What if…everyone has already contracted coronavirus? An intriguing hypothesis

There is not merely a significant underdetection of COVID-19 cases but a nearly 100% underdetection, which means that almost everyone has been infected with coronavirus. Moreover, there are no waves in the pandemic, rather than entirely separate epidemics. Two statements that may seem steep at first, but a single hypothesis. Intrigued? Then read on.
őrült tudos

When the dynamics of a pandemic are perplexing and difficult to fathom, an inquisitive mind explores every option when trying to make sense of it all or to come up with forecasts on the trajectory of the pandemic. Balázs Pártos is one of those minds. He has been closely following the events since the outbreak last spring and publishes his insights, assessments, prognoses, charts on his Facebook page which is followed not only by the ’riffraff’ but also by physicians, virus experts and epidemiologists in the country (more than 4,000 people altogether). He is really good with numbers and was the author of or contributed to various articles on Portfolio. Not that it matters who came up with this theory, just wanting to point out that it was not some dimwit.


This is a hypothesis that attempts to provide a more acceptable or credible explanation to the dynamics of the pandemic. It, however, does not change the methodology used for previous and/or future estimations. It only makes the peaks of the ‘waves’ more calculable and turns various unexplainable factors into explainable phenomena.

It’s important to note that this is a static physical model and a rationale for the dynamics of the pandemic, rather than for the actual biological / virological root.
Simply put, it explains what and why we are witnessing what is in front of our eyes. It does not explore the causes.

It is a hypothesis because it draws up a possible framework as a backdrop. This could be a wrong hypothesis, sure, but the dynamics drawn from the hypothesis are correct and can be verified mathematically. It cannot be verified, however, whether the explanation is good or not. This hypothesis has absolutely no intention to explore the biological and virological background; it is not meant to be an epidemiological modelling or dynamics tool.

Here’s the gist of his hypothesis:

  • there are no waves in the coronavirus pandemic with baffling dynamics, but standalone epidemics, as the virus is still developing and is in the process of reaching its final form;
  • local herd immunity exists in the individual waves (epidemics), that is why these ‘waves’ fizzle out at 80-90%, but there’s no herd immunity for the aggregate epidemic (the group of epidemics), just as there’s none for the common cold or the flu, only for the specific strains
  • these separate clusters arise one after another and many run parallel with each other. And if we examine their individual dynamics, they cease to be confusing;
  • there are clearly parallel epidemics in geographic aspects, but sometimes they co-exist in a single country, only they are at different stages;
  • cross-immunity is small but will increase with time when there are more variants than currently;
  • there is no herd immunity;
  • vaccines give limited protection and only for so long;
  • the actual mortality rate is low in the individual epidemics (0.1 to 0.2%), but there have been many already;
  • everyone or quasi everyone have been infected;
  • yes, they probably contracted all of them except for the Delta variant, it’s next.

Wait, whaaat?

Pártos uses an analogy to make his theory clearer.

Wi-Fi connection and testing

Let’s say there’s a vacant building with a working Wi-Fi router we don’t see. No problem, we have s smartphone and it shows a Wi-Fi connection, so we know there’s Wi-Fi.

Now, let’s pretend we’re in the same building, only in bathing suit sans our phone. Then we do not sense there’s Wi-Fi. It’s there but we cannot detect it. Does the electromagnetic wave flow through us? Of course, it does, and so does cosmic radiation. Only we don’t know about it because we have no tool to ‘catch’ the signal.

Whether or not there’s Wi-Fi connection in the building does not depend on our phone but on the network and the router. What depends on our phone is whether or not we can use this Wi-Fi connection.

How do we detect coronavirus? With tests, of course, all kinds of tests. If you ask which one of these is the most reliable, the answer is PCR, the abbreviation of polymerase chain reaction. It's a test to detect genetic material from a specific organism, such as a virus. Is it 100% accurate? Nope. There are false negatives too. Firstly, the more extremely positive samples there are in a batch, the more false negatives we’ll have. Secondly, the PCR test has a minimum sensitivity, meaning that below certain level it does not show the presence of viral RNA. Either because there’s none or because there’s not enough (minimum detectable viral load, MDVL).

Wait, this does not add up...

Pártos listed a couple of factors that bothered him when examining the dynamics of the current pandemic.

  1. the waves end with no apparent reason
  2. the waves are largely of the same height (see chart 1)
  3. when it’s in one place, it is not there in another… like a ball bouncing about in a box (he had already used this analogy when he had claimed there were actually no waves in this pandemic)
  4. the rise in the number of COVID-19 cases on a global scale is rather linear (see chart 2)
  5. the rise in the number of COVID-19 deaths on a global scale is also rather linear (see chart 3)
  6. the number of serious COVID-19 cases in hospitals has been rather constant for a while, regardless of the waves (see chart 4)
  7. the number of Covid deaths does not decrease considerably
  8. it often happens that not each family member ‘gets infected’ despite living under the same roof, while a person that met them for two minutes got infected
  9. vaccination coverage does not appear to be lowering the number of new cases

This particular hypothesis explains all of these concerns.


Turning the focus onto Hungary Pártos claims that last autumn nearly everyone was infected with the variant close to the original one (originating in Wuhan, China), which implies that there were not 300,000 to 400,000 infected people in Hungary but 8 to 9 million (!). And there were 15,000 to 20,000 Covid deaths.

In the spring of 2021, (almost) everyone contracted the Alpha variant (UK or Kent variant). Again, 8 to 9 million people. There were another 15,000 to 20,000 Covid deaths.

In February and March, the two epidemics were in Hungary at once. The original one was petering out, the new one was picking up pace.

They were not the same epidemics, they were not two waves of the same pandemic, they were separate epidemics. And the one we are in right now is a third epidemic. The symptoms look similar to those before, but this is another pathogen and another epidemic. What is similar is the illness. What is different is the sensitivity to the pathogen.

Key similarities

The way the numbers look may be explained by two infection scenarios.

  1. Only 25 to 30% of the population contracted coronavirus. If we accept this, mortality is dramatic. Only 10% of these cases were actually detected so there would be a 3x underdetection which is suspiciously low, with so few tests performed. This would leave 70% of the population susceptible to the virus, most of whom have not been vaccinated. This implies that another 10 to 15% of the population will be infected which would lead to another cc. 20,000 deaths.
  2. We get the same numbers also if we call these waves, or separate epidemics, assuming that in these epidemics 80 to 90% of the population were infected. In that case, herd immunity is reached locally which is attested by the sudden stoppages in the spread of the virus (3 December 2020, 27 March 2021). These were the dates when all at once authorities started to diagnose a lot fewer people with COVID-19. When test positivity is at 30 to 35%, about 70% of the population are actually infected. After the peaks, Covid hospitalisations run out, but there’s no cross-immunity therefore the same 70 to 80% of the population will be infected again (with Delta this time). Under this scenario / assumption, these epidemics when 80% of the population are infected lead to 20,000 deaths each (this is evident in Central Statistical Office (KSH) stats). The deduction is that a new ‘wave’ / epidemic will be almost as deadly. Owing to the vaccination coverage and some cross-immunity the death toll would be lower at an estimated 13,000, but still…

With a 90% vaccination coverage a lot fewer people would be in hospitals with coronavirus infection. However, about half of the population under 45 years of age are unvaccinated, and the largest part of the elderly population were inoculated with China’s Sinopharm which tends to be a lot less effective in the 65+ age group.

As noted above (box) Pártos claims this hypothesis does not change his previous and future estimates, it leaves his methodology intact. This is merely a kind of an explanation to why we are witnessing this particular dynamic in the ‘pandemic’.

The overall conclusion of this hypothesis could be that when the positivity rate exceeds 25%, there could be the end of virus transmissions and when it’s close to 30% that is the end of the line, a sharp drop in new cases will ensue (a die-off model for those that can still be infected).

The use of this is that we will be able to forecast the end of the ‘waves’ with a higher accuracy. Pártos has most accurate models for the acceleration phases but had difficulties projecting when these upswings would end and when the ‘waves’ would start dropping. With this hypothesis this would be easier.

Key differences

1.) The viral load and the detection rate.

The quantity of virus is higher in the case of the Delta variant, hence we can detect more infections. This does not mean that the Wuhan or the Alpha variant did not infect (almost) everyone. They did, only those infected were asymptomatic or developed mild symptoms in 90% of the cases, 80% were practically undetectable because their immune systems beat the virus so easily. But the infections were there.

Imagine this:

If 35% of samples in a test batch are positive then it includes negatives of people discharged or transferred from hospitals and negatives of people needing them to travel abroad or for their work place. There is no differentiation within a batch. It also includes false negatives and the more positive a batch is the higher their number is. Consequently, when you see a 35% test positivity, the ratio of the population actually getting infected is close to 70%. Thus it should not be a surprise when the ascending trajectory stops shortly and starts to ebb.

2.) People are not equally sensitive to the various epidemics.

Some are down on their luck and get infected in more than one or all of them. The lucky ones fend off each and some are the middle, getting infected in one and avoiding infection in the other.

So, when we see that the pandemic (it’s an epidemic in our case) ended, although we ‘haven’t done anything’ (e.g. in the middle and end of last November and before end-March this year), then it’s not divine intervention or a miracle, only the virus run out of people to infect.

It’s an exponential function just like at an extinction event. The infection spreads exponentially without obstruction and then there’s suddenly no more people to infect and it practically fizzles out (see chart 5).

The curve showing the number of new COVID-19 cases continues to go up because of the incubation time that varies per person, and also because not everyone is tested on a single day, but only when they show up for testing, not to mention testing constraints.

But if you look at hospitalisation, it was as if Gandalf stood in front of every hospital in Hungary and shouted at people with COVID-19 waiting to be admitted: YOU SHALL NOT PASS! It was over like that. Up until Easter Covid patients were continuously admitted in hospitals, but after Easter they were practically gone. And the same took place in December. Why? Because no more people were left to take to hospital. The virus was unable to infect more people, the epidemic run its course.

Now, what happens when we have (in our mind for now, it’s a hypothesis, remember?) separate epidemic waves that are also separated geographically? Well, it all starts to make sense.

The symptoms are similar therefore we perceive them as a single disease. It’s like when you see a guy coughing. It can be from asbestos or from cigarettes, the cough is the same, but the trigger is not.

But what do the various epidemic waves do then? They interfere with each other, they get superimposed, or in layman’s terms: they mix (see chart 6).


Several epidemics run parallel with each other. When Hungary was still combating the ‘second wave’, it was already over in the UK and the USA, where the ‘third wave’ was starting. Other places, other ‘waves’ and scenarios. A lot of such superimposing waves in enough places will yield a largely straight line. There will be small bumps globally and large waves locally, but from a distance we’ll see an almost straight line. That is what we are seeing now. Take a look again at the topmost chart that looks like a wave and compare it with Charts 2, 3, and 4.

A hypothetical scenario

The father goes down with coronavirus, and he is really sick. Mom is healthy as an ox. The neighbour, old Mr. Kaminsky, pops in to borrow some sugar for the missus who is baking his favourite cake, and he gets infected and dies in a week. The kid is fine as rain. He gets tested. Negative. The mom’s the same. Her test also comes back negative. Does this mean that little Joey and mom did not contract coronavirus although they live under the same roof with dad who shows severe symptoms, while good ole’ Mr. Kaminsky – peace be upon him – pops in for a minute and gets infected?

Nope. Dad transmitted the virus to ALL OF THEM. Only mom and Joey either had a great immune system or their vaccination worked so well for this variant that even their tests failed to show infection. It’s common sense that they contracted the virus. Why wouldn’t have they?

So, the theory is that everyone got infected. Everyone. With several variants. Multiple times. A few percentage of the population shows severe symptoms in an epidemic and deaths can be measured in the thousandths.

Only there was (and is) not one epidemic but many. Following each other in rapid succession.

The Conclusion

  1. There is no herd immunity and there never will be.
  2. What we call the waves of a pandemic are actually new epidemics. They may look like waves but only locally.
  3. Those that said a pandemic is ‘only’ double or triple as harmful as a rough influenza epidemic were right. Only we have multiple epidemics bumper to bumper so to speak.
  4. Those were also correct that said underdetection is massive. Only they were wrong because massive does not really describe the situation. It’s not even a tenfold underdetection. It’s as dramatic as effectively 100%. More precisely, it’s 80 to 90%, as a temporary local herd immunity in the various epidemics is reached. At the peaks of an epidemic up to 30 to 40% of the COVID-19 tests are positive, according to laboratories. Pártos claims that practically 80-90% of these would be positive if the viruses in the remaining 60 to 70% of the samples were cultivated, as these appear negative only because of the quantity of the viruses does not reach the minimum level of detection. People that gave those samples had such a strong immune response to that particular variant that even the samples came back (false) negative.
  5. There is probably not much cross-immunity. There will be in time, as humans adjust to new and new variants, but there’s none or hardly any at the moment.
  6. That is why the Covid death curves of the various epidemic waves are very similar. It may occur that some of the newly emerging variants will be more deadly than its predecessors, but it is also certain that vaccines are more or less effective (for now) against the strains that are currently in circulation.
  7. The variants that we know of will not lead to a mass mortality event. But, as there is no herd immunity, that 0.1 to 0.2% will die of coronavirus-related diseases one, or two, or three times every year. And when you add these numbers up…that’s a lot of dead people.
  8. Vaccines will provide protection for a while, but as new variants emerge, new vaccines will be required, just like in the case of the influenza virus. After a while, though, there will be dominant strains, our immune system will adjust to them. And by the time coronavirus becomes as docile as a simple cold, those that were sensitive to it will already be six feet under.
  9. If this hypothesis is correct, it makes a lot of sense to get your COVID-19 shots. The other forms of protection, however, are not worth a lot, as the theory is that everyone was or will be infected at a point. Just like in the case of a common cold. Just to be clear, this does not mean that mask-wearing, social distancing, and certain lockdown measures are bad. They can, in fact, delay the progress of an epidemic (or wave if you like), only vaccination beats them in usefulness. The key word here is ‘delay’. Coronavirus is still far from become as docile as the common cold, it is still gaining strength. During this ‘taming’ process everyone that was vulnerable / susceptible to SARS-CoV-2 will either gain immunity or die. For all the others a coronavirus infection is already just like common cold.
  10. And finally, we need to get our immune system in order. Quit smoking! Stop drinking! Lose weight! Get enough sleep! Be in your best shape possible! Quit drugs! Get vaccinated! And hope for the best!

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