Nearly a month ago I proposed the then novel theory that the officially reported coronavirus death rate was exaggerating the actual lethality of the Wuhan Flu by some order of magnitude due to an artifact in the data. Specifically, I theorized that limitations in testing for this disease, including deficiencies in the available testing methods and a failure to test randomly or even broadly enough to identify asymptomatic and mild cases, was causing our health authorities to overlook a vast number of infected individuals. This error has been greatly inflating the reported death rate. https://www.renewamerica.com/columns/jwagner/200323 In effect, some 80% or more of all infected persons, because they did not report to hospitals for treatment, were never tested and were consequently, at least for statistical purposes, being entirely ignored. As I write today, this understanding that our current data limitations are causing a significant overstatement of the death rate is widely accepted, though official reports still do not yet reflect it. https://thehill.com/changing-america/well-being/prevention-cures/490558-study-coronavirus-mortality-rate-lower-than

But since I wrote that article the status of death rate reporting has only grown worse. Although testing is now taking place at a much higher rate, the efficiency of this testing for epidemiological purposes remains deplorably low. That is because we are still using so called “molecular” tests, which while scarcely adequate for identifying current cases (false negatives at a rate as high as 30% https://www.bloomberg.com/news/articles/2020-04-11/false-negative-coronavirus-test-results-raise-doctors-doubts) have no ability to identify those who have been infected with the virus and since recovered. As time passes, an increasingly large but as yet entirely unknown portion of the population has recovered from this disease and presumably become immune as a result. But this entire group is omitted from the infection data, and will continue to be omitted until the long awaited serological (antibody) tests now in development come into widespread use.

Today I have a second contrarian theory on the coronavirus to propose. For some time it has seemed to me that the startlingly precipitous flattening of the curve of new cases around the world, now attributed to social isolation, was actually being caused by a large but unknown contingent of resistant individuals within the population. I read this morning that there have been incubation periods for this virus as long as 24 days, but the CDC concludes that “a very long incubation period could reflect a double exposure.” https://www.worldometers.info/coronavirus/coronavirus-incubation-period/

The trouble with this explanation is that double exposure implies a gray area within which certain persons were “resistant” but not immune as of their first exposure, or were infected without acquiring the protective antibodies by which such infection is defined. But setting aside this conundrum, while a resistance of some sort is implicitly acknowledged in such an explanation I have seen no reference to a resistance of any sort in the statistical reporting on this disease. This suggests a possible second data artifact—or more precisely a data omission—on the part of medical authorities and media.

The omission I am referring to, and it is actually quite enormous, arises from confusion over the definition of “immune.” In the most technical sense, immunity to a disease exists only where an individual has been previously infected with that specific disease and has acquired the corresponding antibodies. In the case of a novel virus like this coronavirus, by definition no one is immune at the onset of the disease. In other words, any portion of the population, large or small, that is able to resist an infection for another reason, be it a strong immune system, a certain blood type (“O” has been reported to be more resistant in this case than “A” https://www.pharmacytimes.com/news/study-suggests-blood-type-a-associated-with-higher-risk-of-covid-19), exposure to a similar disease that triggers a sympathetic immune response, developmental stage, chronological age, gender, or any other biological factor, is not technically immune. Such people may be functionally resistant to the disease to such an extent that they are “practically” immune to it. And yet for immunological purposes they are not counted as such or included in the data. It is as if our medical authorities have simply assumed that without immunity as it is most narrowly defined there can be no resistance whatever.

In the case of this coronavirus, it seems to me that this approach to the data is in error, though it is taking place on a very large scale with profound implications. As a matter of established fact, at least some of those already known to be resistant to this virus are being entirely ignored when it comes to models of transmission. The group I am referring to specifically in this instance is children. You have heard many times that children don’t often get severely ill with the Wuhan version of coronavirus, and rarely die from it. But the fact that they rarely become infected with it at all has been downplayed to such an extent that it might be fair to call this negligence a lie by omission. In an understated report, NBC News let the cat out of the bag. “Coronavirus cases among children have been documented, but according to data from the Centers for Disease Control and Prevention, these cases are rare.” (Italics mine.) https://www.nbcnews.com/health/health-news/coronavirus-kids-rare-mostly-mild-though-serious-cases-can-happen-n1177651

What has been even more dramatically downplayed is the rather obvious fact that the vast majority of children who are resistant to the virus are acting as a contact buffer within the population. Children, because of their mutual proximity and the activities typical of their age group, should be among the most frequently infected and most prevalent vectors. And yet when it comes to this particular virus, it turns out that from an immunological perspective they are no different from those already infected, that is, those technically immune.

Children under 18 years of age make up 22% of the U.S. population. That is a significant buffer to the spread of infection. Or to put it another way, it is a significant contribution to the “herd immunity” we have been hoping for, especially in combination with the vast and yet still unknown number of those already infected and recovered and those currently infected but asymptomatic and thus undetected. And yet as of this morning I have seen no public reference to this rather significant possibility—that is, that children are an actual barrier to the spread of this disease as opposed to a vector to be feared and avoided.

It has been well noted that the death rate for the Wuhan coronavirus varies directly with the chronological age of those infected. But I have seen no data on the rate of infection as it varies by age. That is likely because without serological testing (still not available) it is not at all easy to determine that relative number. Here is what I suspect: The rate of infection for this coronavirus, like the death rate, will vary directly with chronological age. In other words, the rate of infection, already known to be lowest among children under 10, will be incrementally higher for teens, and then for those in their twenties, and so forth. To say that another way, the younger an individual is, the more likely that he or she will be resistant to this disease and unable to spread it. I also suspect, based on published death rates, that the infection rate will increase more or less geometrically with age.

If this turns out to be true it will explain why this virus plateaus so quickly. And an absolute resistance would not be necessary for this effect; even a substantial relative resistance by age group would achieve this effect. Contrary to the underlying assumption of all contagion models for this virus currently in use, which start with the assumption that all segments of the population are equally susceptible to the virus and capable of spreading it, I believe we will find that a very large sector does neither. This virus may be highly contagious to those who are not resistant, but there are likely many others who are so resistant as to be practically if not technically immune to it, including children who have already proven to be highly resistant.

The higher per capita death rate of Europeans compared with the U.S. offers some circumstantial support for this theory. Americans simply have more children. The median age for EU-28 members is 43.1 years, almost five years older than the 38.2 figure for the U.S. That this difference represents children is confirmed by the European fertility rate, which is predictably much lower. With American fertility at 1.77 (1.77 children per couple), EU-28 fertility is at 1.59. More strikingly, we find that Italy, with the highest coronavirus death rate anywhere, has a meager fertility rate of 1.32. Even without the coronavirus, that is a path to early extinction. In Sub Saharan Africa, where the coronavirus has been slow to take hold in spite of sketchy social distancing practices (https://www.brookings.edu/blog/africa-in-focus/2020/04/09/social-distancing-unlikely-to-hold-up-in-africa-without-a-safety-net-for-microentrepreneurs/), the fertility rate hovers around 5.0—five children per couple.

I am not arguing that a variable native resistance in the population is the only explanation for the seemingly early plateaus and abrupt reversals in the coronavirus infection curve. Social isolation undoubtedly plays some part. But I do believe that natural resistance is the major factor. The good news is that if that is true it will mean that a plateau in the infection curve will signify that the pandemic has not merely been postponed but is actually in its decline. It would also mean that subsequent waves of the virus, should they come, would likely be less widely infectious and less lethal, the most vulnerable having already passed. From an historical perspective this would not be surprising. It was true even of the famed bubonic plague of the late middle ages, which arrived in ten successively less lethal waves.

Actually, to be more precise in our terms we should no longer speak of a plateau. New infection rates from all around the world have been in a dramatic decline for some time. https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6 In my view, natural resistance of certain sectors within populations would best explain this reversal we are seeing in the infection curve. It would also justify a more immediate return to normal life, but that is the subject for another article.

While the initial spread of this virus has been exponential, the saturation level seems to have been reached very quickly regardless of the societal means of combatting it in most situations. https://townhall.com/columnists/marinamedvin/2020/04/15/israeli-professor-shows-virus-follows-fixed-pattern-n2566915 (New York City, where subways have remained in operation, is a special case.) None of the current models explain this. A resistant element in the population does explain it. And yet in spite of the known fact that children are proving demonstrably resistant to this particular virus no one is relying on this as an explanation for the descending coronavirus infection curve. No one, as far as I know, has even proposed natural resistance by age group as an explanation for the decline in infections, and I find this oversight incomprehensible.

In order to identify and then quantify the number who have already been infected and are now immune we will need to implement serological testing. To determine what portion of the population may be naturally immune we will need only a better analysis of our data. We could compare infection rates as well as death rates by age, for example. Or we could examine the number of those known to have been exposed but not infected, such as those on the Diamond Princess. A variance of infection rate by age in such confined populations would give us at least an initial indication.

As I have noted, the fact that an ongoing lack of such testing and data analysis has resulted in an overstatement of the death rate by some unknown order(s) of magnitude has finally become widely recognized, although the official reports still do not reflect that. I believe that when such methods are finally implemented they will also show that the infection rate, like the death rate, varies with age as I have here outlined. Even if my theory of age related natural immunity is wrong, an appropriate societal reaction to this virus requires a public examination of such questions.