibody levels after COVID infection.
3. Better protection if variants do not occur. A study from August 2021 found that prior to the emergence of the Delta variant, people who had been infected with COVID but not vaccinated (natural immunity) were 2.3-times more likely to become reinfected than people who were vaccinated but never previously infected (vaccination immunity).
4. You don’t have to get sick to become immune. Although it is true that COVID vaccines can cause side effects, scientific studies as well as my own personal experience show that the side effects of vaccination are way, way, way less than the symptoms of a COVID infection. I have now had 5 different COVID vaccinations and I would take the side effects of all of them combined over even a mild case of COVID infection any day.
5. The vaccines won’t kill you. The vaccines are safe. A study of 11 million people vaccinated with the Pfizer or Moderna vaccines found that there was no increased risk of mortality by getting vaccinated. On the other hand, about one out of every 100 people who get a COVID infection die from the infection. Even those people who survive the initial COVID infection are 233% more likely to die in the year after infection than people who do not get infected based on a study published last December. To put the mortality numbers in perspective, you are 3 million times more likely to die from a COVID infection than to have a winning Powerball ticket.
6. Vaccination after a COVID infection improves immunity. A study from July 2022 found that the effectiveness of infection was 46%, the effectiveness of three doses of a vaccine was 52% but the effectiveness of infection plus three doses of a vaccine was 77%. This is sometimes called “hybrid immunity”.

Disadvantages of vaccination immunity:

1. Single type of IgG antibody. Since the original vaccines resulted in IgG against a specific part of the COVID spike protein, if there is a change in that protein, then the antibodies may not work as well. This was a particular problem with the Omicron variant that caused infection in many people who had been vaccinated earlier. However, even though the vaccines do not work as well if the virus mutates, they do still work and as a result, vaccinated people who get a COVID infection will have milder cases of the infection than unvaccinated people. The newer booster vaccines are bivalent and result in production of two types of antibodies which improves the effectiveness against variants.
2. Lower mucosal IgA levels. Because the airway B-lymphocytes are not strongly stimulated by vaccination, there is lower anti-COVID IgA in the mucus of vaccinated persons compared to those who have previously had a COVID infection. Thus vaccinated persons may not have as strong of a first-line defense against infection. A study from 2021 found that vaccination causes high levels of IgA and IgG in the bloodstream but little to no IgA in the saliva. A study from July 2022 found that infection with the Omicron variant of COVID resulted in 10-times more IgA in respiratory secretions (bronchoalveolar lavage fluid) than vaccination. A second study from October 2022 also found that people previously infected with COVID had higher mucosal IgA levels than vaccinated but not previously infected people.

What does all of this mean?

So, is natural immunity better than vaccination immunity? Well, it depends… We can draw several conclusions from all of the above findings:

• If variants do not emerge, vaccination immunity is better than natural immunity.
• The more boosters a person gets, the better their protection.
• If variants emerge, natural immunity may be stronger than vaccination immunity until new vaccines are developed against those variants.
• Natural immunity plus vaccination immunity (hybrid immunity) gives the strongest protection.
• Although early studies are promising, it is too early to tell if the new boosters that cover Omicron will be better than natural immunity.

For employers trying to decide about whether to mandate vaccination for employees, it is hard to defend a position that vaccination is superior to natural immunity in every case. For example, a person who received 2 shots of the original mRNA vaccines in 2021 may have less immunity than a person who survived an Omicron infection in 2022. Instead of vaccination mandates, a better approach would be immunity mandates by having employees either provide documentation of vaccination or documentation of past infection. However, Americans as a society dislike mandates of any kind and so rather than mandates, it may be better to link immunity documentation to health insurance premium prices, life insurance premium prices, or other employment fringe benefits.

My recommendation is that everyone should get vaccinated and then get as many boosters as you can, including the newest booster that covers Omicron. In theory, immunity from these new boosters should be better than having natural immunity alone. If you have previously had a COVID infection (and are still alive), then get vaccinated and also get the new booster… you can relax with the knowledge that you will then probably have the best immunity against COVID on the planet. We have come to a point in the pandemic where having no immunity (neither natural nor vaccination immunity) is socially irresponsible and only prolongs the pandemic for the rest of us.

October 20, 2022

The NFL has a hall of fame in Canton. Cooperstown has the baseball hall of fame. There is even a polka hall of fame in Euclid, Ohio. It is time to create a memorial to prominent figures in public health but instead of a hall of fame, I propose we create a hall of shame to recognize people whose actions have promoted disease, injuries, and death. Here are 10 people worthy of induction into the Public Health Hall of Shame, listed in chronological order.

1. Christopher Columbus

Unlike many of of the Hall of Shame nominees, Christopher Columbus did not knowingly promote the spread of disease but his inadvertent actions make him worthy of inclusion. He was the first worldwide disease importer/exporter. On October 12, 1492, Columbus arrived in the Bahamas bringing to the newly discovered lands European diseases. When he returned to Spain on March 15, 1493, he brought gifts from the New World. One of those gifts carried by crew members was syphilis that then spread to Spanish soldiers. Two years later, in 1495, Pope Innocent VIII invited King Charles of France to wage war against the King of Naples in Italy. Spanish mercenaries employed by the French army brought syphilis with them to Naples and within a few years, syphilis had spread throughout Europe. Because of the association with the French army, syphilis became known as the “French disease” but it was really the Spanish sailors who brought it back with them from the Americas. Recently, historians have proposed that syphilis occurred sporadically in Europe before Columbus sailed but given the correlation with the Naples war, it seems likely that his crew carried the infection on their return to Spain thus fostering its European spread in the 16th century. For his contribution to the spread of syphilis to Europe (even though inadvertently), Christopher Columbus is nominated to the Hall of Shame.

2. Hernán Cortés

Another Spaniard who warrants inclusion in our Hall of Shame was the conquistador, Hernán Cortés. He was from a lesser nobility family in Spain but chose to come to the New World to seek gold and silver rather than live the life of a nobleman in Europe. In February 1519, he sailed from Cuba to Mexico in order to conquer the Aztecs and loot their empire. His force of 1,000 men was no match for the 200,000 residents in the Aztec capital of Tenochtitlan in Central Mexico. But Cortés had a secret weapon… smallpox. One of Cortés’ soldiers had become infected with smallpox before leaving Cuba. The Aztecs and other Native Americans had no immunity to smallpox because it had not existed in the Americas until it was brought by the early European explorers. 70 days after Cortés first arrived in Mexico, 40% of the population of Tenochtitlan was dead from smallpox. Within a few years, between 5-7 million Aztecs and other indigenous Mexicans died from smallpox. Cortés proved that infectious diseases are more powerful in battle than swords and cannon. In all, it is suspected that infectious diseases brought by European explorers resulted in the death of up to 95% of the native population of the Americas. For his actions resulting in the deaths of millions of Native Mexicans due to smallpox, Hernán Cortés is nominated to the Hall of Shame.

Honorable mention: Colonel Henry Bouquet. In June 1763, Bouquet was the commanding officer at Fort Pitt during Potomac’s War. When the fort was under siege by members of the Delaware Tribe, Bouquet needed help to defeat the Native Americans. So, he ordered his men to distribute smallpox-infested blankets to the besieging warriors in an attempt to infect them and reduce their forces. More than 100 Native Americans died from the resultant smallpox outbreak. Bouquet can be considered the father of germ warfare.

3. Anthony Comstock

In 1873, U.S. postal inspector Anthony Comstock formed the New York Society for the Suppression of Vice. Later that year, he lobbied the U.S. Congress to pass what became known as the Comstock Act that prohibited the postal service from delivering obscene material. As a result, more than 15 tons of books that Comstock determined were obscene were destroyed. These included anatomy books used by medical schools because those books included drawings of reproductive organs. Another provision of the Comstock Act was to prohibit the production of or publication of information about methods of contraception or prevention of venereal disease. Comstock was convinced that by making condoms illegal that Americans would stop having sex outside of marriage. He was oblivious to the fact that the drive to have sex is the most powerful drive in all species of living organisms on planet Earth. He zealously prosecuted and imprisoned anyone who defied his definition of morality, including Julius Schmidt, the inventor of the rubber condom. After release from prison, Schmidt resumed condom manufacturing in a clandestine production facility in New York City. During World War I, being unable to legally sell his condoms to the U.S. Army because of the Comstock Act, Schmidt turned to other allied governments that enthusiastically purchased and distributed condoms to their servicemen. As a result, unlike other Allied armies, at any given time, approximately 15% of the U.S. military force in Europe was actively infected with a venereal disease. Eventually, the U.S. government relented and the production and distribution of condoms became legal but not before Comstock’s efforts had resulted in tens of thousands of cases of syphilis and gonorrhea that could otherwise have been prevented. For his efforts to promote the spread of sexually transmitted disease, Anthony Comstock is deserving of induction into the Hall of Shame.

4. Mary Mallon

From 1900 to 1907, Mary Mallon worked for eight wealthy New York families as a cook. At each household where she worked, household members developed typhoid fever. When a public health investigator determined that Ms. Mallon was the common link in the series of typhoid outbreaks, he went to interview her. But when he asked her to provide samples to test, she attacked him with a fork. She was sentenced by the Health Department to quarantine at North Brother Island from 1907 – 1910. She was released from quarantine under the condition that she never resume work as a cook again. However, she went back to cooking for families, restaurants, and hospitals under a false name. Everywhere she went, she left a trail of typhoid cases. In 1915, when 25 inpatients developed typhoid at a hospital where she worked as a cook, she was again sentenced to quarantine at North Brother island where she lived for 23 years. For her efforts to spread typhoid fever as an asymptomatic carrier, she earned the name “Typhoid Mary” and warrants induction into the Hall of Shame.

5. Emma Marie Harrington

Also known as E.C. Harrington, she was an attorney and the first woman registered to vote in San Francisco. She was a champion of progressive issues in California in the early 1900’s. However, she became famous for her actions that today would make her the darling of political conservatives. In March 1918, an army cook at Camp Funston in Kansas became sick with a respiratory infection. Within days, 522 soldiers became ill. Because the U.S. had entered World War I, troops from Camp Funston were sent to Europe to fight. By April, the H1N1 strain of influenza had spread throughout the world. Within 2 years, one-third of the world’s population had become infected. The number of deaths were estimated to be as high as 100 million making it the second most deadly pandemic after the 14th century bubonic plague. Because there were no vaccines or anti-viral medications at that time, the only defense against influenza was to avoid getting it in the first place. The two public health measures that were found to reduce the spread of the infection were face masks and banning mass gatherings. But some Americans considered face mask mandates to be an affront to personal liberty. Many of them organized to oppose face masks which they called “muzzles”. One of these organizations was the San Francisco Anti-Mask League and E. C. Harrington was its president. During the fall of 1918 and early winter of 1919, more than 3,000 San Francisco residents had died from influenza and the death rate per 100,000 was one of the highest in the world. Despite magnitude of deaths, the Anti-Mask League put enormous political pressure on the city government to lift its mask ban. On January 27, 1919, Mrs. Harrington submitted a petition to the city’s Board of Supervisors to repeal the mask ordinance and 5 days later, on February 1, 1919, San Francisco lifted its mask requirement. For helping to promote influenza deaths in 1919 and for later inspiring thousands of anti-maskers during the COVID-19 pandemic, E. C. Harrington deserves nomination into the Hall of Shame.

6. John W. Hill

America’s economic fortunes were built on tobacco. When anticipated riches from early settlements such as Jamestown failed to materialize, the settlers turned to growing tobacco for export to Europe. Demand for tobacco was enormous and soon farms and plantations across the colonies were making their fortunes by growing tobacco. The invention of a machine for large scale manufacturing of cigarettes in 1880 revolutionized the U.S. tobacco industry. After the turn of the century, per capita cigarette consumption increased exponentially. But by 1950, there were increasing reports that tobacco smoke could be harmful to people’s health. The CEOs of the largest cigarette makers – American Tobacco Co., R. J. Reynolds, Philip Morris, Benson & Hedges, U.S. Tobacco Co. and Brown & Williamson, were worried that sales would suffer so they turned to John W. Hill, the founder of Hill & Knowlton, one of the top public relations firms in the country. In 1953, Hill devised a PR campaign to discredit the mounting scientific data and named it “Operation White Coats”. The plan was to employ physicians and scientists (who wore white coats) to downplay the health hazards of cigarette smoke. Operation White Coats was the genesis of the Tobacco Research Council that provided easy-to-obtain grants to prominent medical researchers for studies that showed health benefits of nicotine and other tobacco components. Hill’s cigarette marketing strategy was successful and by 1965, 45% of U.S. adults were daily smokers. In reality many people have contributed to the the misinformation campaigns of American tobacco companies but John W. Hill stands out as of the most effective in denying that smoking cigarettes causes lung cancer, COPD, and other diseases. His has been a legacy of death and even today, smoking accounts for 480,000 deaths per year in the U.S., or about 1 out of every 5 deaths. For his contribution to to the death of millions of Americans since his 1953 advertising campaign, John W. Hill is our 6th nominee to the Hall of Shame.

Honorable Mention: Carrie Nation. She was the public face of the Women’s Christian Temperance Union which was the primary driver of the prohibition movement that led to passing the 18th Amendment to the U.S. Constitution outlawing the sale of alcohol on January 16, 1919. She claimed to have a divine vision from God commanding her to destroy bars and saloons. She traveled across the United States with a hatchet that she would use to smash saloon fixtures and liquor bottles. She described herself as “a bulldog running along at the feet of Jesus, barking at what He doesn’t like”. Overall, prohibition did reduce U.S. alcohol consumption by about 30% but instead of drinking low-alcohol percentage beer, people just started drinking bootlegged liquors. These were produced in unregulated stills and were frequently contaminated with methanol. Sellars of illegal spirits would often water them down and then add various poisonous chemicals to mimic the taste and color of liquors. During prohibition, over 1,000 people per year died from consuming tainted liquor. Within 15 years, it became apparent that prohibition did not stop people from drinking, it only created a market for poisonous moonshine. In 1933, the 21st Amendment repealed prohibition.

7. Peter Duesberg, PhD

In the early 1980’s, gay men were dying from an immunodeficiency syndrome and no one knew why. In 1983, the cause was identified simultaneously by French virologist Luc Montagnier and American virologist Robert Gallo. It was a virus that became known as HIV, or human immunodeficiency virus. Soon after, a lab test was created to diagnose the infection followed by development of AZT, a life-saving anti-viral drug that could treat AIDS. These milestones should have been celebrated by the medical and scientific community as breakthroughs in conquering AIDS. But history has proven that for every disease, there is a disease denialist and for AIDS, the most prominent denialist was Peter Duesberg. He is a Professor of Molecular Biology at the University of California, Berkley who built a successful academic career on his discovery of genes that could cause cancer. He argued that HIV was a harmless virus and that the cause of AIDS was long-term consumption of recreational drugs and anti-viral drugs. Because of his academic credentials, he developed a following of AIDS denialists in the 1990’s. Around the globe, people continued to die of AIDS and by 2000, about 25% of all deaths in South Africa were due to AIDS. Thabo Mbeki, the president of South Africa, convened an AIDS advisory committee to help direct public policy. The committee included Peter Duesberg. Mbeki bought into Duesberg’s AIDS denialism and withheld the use of anti-retroviral drugs in his country. As a result, it is estimated that there were 330,000 preventable deaths from AIDS in South Africa. Duesberg has kept up his claims that HIV does not cause AIDS and as recently as 2012 said on the Joe Rogan podcast that HIV is “one of the most harmless type of viruses we know”. For his actions that contributed to one-third of a million AIDS deaths in South Africa and his inspiration for AIDS denialists everywhere, Peter Duesberg should be nominated for the Public Health Hall of Shame

Honorable Mention: Christine Maggiore. She was diagnosed with HIV in 1992 and became involved in AIDS activism. In 1994, she met Peter Duesberg who convinced her that HIV does not cause AIDS. She came to believe that her own positive HIV test was actually due to an influenza vaccination. She authored a book entitled What If Everything You Thought You Knew about AIDS Was Wrong? and became prominent in the AIDS denialist community. She founded an organization that urged HIV-positive pregnant women to avoid anti-HIV medication. Ironically, she went on to become pregnant herself and refused to take HIV medications. She give birth to a daughter, Eliza Jane, and refused to allow her infant daughter to be tested for HIV. Eliza Jane died of AIDS at age 3 and Christine Maggiore died of AIDS three years later.

8. Jay Dickey

Most of our Hall of Shame nominees are proposed because of their actions that resulted in the proliferation of disease. Although bullets are not a disease, guns have proliferated in the United States just like contagious pathogens. Each year, more than 45,000 Americans die from gunshots and twice that number suffer non-fatal gun injuries. One of the barriers to reducing firearm deaths over the past 25 years has been a law prohibiting research into firearm-related deaths and injuries. The architect of that law was U.S. Representative James Dickey of Arkansas who at the behest of the National Rifle Association, added a clause to the 1996 Omnibus bill that became known as the Dickey Amendment. The amendment stated that “…none of the funds made available for injury prevention and control at the Centers for Disease Control may be used to advocate or promote gun control.” It effectively stopped all research by the CDC into gun-related deaths and injuries. It was not until 2018 that Congress passed a law allowing the CDC to report data on firearm injuries and not until 2020 that Congress allowed funding for firearm injury research by the CDC. By prohibiting the CDC to study gun injuries for 22 years, there was no good data on which to base public policy to reduce firearm injuries and hundreds of thousands of Americans died from guns. Later in his life, Dickey reversed his opinion about gun violence research but he nevertheless deserves inclusion in the Hall of Shame.

Honorable mention: Wayne LaPierre. Mr. LaPierre has been the executive vice president and chief executive of the National Rifle Association since 1991. It was he who was the principal lobbyist who influenced Dickey to add the NRAs amendment to the Omnibus bill in 1996. LaPierre has continued to lobby for the proliferation of guns in the United States. Because of his efforts, the U.S. is now the only country in the world with more guns than people.

9. Andrew Wakefield, MD

As the son of two physicians, it was no surprise that Andrew Wakefield went to medical school at St. Mary’s Medical School in London. He went on to do research in liver and small intestine transplantation and became a member of the Royal College of Surgeons. He developed a hypothesis that the measles virus might be the cause of Crohn’s disease. This evolved into a hypothesis that the measles vaccine might cause Crohn’s disease. Both of these hypotheses were disproven. But Wakefield was undeterred in his quest to link the measles vaccine to some disease. So, he turned to autism and in 1998, he published a paper in The Lancet in which he concluded that 12 children with autism developed “autistic enterocolitis” from the MMR vaccine (measles, mumps, rubella vaccine). He then called for a suspension of childhood vaccination with MMR in a press conference at his hospital. In 2000, he repeated his claims on the CBS news show, 60 Minutes, introducing his theory to American vaccine conspiracy theorists. In 2004, the British public service network Channel 4 reported that before he published his 1998 article about the MMR vaccine, Wakefield submitted a patent for a rival measles vaccine that he said would not cause autism. Presumably, if his vaccine replaced the MMR vaccine worldwide, he would stand to profit enormously. He also started a company to make diagnostic test kits for “autistic enterocolitis” that he predicted would make him $43 million per year. In 2009, his original research was found to be fraudulent and in 2010, The Lancet retracted his 1998 article. Three months later, his medical license was revoked. Dr. Andrew Wakefield’s false claims about the MMR vaccine were the inspiration for other anti-vaxxers. This not only led to thousands of children not receiving appropriate vaccinations but also laid the groundwork for false claims about the COVID-19 vaccines. For his efforts to increase childhood infections, Andrew Wakefield should be included in the Hall of Shame.

Honorable Mention: Robert F. Kennedy, Jr. The son of the late Senator Robert F. (Bobby) Kennedy is an environmental lawyer who makes a living as an anti-vaxxer. Since 2005, he has promoted Andrew Wakefield’s discredited idea that vaccines cause autism. When 2 Samoan infants died in 2018, he opined that the cause of their death was the MMR vaccine. It was later determined that the infants had been errantly injected with a muscle relaxant along with the vaccine and the muscle relaxant was the cause of death. Nevertheless, his views caused many Samoans to forgo the MMR vaccine in their children. As a consequence, in 2019, a measles outbreak resulted in 5,700 infections or 3% of the Samoan population; 83 Samoans died from measles infections. Kennedy became convinced that the preservative thimerosal in vaccines could cause neurological disorders such as autism in children and spread anti-vaccine misinformation. As a result, thousands of pregnant women refused influenza vaccination and thousands of parents refused to allow their children to get flu shots resulting in countless influenza infections and deaths. Many studies have shown that thimerosal in vaccines is safe. He has been a tireless conspiracy theorist and suggested that Anthony Fauci and Bill Gates conspired to prolong the COVID pandemic for financial gain. He promoted the use of ivermectin to treat COVID, despite studies showing that the anti-parasite drug had no effect on COVID infection. Other members of the Kennedy family issued a joint statement about his efforts and said: “…on vaccines he is wrong. And his and others’ work against vaccines is having heartbreaking consequences.”

10. Joseph Mercola, DO

The last of our nominations is for efforts to promote the spread of COVID-19. Dr. Joseph Mercola is an American alternative medicine proponent with a lucrative internet business selling dietary supplements. He stopped seeing patients in 2009 to devote his attention to his internet business and has stated that his net worth is in excess of $100 million. Following in Andrew Wakefield’s shoes, he has been a staunch vaccine critic. It was during the COVID-19 pandemic that Dr. Mercola really hit his stride by promoting unproven supplements (that he sold) as treatments for COVID. He also advocated using inhaled hydrogen peroxide to prevent or cure COVID. An article in the New York Times identified him as the single most influential spreader of COVID misinformation. Becker’s Hospital Review reported that a “Disinformation Dozen” individuals were responsible for 65% of all of the misinformation about COVID and number 1 on that list was Joseph Mercola. His actions have contributed to unfounded fears of effective COVID vaccines and even as of today, one-third of the U.S. population is not fully vaccinated. For his contribution to the perpetuation of the COVID pandemic that has so far killed more than 1 million Americans, Dr. Joseph Mercola is our 10th nominee for induction into the Hall of Shame.

Honorable Mention: Sherri Tenpenny, DO. Occupying the 4th rank in the COVID “Disinformation Dozen” is Ohio’s own Dr. Sherri Tenpenny. She is an anti-vaccine activist who supports the claim that vaccines cause autism. She has written 4 books claiming dangers of vaccines and has stated that COVID vaccines cause death, autoimmune disease, and infertility. She sells these books along with videos and dietary supplements on her website. She stated that COVID-19 vaccines will turn people into “transhumanist cyborgs” and that “by the end of 2022, every fully vaccinated person over the age of 30 may have the equivalent of full-blown vaccine-induced immune suppressed AIDS”. She claims that wearing face masks makes people unhealthy by suppressing their immune systems. In June 2021, she was called by Ohio Republican legislators to testify at the Ohio Statehouse against vaccine mandates. She testified that the COVID vaccines cause people to become magnetized and meanwhile her minions posted on-line videos of spoons stuck to their noses to try to prove her point. Dr. Tenpenny’s claims about magnetism proved to be too far-fetched even for Ohio’s conservative State Representatives and the bill to ban childhood vaccine requirements died in committee.

History is replete with people who have helped to spread disease. Some, like Columbus, did it unknowingly. Some, like Bouquet, did it purposefully. Some, like Comstock, did it in defiance of human nature. Some, like Hill, did it by spreading misinformation. Others, like Mercola, did it in order to make a profit. But whether their actions were intended or unintended, each of our nominees for induction in the  Public Health Hall of Shame helped to promote disease, death, or injury by their actions. The bitter news for the medical profession is that as long as we have people like these 10 inductees, doctors and morticians will never go out of business.

August 9, 2022

Who lives longer, Republicans or Democrats? The answer may surprise you. Many people hold the stereotype of Republicans being wealthy, being better educated, and having better access to healthcare. Democrats often hold the stereotype of being working class, poor, and wanting government healthcare handouts. Intuitively, this would translate to Republicans being healthier and living longer than Democrats.

 

Historically, Republicans were found to be healthier than Democrats. In a 2009 article from the International Journal of Epidemiology, investigators analyzed data from the 1972 – 2006 General Social Surveys and found that survey respondents who identified as Republican had better self-reported health and were less likely than Democrats to be smokers. Similarly, a 2015 article from the journal Political Research Quarterly found that people who identified as having good health were more likely to vote Republican in the preceding presidential election.

A more recent study in the May 2022 edition of the British Medical Journal found that the association of political party with health may be reversing. This study compared the voting patterns of individual U.S. counties in the 5 presidential elections between 2000 to 2019 with the changes in the mortality rates in each of those counties during the same time period. The results indicated that counties voting Democratic had greater improvements in mortality rates than counties voting Republican. Moreover, the separation between improved mortality rates and political party voting only became apparent after 2008. This suggests that there has been a change over the past 15 years with Democrats now becoming the healthier of the two political parties.

It turns out that determining how political party affiliation affects life expectancy and other health metrics is quite difficult. Nowhere on a death certificate is there an entry for the doctor to  record political party. Because our voting choices are confidential, there is no way to do a public record search for how dead Americans voted in the past Therefore, the only way to study political party affiliation and health outcomes is by correlation studies that look at voting patterns and health metrics of different geographic locations.

The Cook Partisan Voting Index

In 1997, a new method of determining political affiliation was developed called the Cook Partisan Voting Index. For the past 25 years, the index has been used to determine how strongly a congressional district or a state leans toward the Republican party or the Democratic Party. The index is based on voting patterns in the previous two presidential elections. The most recent data is based on voting in the 2016 and 2020 elections. The higher the number, the more strongly a state leans towards one political party.

In this table, Democratic-leaning states are in blue and are denoted with negative numbers; the more negative the number, the more the state leans Democratic. Republican-leaning states are in red and denoted with positive numbers; the higher the number, the more the state leans Republican. The most strongly Republican state is Wyoming and the most strongly Democratic states are Vermont and Hawaii. Two states (Nevada and New Hampshire) are equally split between Republican and Democratic parties and they are denoted in purple. The use of negative numbers for Democratic states and positive numbers for Republican states in this table is purely to facilitate statistical comparisons.

The Cook Partisan Index also reports the political leaning by individual congressional district. The most Democratic district is California’s 12th (Oakland area) and the most Republican district is Alabama’s 4th (rural northern Alabama).

Party affiliation and life expectancy

If we use the Cook Partisan Voting Index as a marker for party affiliation, then we can compare states with a high Republican index to states with a high Democratic index and see how those voting patterns correlate with health metrics. Life expectancy is one of the simplest of these metrics. Life expectancy can be measured in several ways. The most common measurements are (1) life expectancy from birth, (2) life expectancy from age 18, and (3) life expectancy from age 65. Each of these measurements has advantages and disadvantages.

Life expectancy from birth will be lower if there is a high infant and childhood mortality rate. Life expectancy from age 18 eliminates infant mortality but will be affected by gun-related deaths, drug overdoses, and motor vehicle deaths that are more common in young adults. Life expectancy from age 65 eliminates those young adulthood causes of death and is more affected by life-long unhealthy habits such as smoking, obesity, and alcohol abuse. For this analysis, let’s use life expectancy from birth since it incorporates all of the variables that can affect mortality from infancy through early adulthood and into older age.

In comparing the Cook Partisan Voting Index to life expectancy from birth, many people would suspect that Republicans would have a longer life expectancy than Democrats. However, just the opposite is true. People living in Democratic party states live longer than those in Republican party states. States that most strongly leaned Democrat had the longest life expectancy.

Overall, life expectancy in states found to be Democratic by the Cook Partisan Voting Index had a mean life expectancy of 79.6 years whereas the mean life expectancy in Republican states was 77.4 years (p < 0.001). This represents an average 2.2 year longer life expectancy in Democrat-leaning states.

Party affiliation and smoking

The finding of longer life expectancy in states that lean Democratic indicates that there has been a change in political party affiliation and health measures compared to older studies that showed Republicans were generally healthier than Democrats. One of the strongest predictors of life expectancy is smoking. In the past, Republicans were less likely to be smokers than Democrats. Could a change in the prevalence of smoking among people voting Republican versus Democrat be partially responsible for the change in life expectancy?

To answer this question, let’s examine the association between the Cook Partisan Voting Index and smoking rates by state. Each year, the Centers for Disease Control reports the percentage of adults in each state who smoke. Overall, the percentage of all Americans who smoke has been steadily falling since the mid-1960’s.

However, there are wide differences in smoking patterns between different states, ranging from a low of 7.9% of adults smoking in Utah to a high of 23.8% of adults smoking in West Virginia. Overall, states that lean Republican have a higher prevalence of smoking than states that lean Democratic (r = 0.64). The average adult smoking rate was 13.7% in Democrat states and 17.8% in Republican states (p < 0.001).

Party affiliation and obesity

A second health demographic that has changed over the past several decades is obesity. Overall, Americans have been becoming more obese each year. The CDC reports that the rate of obesity (BMI > 30) has increased from 30.5% in 2000 to 42.4% in 2018. Similarly, the rate of severe obesity (BMI > 40) has increased from 4.7% to 9.2%. These statistics are from the National Health and Nutrition Survey (NHANES) which is based face-to-face surveys performed in participating American’s homes by a physician and other health professionals.

As with smoking, there are substantial differences in the rate of obesity among different states. The Behavioral Risk Factor Surveillance System (BRFSS) reports obesity rates by state based on adult self-reported information from phone surveys. These self-reported obesity data differ from the NHANES data with a lower overall incidence of obesity than NHANES. This difference has been attributed to differences in how the data are obtained (in-person interview versus phone survey). The state with the highest rate of obesity is West Virginia and the state with the lowest rate of obesity is Colorado. Based on the BRFSS data, states that lean Democratic have an adult obesity prevalence of 29.1% and states that lean Republican have an adult obesity prevalence of 34.3% (p < 0.001)

Party affiliation and COVID mortality

One of the major causes of death in the United States in the past two years has been COVID-19. So far, 1,024,611 Americans are known to have died from COVID and many more have likely died from COVID or COVID complications that were not listed on death certificates. A study published last month in JAMA Internal Medicine found that in 2021, COVID was the 4th leading cause of death in Americans age 25-34 (after accidents, suicide, and assault), the number 1 cause of death in Americans age 45-54, and the 3rd leading cause of death in Americans over age 65 (after cancer and heart disease).

As noted in a previous post, there are significant differences in how Republicans and Democrats fared during the COVID-19 pandemic with residents in Democratic states more likely to be vaccinated against COVID, less likely to become infected with COVID, and less likely to die from COVID than residents in Republican states. By comparing the Cook Partisan Voting Index to the death rate of COVID for each state, we again find that the  there is an association between party affiliation and death from COVID. Overall, 260 people per 100,000 population have died from COVID in Democrat-leaning states whereas 331 per 100,000 died from COVID in Republican-leaning states (p = 0.005).

Party affiliation and personal income

As noted earlier, historically Republicans had a higher self-reported annual income than Democrats. The stereotypical Republican was a capitalism-supporting business owner and the stereotypical Democrat was a blue collar worker who belonged to a union. Personal income has been shown to affect health outcomes with wealthier persons having better health and poorer persons having worse health. Could a change in income demographics between Republicans and Democrats be partially responsible of the shorter life expectancy of residents of Republican states?

By comparing household income to the Cook Partisan Voting Index, we find that residents of states leaning Democratic have a higher annual income than residents of states leaning Republican. The average income in Democratic-leaning sates was $71,264 and the average come in Republican-leaning states was $59,108 (p < 0.001).

Money is only worth what you can buy with it. The highest income states are also the states with the highest cost of living so the above analysis man not necessarily equate to the purchasing power of each household. Nevertheless, it appears that voters favoring Republicans in the last two presidential elections have a different relative annual income than voters favoring Republicans in previous presidential elections. Residents of states who have recently favored Republicans have a lower income than those favoring Democrats.

Today’s Republicans are not your parent’s Republicans

A generation ago, compared to Democrats, Republicans were wealthier, healthier, and less likely to smoke. Today’s Republicans have a lower income, are more obese, are more likely to smoke, and are more likely to die young than Democrats. This generational reversal in the relationship between party affiliation and health metrics has implications for future healthcare utilization.

For example, given a 2.2 year longer life expectancy, residents of Democrat-leaning states would be expected to utilize 18% more Medicare and Social Security benefits than residents of Republican-leaning states (assuming Medicare and Social Security benefits starting at age 65). The longer a person lives, the more elections that person can vote in. The results imply that people voting Democrat will vote in an average of 2 more annual elections over the course of their lifetimes than those who vote Republican.

Obesity is associated with other health conditions such as diabetes, hypertension, sleep apnea, and arthritis. This could indicate that people voting Republican are more likely to have these conditions in addition to being more likely to be smokers. The result could be a higher incidence of disability among people voting Republican than among people voting Democrat.

It seems paradoxical that people living in states that lean toward the Democratic party have higher incomes and thus are in higher income tax brackets and pay more in income tax than people living in states that lean toward the Republican party. Democrats are often characterized as favoring higher taxes whereas Republicans are generally characterized as favoring tax cuts.

We will not fully know all of the healthcare implications for the apparent change in voter demographics for several years. However, it is likely that the evolving differences in health metrics between states that vote Republican and states that vote Democrat will result in very different approaches to healthcare policy.

August 1, 2022

Sometime next month, the United States will surpass one million reported deaths from COVID-19. So, how did your state compare in combating the pandemic? I graded each state by four measures: (1) total cases per 100,000 population, (2) total deaths per 100,000 population, (3) seroprevalence, and (4) percent of the population fully vaccinated. I then created a composite score using all four metrics to give an overall grade for every state plus Washington DC and Puerto Rico. Grades for each metric from A+ through F were assigned with 4 states getting any given grade.

1. Total cases per 100,000 population. These are the cases reported by state health departments to the CDC as of April 28, 2022. The higher the number, the more documented cases occurred since January 2020 per capita. This number does not reflect the true number of cases since many people test positive with home test kits that are not reported to their health departments and many patients with mild or no symptoms do not get tested.
   • Grade A+ states: Puerto Rico, Oregon, Maryland, Hawaii,
   • Grade F states: Alaska, Rhode Island, North Dakota, Tennessee
2. Total deaths per 100,000 population. These are the deaths reported by state health departments to the CDC as of April 28, 2022. The higher the number, the more deaths occurred since January 2020 per capita. Because the deaths from COVID are only counted if COVID is listed as a cause of death on the death certificate, these numbers are undoubtedly also an underestimate since COVID may not be listed on a death certificate if a person did not have a COVID test before dying or if a person died at home and no information about symptoms was available to the physician signing the death certificate.
   • Grade A+ states:Vermont, Hawaii, Puerto Rico, Utah
   • Grade F states: Mississippi, Arizona, Alabama, Tennessee
3. Seroprevalence. This is from the February Nationwide Antibody Seroprevalence Survey. In this study, left-over blood samples from blood drawn from clinical labs are tested for antibodies against the COVID-19 virus. Notably, the specific antibodies tested for are those generated from actual infection and do not result from vaccination. The higher the number, the greater the percentage of the state’s population has actually had a true COVID-19 infection (of note, there is no recent data for North Dakota; because there was no data for Montana and New Hampshire from the February study, data from the January study was used for these two states). Overall, this study estimates that 57.5% of Americans have had a COVID infection. However, because antibody levels decline over time, many people who have had an infection many months previously will no longer have antibodies. Therefore, these numbers likely underestimate the actual percentage of the population that has had an infection.
   • Grade A+ states: Vermont, New Hampshire, Hawaii, Puerto Rico,
   • Grade F states: Iowa, Texas, Mississippi
4. Percent of the population fully vaccinated. This is the percentage of people in each state that have received at least 2 doses of the Pfizer vaccine, 2 doses of the Moderna vaccine, or 1 dose of the Johnson & Johnson vaccine as reported by the CDC. This percentage reflects the entire population of the state, including young children who are not yet eligible to receive vaccinations and therefore the percentage of adults fully vaccinated will be higher.
   • Grade A+ states: Puerto Rico, Rhode Island, Vermont, Maine
   • Grade F states: Alabama, Wyoming, Mississippi, Louisiana
5. Overall score. For each of the above four metrics, states (plus Washington D.C. and Puerto Rico) were ranked 1 through 52. The overall score was calculated by adding the ranks for each of the four metric and determining the average of those 4 numbers. For North Dakota, there is no data available for the seroprevalence study so the overall score was calculated by the average of the other 3 metrics.
   • Grade A+ states: Puerto Rico, Vermont, Hawaii, Maine
   • Grade F states: Tennessee, Mississippi, Arkansas, Alabama

Here are the scores for each state

Alabama

• Case Rate per 100,000 = 26,524; grade: C-
• Death Rate per 100,000 = 398; grade: F
• Seroprevalence = 66.0%; grade: D
• Percent Fully Vaccinated = 51.1%; grade: F
• Overall Rank = 49; grade: F

Alaska

• Case Rate per 100,000 = 33,479; grade: F
• Death Rate per 100,000 = 166; grade: A
• Seroprevalence = 61.0%; grade: C
• Percent Fully Vaccinated = 62.3%; grade: C+
• Overall Rank = 26; grade: C+

Arizona

• Case Rate per 100,000 = 27,773; grade: D
• Death Rate per 100,000 = 411; grade: F
• Seroprevalence = 63.0%; grade: C-
• Percent Fully Vaccinated = 61.5%; grade: C
• Overall Rank = 48; grade: D-

Arkansas

• Case Rate per 100,000 = 27,683; grade: D
• Death Rate per 100,000 = 377; grade: D-
• Seroprevalence = 64.0%; grade: D+
• Percent Fully Vaccinated = 54.4%; grade: D-
• Overall Rank = 50; grade: F

California

• Case Rate per 100,000 = 23,281; grade: B+
• Death Rate per 100,000 = 226; grade: B+
• Seroprevalence = 55.5%; grade: B
• Percent Fully Vaccinated = 72.0%; grade: B+
• Overall Rank = 12; grade: A-

Colorado

• Case Rate per 100,000 = 23,979; grade: B
• Death Rate per 100,000 = 210; grade: A-
• Seroprevalence = 47.9%; grade: A-
• Percent Fully Vaccinated = 70.2%; grade: B
• Overall Rank = 10; grade: A-

Connecticut

• Case Rate per 100,000 = 21,204; grade: A-
• Death Rate per 100,000 = 303; grade: C+
• Seroprevalence = 44.4%; grade: A
• Percent Fully Vaccinated = 79.2%; grade: A
• Overall Rank = 11; grade: A-

Delaware

• Case Rate per 100,000 = 26,902; grade: D+
• Death Rate per 100,000 = 298; grade: C+
• Seroprevalence = 54.0%; grade: B+
• Percent Fully Vaccinated = 69.1%; grade: B
• Overall Rank = 23; grade: B-

Washington D.C.

• Case Rate per 100,000 = 20,112; grade: A-
• Death Rate per 100,000 = 189; grade: A-
• Seroprevalence = 63.6%; grade: D+
• Percent Fully Vaccinated = 74.1%; grade: A-
• Overall Rank = 13; grade: B+

Florida

• Case Rate per 100,000 = 27,568; grade: D
• Death Rate per 100,000 = 344; grade: C-
• Seroprevalence = 58.4%; grade: B-
• Percent Fully Vaccinated = 66.9%; grade: B-
• Overall Rank = 35; grade: C-

Georgia

• Case Rate per 100,000 = 23,689; grade: B
• Death Rate per 100,000 = 356; grade: D
• Seroprevalence = 63.8%; grade: D+
• Percent Fully Vaccinated = 54.7%; grade: D-
• Overall Rank = 37; grade: D+

Hawaii

• Case Rate per 100,000 = 17,089; grade: A+
• Death Rate per 100,000 = 99; grade: A+
• Seroprevalence = 34.2%; grade: A+
• Percent Fully Vaccinated = 78.2%; grade: A
• Overall Rank = 3; grade: A+

Idaho

• Case Rate per 100,000 = 24,947; grade: C+
• Death Rate per 100,000 = 275; grade: B
• Seroprevalence = 67.8%; grade: D-
• Percent Fully Vaccinated = 54.0%; grade: D-
• Overall Rank = 31; grade: C

Illinois

• Case Rate per 100,000 = 24,686; grade: B-
• Death Rate per 100,000 = 298; grade: B-
• Seroprevalence = 60.8%; grade: C+
• Percent Fully Vaccinated = 68.7%; grade: B-
• Overall Rank = 20; grade: B

Indiana

• Case Rate per 100,000 = 25,263; grade: C+
• Death Rate per 100,000 = 350; grade: D+
• Seroprevalence = 61.2%; grade: C
• Percent Fully Vaccinated = 54.8%; grade: D
• Overall Rank = 39; grade: D+

Iowa

• Case Rate per 100,000 = 24,189; grade: B
• Death Rate per 100,000 = 302; grade: C+
• Seroprevalence = 70.7%; grade: F
• Percent Fully Vaccinated = 61.9%; grade: C+
• Overall Rank = 32; grade: C

Kansas

• Case Rate per 100,000 = 26,561; grade: C-
• Death Rate per 100,000 = 295; grade: B-
• Seroprevalence = 62.2%; grade: C-
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 29; grade: C

Kentucky

• Case Rate per 100,000 = 29706; grade: D-
• Death Rate per 100,000 = 346; grade: C-
• Seroprevalence = 56.6%; grade: B-
• Percent Fully Vaccinated = 57.4%; grade: D+
• Overall Rank = 42; grade: D

Louisiana

• Case Rate per 100,000 = 25,226; grade: C+
• Death Rate per 100,000 = 370; grade: D-
• Seroprevalence = 68.9%; grade: D-
• Percent Fully Vaccinated = 53.5%; grade: F
• Overall Rank = 45; grade: D-

Maine

• Case Rate per 100,000 = 18,124; grade: A
• Death Rate per 100,000 = 169; grade: A
• Seroprevalence = 35.3%; grade: A
• Percent Fully Vaccinated = 79.5%; grade: A+
• Overall Rank = 4; grade: A+

Maryland

• Case Rate per 100,000 = 17,039; grade: A+
• Death Rate per 100,000 = 239; grade: B
• Seroprevalence = 49.9%; grade: A-
• Percent Fully Vaccinated = 75.6%; grade: A-
• Overall Rank = 9; grade: A-

Massachusetts

• Case Rate per 100,000 = 25,387; grade: C
• Death Rate per 100,000 = 293; grade: B
• Seroprevalence = 52.6%; grade: B+
• Percent Fully Vaccinated = 78.9%; grade: A
• Overall Rank = 15; grade: B+

Michigan

• Case Rate per 100,000 = 24,291; grade: B-
• Death Rate per 100,000 = 360; grade: D
• Seroprevalence = 56.9%; grade: B-
• Percent Fully Vaccinated = 60.1%; grade: C-
• Overall Rank = 27; grade: C+

Minnesota

• Case Rate per 100,000 = 25,692; grade: C
• Death Rate per 100,000 = 226; grade: B+
• Seroprevalence = 60.8%; grade: C+
• Percent Fully Vaccinated = 69.1%; grade: B
• Overall Rank = 18; grade: B

Mississippi

• Case Rate per 100,000 = 26,788; grade: D+
• Death Rate per 100,000 = 417; grade: F
• Seroprevalence = 69.4%; grade: F
• Percent Fully Vaccinated = 51.8%; grade: F
• Overall Rank = 51; grade: F

Missouri

• Case Rate per 100,000 = 23,156; grade: B+
• Death Rate per 100,000 = 330; grade: C
• Seroprevalence = 55.7%; grade: B-
• Percent Fully Vaccinated = 56.0%; grade: D
• Overall Rank = 17; grade: B

Montana

• Case Rate per 100,000 = 25,617; grade: C
• Death Rate per 100,000 = 313; grade: C+
• Seroprevalence = 47.5%; grade: A-
• Percent Fully Vaccinated = 56.7%; grade: D+
• Overall Rank = 19; grade: B

Nebraska

• Case Rate per 100,000 = 24,798; grade: B-
• Death Rate per 100,000 = 216; grade: A-
• Seroprevalence = 65.4%; grade: D
• Percent Fully Vaccinated = 63.6%; grade: C+
• Overall Rank = 22; grade: B-

Nevada

• Case Rate per 100,000 = 23,332; grade: B
• Death Rate per 100,000 = 349; grade: D+
• Seroprevalence = 60.1%; grade: C+
• Percent Fully Vaccinated = 60.8%; grade: C-
• Overall Rank = 25; grade: C+

New Hampshire

• Case Rate per 100,000 = 22,740; grade: A-
• Death Rate per 100,000 = 182; grade: A-
• Seroprevalence = 33.1%; grade: A+
• Percent Fully Vaccinated = 70.2%; grade: B+
• Overall Rank = 6; grade: A

New Jersey

• Case Rate per 100,000 = 25,355; grade: C+
• Death Rate per 100,000 = 376; grade: D-
• Seroprevalence = 60.9%; grade: C+
• Percent Fully Vaccinated = 75.6%; grade: A-
• Overall Rank = 33; grade: C-

New Mexico

• Case Rate per 100,000 = 24,886; grade: B-
• Death Rate per 100,000 = 356; grade: D
• Seroprevalence = 49.1%; grade: A-
• Percent Fully Vaccinated = 71.0%; grade: B+
• Overall Rank = 21; grade: B-

New York

• Case Rate per 100,000 = 26,376; grade: C-
• Death Rate per 100,000 = 347; grade: D+
• Seroprevalence = 61.5%; grade: C
• Percent Fully Vaccinated = 76.9%; grade: A
• Overall Rank = 36; grade: C-

North Carolina

• Case Rate per 100,000 = 25,355; grade: C
• Death Rate per 100,000 = 223; grade: B+
• Seroprevalence = 52.0%; grade: B+
• Percent Fully Vaccinated = 61.0%; grade: C-
• Overall Rank = 14; grade: B+

North Dakota

• Case Rate per 100,000 = 31,620; grade: F
• Death Rate per 100,000 = 297; grade: B-
• Seroprevalence data not available
• Percent Fully Vaccinated = 54.9%; grade: D
• Overall Rank = 41; grade: D

Ohio

• Case Rate per 100,000 = 22,999; grade: B+
• Death Rate per 100,000 = 328; grade: C
• Seroprevalence = 63.2%; grade: C-
• Percent Fully Vaccinated = 58.4%; grade: C-
• Overall Rank = 24; grade: B-

Oklahoma

• Case Rate per 100,000 = 26,293; grade: C-
• Death Rate per 100,000 = 360; grade: D
• Seroprevalence = 69.1%; grade: D-
• Percent Fully Vaccinated = 57.2%; grade: D+
• Overall Rank = 47; grade: D-

Oregon

• Case Rate per 100,000 = 17,038; grade: A+
• Death Rate per 100,000 = 177; grade: A
• Seroprevalence = 46.9%; grade: A
• Percent Fully Vaccinated = 69.9%; grade: B
• Overall Rank = 5; grade: A

Pennsylvania

• Case Rate per 100,000 = 21,973; grade: A-
• Death Rate per 100,000 = 348; grade: D+
• Seroprevalence = 54.6%; grade: B
• Percent Fully Vaccinated = 68.4%; grade: B-
• Overall Rank = 16; grade: B+

Puerto Rico

• Case Rate per 100,000 = 16,358; grade: A+
• Death Rate per 100,000 = 131; grade: A+
• Seroprevalence = 34.3%; grade: A+
• Percent Fully Vaccinated = 83.0%; grade: A+
• Overall Rank = 1; grade: A+

Rhode Island

• Case Rate per 100,000 = 33,226; grade: F
• Death Rate per 100,000 = 333; grade: C-
• Seroprevalence = 53.4%; grade: B+
• Percent Fully Vaccinated = 82.5%; grade: A+
• Overall Rank = 30; grade: C

South Carolina

• Case Rate per 100,000 = 28,592; grade: D-
• Death Rate per 100,000 = 344; grade: C-
• Seroprevalence = 64.5%; grade: D+
• Percent Fully Vaccinated = 56.6%; grade: D
• Overall Rank = 46; grade: D-

South Dakota

• Case Rate per 100,000 = 26,882; grade: D+
• Death Rate per 100,000 = 329; grade: C
• Seroprevalence = 61.3%; grade: C
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 38; grade: D+

Tennessee

• Case Rate per 100,000 = 29,715; grade: F
• Death Rate per 100,000 = 382; grade: F
• Seroprevalence = 67.4%; grade: D
• Percent Fully Vaccinated = 54.5%; grade: D-
• Overall Rank = 52; grade: F

Texas

• Case Rate per 100,000 = 23,215; grade: B+
• Death Rate per 100,000 = 298; grade: B-
• Seroprevalence = 69.7%; grade: F
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 28; grade: C+

Utah

• Case Rate per 100,000 = 29,026; grade: D-
• Death Rate per 100,000 = 147; grade: A+
• Seroprevalence = 69.2%; grade: D-
• Percent Fully Vaccinated = 64.3%; grade: C+
• Overall Rank = 34; grade: C-

Vermont

• Case Rate per 100,000 = 18,336; grade: A
• Death Rate per 100,000 = 96; grade: A+
• Seroprevalence = 28.9%; grade: A+
• Percent Fully Vaccinated = 81.1%; grade: A+
• Overall Rank = 2; grade: A+

Virginia

• Case Rate per 100,000 = 19,912; grade: A
• Death Rate per 100,000 = 236; grade: B+
• Seroprevalence = 45.1%; grade: A
• Percent Fully Vaccinated = 73.1%; grade: A-
• Overall Rank = 8; grade: A

Washington State

• Case Rate per 100,000 = 19,609; grade: A
• Death Rate per 100,000 = 166; grade: A
• Seroprevalence = 54.3%; grade: B
• Percent Fully Vaccinated = 72.5%; grade: B+
• Overall Rank = 7; grade: A

West Virginia

• Case Rate per 100,000 = 27,938; grade: D-
• Death Rate per 100,000 = 382; grade: D-
• Seroprevalence = 54.6%; grade: B
• Percent Fully Vaccinated = 57.6%; grade: D+
• Overall Rank = 44; grade: D

Wisconsin

• Case Rate per 100,000 = 27,604; grade: D
• Death Rate per 100,000 = 247; grade: B
• Seroprevalence = 66.7%; grade: D
• Percent Fully Vaccinated = 65.5%; grade: B-
• Overall Rank = 40; grade: D+

Wyoming

• Case Rate per 100,000 = 27,049; grade: D+
• Death Rate per 100,000 = 313; grade: C
• Seroprevalence = 62.5%; grade: C-
• Percent Fully Vaccinated = 51.6%; grade: F
• Overall Rank = 43; grade: D

The data indicates that during the pandemic, you were best off living on an island (Puerto Rico or Hawaii). If you couldn’t live on an island, then you were best off living in either Vermont or Maine. The states that were the worst to live in during the pandemic were Tennessee, Mississippi, Arkansas, and Alabama.

But the pandemic is not yet over. Today’s epidemiologic data from the CDC shows that we are likely entering a new COVID -19 surge. Since the beginning of the pandemic, we have seen that the percent test positivity starts going up about 2 weeks before the case numbers rise followed a few days later by a rise in hospitalization rates and then about 2 weeks later by a rise in death rates. The graph below shows that the test percent positivity (yellow curve) began to increase on March 19, 2022 and the case numbers then began to increase on April 5, 2022.

The number of COVID-19 hospitalizations (yellow curve in the graph below) then began to rise on April 7, 2022:

The daily death rate began rising on April 27, 2022 (not shown). With a recent societal move toward elimination of masking and social distancing, the number of cases, hospitalizations, and deaths will likely continue to rise in the coming weeks. So, there is still a chance for states to pull up their grades. But given the geographic variation in cultural attitudes toward infection control, I don’t expect this to happen.

April 29, 2022