Ever since the alarm over the SARS-Cov-2 virus was raised there have been heated arguments over comparisons to previous influenza pandemics and the social reactions to them. It is curious to think back on how casually society put children at risk during pandemics that were more dangerous to children than the new corona virus. The risk was accepted as part of life, and we did not shame and condemn people who did not take extreme precautions to avoid infecting others.

The last dangerous influenza pandemic, H1N1 in 2009-10, offers some interesting points of comparison in terms of the statistics compiled on it. The United States Center for Disease Control (CDC) and the WHO report stats like this for H1N1 influenza:

From April 12, 2009 to April 10, 2010, CDC estimated there were 60.8 million cases (range: 43.3-89.3 million), 274,304 hospitalizations (range: 195,086-402,719), and 12,469 deaths (range: 8868-18,306) in the United States due to the (H1N1)pdm09 virus.

In recent media commentary on the corona virus panicdemic of 2020 there have been cries of alarm that the number of Americans who will die will be equal to the best estimate of the infectious fatality rate (0.2%, though estimates vary) times the entire population of 320 million, which would mean 640,000 deaths within a year. There have already been 150,000 deaths, so some believe the only way of avoiding this catastrophe is to continue making everyone wear masks and apply measures of isolation and shutdown of the economy.

However, from the CDC estimate for H1N1, we can see that the CDC never thought every last person in the country would be infected. The estimate must have been based on what they had learned from previous pandemics—that the threat fades away long before every last person has been infected. Thus the CDC had no fear that 0.02% of the entire population of 310,000,000 (62,000 people) would die from influenza before the pandemic ended. In the prediction of how many will die, the entire population is not the denominator. The denominator is what their model (their best guess) shows as the total number of infections, and the numerator is their estimate of deaths caused by H1N1. That gives the following infection fatality rate: 12,469/60,800,000 = 0.02% (2 deaths per 10,000 cases of infection). The modelling assumes that with no drastic measures to stop the spread of the virus (no confinement of the healthy, no shutdown of borders), the majority of the US population never came into contact with the H1N1 virus or never developed an infection.

Thus the good question to ask is whether the same pattern would emerge with Sars-Cov-2. It’s a different kind of virus, but would it be safe to assume that about 1/5 of the population would get infected, at which point herd immunity would be established and the virus would become such a low-level threat that people could stop worrying about it? Once there are enough immune people walking around, they act sort of like control rods in a nuclear reactor. The uranium fuel rods are still dangerously radioactive and hot after the control rods are inserted, but they are no longer reacting enough to produce the heat that powers a turbine. The exponential transmission of a virus gets shut down the same way when a virus cannot find enough hosts to infect. H1N1 still exists, and cases are still reported, but the pandemic status ended long ago, according to the CDC.

The alarmists have also overlooked the fact that viral pandemics move in mysterious ways. On their first appearance they spread rapidly, but then for various reasons related to mutation of the virus, climate, public health interventions, demographics, and natural immune responses, they fade away long before they have infected even half the population.

The alarmists also note that there is a ten-fold difference between the infectious fatality rate of H1N1 and SARS-Cov-2: 0.02% vs. 0.2% (estimates vary because there are so many unquantifiable variables in play). That is a fair objection that would seem to justify the drastic measures that have been taken in 2020, but then again, this is not the return of something like the bubonic plague. The shocking statistic of 150,000 dead in the United States in six months reflects a rate of death that was not seen in many other parts of the world where people and their health care systems were healthier to begin with. The mortality rate does not exist in the nature of the virus itself.

Furthermore, as Robert F. Kennedy Jr., has pointed out, the 1969 Hong Kong flu killed 100,000 Americans when the population was 2/3 of what it is today, and it was a back page story. The hippies went to Woodstock, men walked on the moon, and Nixon continued the war in Laos, Cambodia and Vietnam. In those days, national security was the excuse for all inaction. President Johnson claimed a thorough investigation of the JFK assassination would reveal Soviet involvement and trigger a nuclear war. The government would not have dared to shut down the economy over a viral pandemic lest it give the Soviets a vulnerability to exploit.

The CDC also noted that H1N1 took a particularly heavy toll on children and young adults, but spared the elderly, possibly because they had immunity from exposure to pandemics from many decades earlier. The CDC commented that the death toll could be considered much higher than 12,469 if society showed more concern about the loss of “years lived.” If one subtracts the age of death from the average life expectancy, the contrast with deaths from SARS-Cov-2 is quite apparent. SARS-Cov-2 has severely afflicted the elderly but not affected children, so in this metric, the gap between H1N1 and SARS-Cov-2 would close considerably. If some of those elderly people had been adequately cared for and protected, the death toll would be much lower and the measure of loss of “years lived” for both pandemics might be very close. In any case, what is your magic trigger number that should force quarantine of the healthy and economic paralysis? How many deaths, and whose deaths, and which causes of death matter? 12,000 deaths are acceptable but 120,000 are not. How about 30,000 or 50,000? Children who were at greater risk from H1N1 did not get to decide on these matters, but the adults decided no drastic measures were necessary. Ten years later, when adults were at risk and children were not, the adults demanded great sacrifices from the young. The young had to stop living their lives in a way that was never demanded of the older generations when they were young.

Many older persons are outraged that they have been mistreated and neglected during the present pandemic, and they resent hearing that the virus is not dangerous because it’s a “boomer remover” that “only kills old folks.” This is a valid sentiment about a cold-hearted way to talk about the facts of the matter, but on the other hand, as a sixty-one-year-old father, I would feel ashamed to tell my children to stop enjoying the things I enjoyed at their age. I will take responsibility for protecting myself, and if the virus gets me, so be it. I want young people to carry on with their lives, get the virus if it comes their way, and get over it. It will give them much needed immunity to future corona viruses. Go out, get immunity, and be the control rods we need to shut down this pandemic. But apparently I’m writing a minority report here. The rest of my generation seems willing to turn the younger generations into a figurative Picture of Dorian Gray locked away in their attic. Baby Boomers, do you still wonder why you are resented by the young?

dorian gray-albright-03
The Picture of Dorian Gray, by Alvin Albright, 1943, story by Oscar Wilde, 1890

Fortunately, there are some reasons to be optimistic, even if so many are determined to see only the doom and gloom of the situation. The CDC’s figure of 20% infected with H1N1, at which point the pandemic ends, has appeared again in mathematical models of the SARS-Cov-2 pandemic.  An article in The Atlantic reported on the work of Gabriela Gomes, professor at the University of Strathclyde, in Glasgow, Scotland:

Now, based on the U.S. response since February… we’re still likely to see the virus spread to the point of becoming endemic. That would mean it is with us indefinitely, and the current pandemic would end when we reach levels of “herd immunity,” traditionally defined as the threshold at which enough people in a group have immune protection so the virus can no longer cause huge spikes in disease…

… the complexities of real life create what modelers refer to as heterogeneity. People are exposed to different amounts of the virus, in different contexts, via different routes. A virus that is new to the species creates more variety in immune responses. Some of us are more susceptible to being infected, and some are more likely to transmit the virus once infected. Even small differences in individual susceptibility and transmission can, as with any chaos phenomenon, lead to very different outcomes as the effects compound over time, on the scale of a pandemic. As Gomes explains, “There doesn’t need to be a lot of variation in a population for epidemics to slow down quite drastically.”

… She describes a model in which everyone is equally susceptible to coronavirus infection (a homogeneous model), and a model in which some people are more susceptible than others (a heterogeneous model). Even if the two populations start out with the same average susceptibility to infection, you don’t get the same epidemics. “The outbreaks look similar at the beginning. But in the heterogeneous population, individuals are not infected at random… The highly susceptible people are more likely to get infected first. As a result, the average susceptibility gets lower and lower over time.”

Effects like this—”selective depletion” of people who are more susceptible—can quickly decelerate a virus’s spread. When Gomes uses this sort of pattern to model the coronavirus’s spread, the compounding effects of heterogeneity seem to show that the onslaught of cases and deaths seen in initial spikes around the world are unlikely to happen a second time. Based on data from several countries in Europe, she said, her results show a herd-immunity threshold much lower than that of other models.

“We just keep running the models, and it keeps coming back at less than 20 percent,” Gomes said. “It’s very striking.” [emphasis added]

If that proves correct, it would be life-altering news. It wouldn’t mean that the virus is gone. But by Gomes’s estimates, if roughly one out of every five people in a given population is immune to the virus, that seems to be enough to slow its spread to a level where each infectious person is infecting an average of less than one other person. The number of infections would steadily decline. That’s the classic definition of herd immunity. It would mean, for instance, that at 25 percent antibody prevalence, New York City could continue its careful reopening without fear of another major surge in cases.

Professor Gomes stresses in the article that the 20% figure is not provable and reliable because other determining factors are such variables as population density, behavior and social policy. Nonetheless, her models are an indication that there is no call for the pervasive pessimistic attitude that has dominated media reporting and government decisions this year.

The article in The Atlantic fails to mention other aspects of the concept of immunity that make the picture even more heterogeneous than what Professor Gomes described. Biophysicist Creon Levit explained other aspects of the immune system besides antibodies and how they relate to predictions of how the pandemic will end. He described the following types of immune responses:

  1. Denatured/Barriered: The virus doesn’t penetrate skin or mucous membranes.
  2. Innate Cleared: Certain antibodies and certain other signaling processes can prevent or clear a viral infection even though you’ve never been exposed to that particular virus before. These are generic mechanisms that work against all harmful viruses and bacteria.
  3. T-Cells Prior Adapted: You can have immunological memory that you get from viruses that are not identical to the current virus but are similar. All corona viruses, for example, have similarities.
  4. T/B Cells Newly Adapted: Your infection may get cleared, in principle, by one of the T-cell-mediated pathways like cytotoxic T-cells. These new antibodies are not detected by the antibody test.
  5. Production of antibodies for a specific virus.

Types 1, 2, 3 and 4 do not produce antibodies, although antibody response might happen at the same time as these other immune system mechanisms are active. Presently, epidemiologists are trying to find out how many people have been infected by the new corona virus, and they are using antibody tests (which produce a lot of false positive and false negative results) to measure how widespread the virus is in society. The main idea stressed by Creon Levit is that antibody tests reveal only a small fraction of the number of people who have been infected or in contact with the virus. It is possible that the virus has already spread widely, unnoticed or with little harm to most people. If some people got infected and recovered, many more did not develop a serious infection and they can also be described as immune (if that suits your definition of immunity) even if they did not produce antibodies. However, immunity is a fluid concept. A person who is immune now may not be immune in the future if she is weakened by age, malnutrition, stress, chronic disease and so on. It is unrealistic to expect there will soon be a time when we can say the virus is 100% gone and it is 100% safe to travel or to sit in crowded theaters. As Robert Kennedy Jr. said in the interview cited above (paraphrasing): Wasn’t this is supposed to be the land of the free and the home of the brave? People will just have to reclaim the freedoms that are being lost in this time of bio-security anxiety and find the courage to be social animals again.

It was very easy to tell people to wear masks everywhere, but when the time comes to end the panic, it is going to be difficult to convince them that it is safe to breathe freely. A new neurosis has been created. How safe does the air have to be? Here in Japan, before this pandemic, it was already normal for people to wear masks throughout the fall and winter as a barrier against allergens and microbes. Before Covid-19, I had already found this habit to be a frustrating barrier to communication. The ones who liked the masks were the ones who seemed the sickest and most socially withdrawn. Did they wear the masks because they had weak immune systems, or did they have weak immune systems because they wore the masks constantly? Were these causes and effects amplifying in a vicious circle?

Counsellor and author Yuzo Kikumoto, in 2009, was the first to describe mask-wearing as an unhealthy psychological dependency. Research subjects who mask up regardless of the season were quoted as saying, “I don’t want to show others my true self,” or “Since my face is covered, people don’t know how I’m really feeling. It’s comforting,” and “I don’t like having to create facial expressions for people” [emphasis added]. Mr. Kikumoto says, “They have an abnormal fear of showing who they really are to their peers.”

Ever since I came to Japan in the 1980s, I’ve heard observers of the country say you can always get a glimpse of the future in Japan: life after a nuclear bombing, life after the end of your empire, robotics, sexbots, karaoke, emojis, papering over a systemic crisis with unrepayable debt, surgical masks for the masses. Even the pop ditties of the 1980s saw all this coming.

The Vapors 1980, Turning Japanese:

No sex, no drugs, no wine, no women

No fun, no sin, no you, no wonder it’s dark

Everyone around me is a total stranger

Everyone avoids me like a cyclone ranger, everyone

That’s why I’m turning Japanese, I think I’m turning Japanese

I really think so

Styx, 1983, Domo Arigatou, Mr. Roboto:

You’re wondering who I am (Secret, secret, I’ve got a secret)

Machine or mannequin (Secret, secret, I’ve got a secret)

With parts made in Japan (Secret, secret, I’ve got a secret)

I am the modern man

I’ve got a secret I’ve been hiding under my skin

My heart is human, my blood is boiling, my brain IBM

So if you see me acting strangely, don’t be surprised

I’m just a man who needed someone and somewhere to hide

To keep me alive, just keep me alive

Somewhere to hide to keep me alive…

I am the modern man (Secret, secret, I’ve got a secret)

Who hides behind a mask (Secret, secret, I’ve got a secret)

So no one else can see (Secret, secret, I’ve got a secret)

My true identity…

(Domo arigato, Mr. Roboto) Thank you very much, Mr. Roboto

(Domo arigato, Mr. Roboto) For doing the jobs that nobody wants to

The problem’s plain to see

Too much technology

Machines to save our lives

Machines dehumanize