Herd Immunity Ratio
As an intellectual exercise let’s think of an imaginary state, “State A.” Our fictional State A is devastated that 100 of its citizens are infected with Covid-19. For this exercise, we accept that these 100 citizens are representative of State A‘s demography, classes, ethnicities and so on. Apparently, State A’s nightmare is just the beginning because out of its 100 Covid-19 carriers, not one survives the next three weeks.
Let’s now imagine another case, we will call “State B.” State B is similar to state A in terms of its size, population, geography, climate, culture, ethnicity, nutrition, etc. In State B 100 citizens also tested positive for Covid-19. Following the experience of State A, State B braces itself for the possibility that all its infected citizens may perish but then for reasons that are not yet clear to us, no one in state B dies. And if this is not different enough, hardly any of the 100 develop any symptoms.
The crude difference between State A and B may tell us something about the herd immunity in States A and B. It is easy to detect that the ratio created by the number of fatalities (F) divided by the number of those infected (I) is an indication of the level of immunity or ‘herd immunity’ in a given region or a state.
State A: F/I = 100/100=1
State B: F/I = 0/100=0
State A’s immunity ratio equals 1. This means that anyone who contracts the virus in State A will likely die. In state B, on the other hand, one is likely to survive the virus. In fact, they may, without knowing it, have already survived.
But let us now consider some more realistic cases. In “State C,” again, a state similar to A and B, out of 100 who tested Covid-19 positive, 10 people died within the next few weeks.
State C: F/I=10/100=0.1
The herd immunity ratio in State C is 0.1. In terms of herd immunity, State C is far better off than State A as a virally infected subject may benefit from a 0.9 chance to survive. But State C’s situation is not as good as in State B where no one is expected to die as the F/I ratio in State B is O. We can see that the smaller the F/I ratio is, the greater is the herd immunity in a given state or a region.
But let us look at another realistic case. In “State D” out of 100 patients only 1 died within a few weeks.
State D: F/I=1/100=0.01.
This means that in State D the herd immunity is close to perfect. Someone who contracts the Covid-19 virus has only a remote chance that he will lose his life. In other words, the survival rate is 0.99
State C and D are not completely imaginary cases. The F/I ratio in State C is a good representation of the numbers we saw in Northern Italy, NYC, Spain, UK and other vulnerable regions that have suffered heavily in the last few weeks. The ratio in State D is very similar to South Korea and Israel. Though many people are identified with Covid-19 in these two states alone, very few have died.
Such a methodical search for herd immunity ratio may help to identify the survival rate in different states, regions and cities. It may help us to determine policy; to decide who, what and how to lockdown or maybe not to lockdown at all. It can also help to locate the origin and the spreaders of the disease as we have a good reason to believe that the regions with the most immunity to a given viral infection have likely experienced the disease in the past and have developed some form of resistance.
In reality, this model is problematic for many reasons and can hardly be applied. As things stand (in reality), we are comparing data that was collected under different circumstances and using various procedures designed with completely different strategies and philosophies. Both Israel and South Korea, for instance, conducted testing on mass scale and hence, identified many more carriers. More crucially both Israel and S. Korea made a huge effort to identify super spreaders and applied strict isolation measures to those spreaders and those who were infected by them. Britain, USA and Italy on the other hand conducted limited testing and have generally tested those who developed symptoms or were suspected of being infected.
But there is a far greater problem with the above herd immunity ratio model. It assumes that we know what we are dealing with i.e., an infectious viral situation, while the evidence may point otherwise.
The Radioactive Clock
It has become clear that the health crisis we are facing isn’t consistent with anything we are familiar with. Those who predicted a colossally genocidal plague weren’t necessarily stupid or duplicitous. They assumed that they knew the root cause of the current crisis. They applied recognized models and algorithms associated with viral pandemics. They ended up eating their words, not because their models were wrong but because they applied their models to the wrong event. While no one can deny the alarming exponential growth of the disease, it is the unusual ‘premature’ curve-flattening point and then the rapid decline of infections which no one explained. In fact, some still prefer to deny it.
Many of us remember that our so-called ‘experts’ initially tended to accuse China of ‘hiding the real figures’ as no one could believe that the virus, all of a sudden, pretty much ran out of steam. Some also claimed that Iran was faking its figures to make its regime look better. Then came South Korea and the scientific community started to admit that despite its initial rapid exponential growth, for an unexplained reason, the ‘virus’ seems to run out of energy in an unpredictable fashion: the curve straightens out almost abruptly and starts to drop soon after, almost literally disappearing to the point where even a country as enormous as China passes days without diagnosing a single new Covid-19 carrier.
When Italy experienced its Corona carnage, every health ‘expert’ predicted that when the ‘virus’ slipped out of the rich Lombardy region and made it to the poor south, we would see real genocide. That didn’t happen.
We have also started to notice that lockdowns have not necessarily saved the situation and that adopting relatively light ‘lockdown’ measures doesn’t translate into a total disaster as Sweden has managed to prove. The ‘virus,’ appears to stop spreading according to its own terms rather than the terms we impose upon it.
Thinking about the anomalies to do with the virus in analytical mathematical terms, as opposed to seeing the virus in biological or medical terms, has made me believe that a paradigm shift may be inevitable. We seem to have been applying the wrong kind of science to a phenomenon that is not really clear to us. This may explain what led a British ‘scientist’ to reach a ludicrous and farfetched estimate that Britain could be heading towards an astronomic death figure of 510.000. Following the same flawed algorithm, Anthony Fauci advised the American president that America could see two million dead. Both scientists were wrong by a factor of 25-40 times. Such a mistake in scientific prediction should be unforgivable considering the damage it inflicted on the world’s economy and its future. One might say that the good news is that our governments are finally listening to scientists, the tragedy, however, is that they are listening to the most idiotic scientists around.
Looking at the tsunami of raw data regarding worldwide spread of Covid 19 reveals a lot, perhaps more than we are willing to admit at this stage. The numbers, the shape of the Corona growth curve and the manner in which it flattens and declines suggests to me that something different may be at play. It seems as if the disease is shaped by an autonomous internal clock that determines its time frame and that it is not impeded by any form of organic resistance such as antibodies or herd immunity. The curve’s rise toward that flattening instant is indeed characterized by consistent and exponential growth. But then, in a seemingly arbitrary manner, the disaster stops its increase and the numbers of those infected by Covid-19 starts to drop.
Looking for such a pattern that produces an exponential growth that comes to a sudden end calls to attention the concepts of radioactivity in general and of the half-life in particular.
Each radioactive isotope has its own decay pattern. The rate at which a radioactive isotope decays is measured in ‘half-life.’ The term half-life is defined as the time it takes for one-half of the atoms of a radioactive material to disintegrate. Radioactive decay is the disintegration of an unstable atom with an accompanying emission of radiation. The change from an unstable atom to a completely stable atom may require several disintegration steps and radiation will be given off at each step.
Half-life is a measurement of time (set by the radioactive isotope) that involves a repeated release of radiation. Each time radiation is released the radioactive isotope is splitting in half, this repeats until it either reaches stability or maybe becomes ineffective. If you bear the half-life dynamic in mind you can see how one person can ‘infect’ or shall I say, radiate an entire stadium a few times over during a two hour football match. All it takes is a radioisotope with a half-life cycle of a few seconds.
Once the atom reaches a stable configuration, no more radiation is given off. For this reason, radioactive sources become weaker with time, as more and more unstable atoms become stable atoms, less radiation is produced and eventually the material will become non-radioactive. I wonder whether this could provide an explanation for the abrupt curve flattening that is associated with Covid-19
What may be possible is that Covid 19 is not the root cause of the current disease, it may instead be a by-product of a radioactive interaction. I am not in any position to substantiate this theory. Instead, I offer an alternative way of thinking about the problem that may shed light on the situation. If Covid-19 is a by-product of radiation, then the sudden decrease in radioactivity due to the nature of half-life reactions can explain why the virus loses its growth energy when it seems as if it has become unstoppable.
If this theory has any merit, then we are misdiagnosing the Corona crisis, misapplying the science and implementing the wrong strategies. It may also indicate that herd immunity won’t work, as we are not dealing with a viral infection but instead becoming ourselves, a source of radiation.
This theory may help explain why Israel and South Korea (State D) were so successful in combating the crisis. It wasn’t the lockdown that saved these countries. It was their aggressive search for and quarantine of super spreaders and those who were potentially radiated by them. Consciously or not, rather than stopping the virus they isolated the catalysts that were leading to the creation of the virus.
Our world is in a grave crisis and could benefit from thinkers who are slightly more creative, sophisticated and responsible than the characters who currently occupy the World Health Organisation, the CDC and London’s Imperial College. But more than anything else, I reiterate once again: we need to escalate our response to the Corona crisis into a criminal investigation so we can figure out every possible error or malevolent act that led humanity into the current grim situation.