Prevalence and Epidemiological Considerations

 

A Pandemic of Heart Attacks and Mental Ill Health?

After catching the virus described on this website, and after witnessing the permanent ill health conditions this pathogen triggered in myself and 30+ other people who caught it, my concern was that this virus might spread as a slow pandemic, and cause a worldwide increase in the mental and physical diseases this virus can induce (like sudden heart attacks, chronic viral myocarditis, anxiety, depression and anhedonia).

So here we examine the possibility that this virus might spread globally in a slow pandemic.

The Prevalence of This Virus

Evidence indicates the virus described on this website was not prevalent in human populations at the time I caught it in 2003. This can be deduced from the fact that nearly everyone I know who was significantly exposed to this virus (including people of different nationalities) eventually contracted it. This demonstrates no one had this virus already in their body (if they had already had the virus in their body from an exposure earlier in life, they would not have been infected when exposed to it a second time, as you usually cannot catch the same virus twice). So the fact that everyone seemed susceptible to being infected with my virus implies it had a very low prevalence in the human population around the time I first caught it.

Incidentally, this low prevalence information is a useful fact in terms of identifying this virus: its low prevalence allows us to rule out viruses that are known to be already widespread. For example, just with this low prevalence information, we can rule out Epstein-Barr virus as a possible candidate, as Epstein-Barr virus has a high (95%) prevalence in the adult population.

Pandemic Calculations

So the virus described on this website had low prevalence in the human population at the time I caught it. Obviously I have no precise information, but just as a starting point for calculation, let us assume that only say 1 in 10,000 people in the United States or Europe had this virus at the beginning of 2010. Taking the US population as of the order of 300 million, this equates to around 30,000 people infected in the US in 2010. This is just to give us a very approximate initial prevalence figure to work with.

Now, my own observations on my local group of infectees indicate that on average, a person infected with this virus goes on to infect around 3 more people within the first year or so, but after that period, my guess is not many more people get infected from this first person (since the sore throat and sinus/nasal infection clear up to a degree after around a year, and may therefore shed less viral particles).

So as a mathematical simplification, let us say that on average, every person infected with this virus will infect 3 new people within the first year, but will not infect any more people after that. These 3 newly infected people will each go on to each infect 3 further people in the second year. So you get an increase in numbers of infected individuals in the following pattern: year zero 1 person infected, one year later 1 + 3 people infected, two years later 1 + 3 + 9 people infected, three years later 1 + 3 + 9 + 27 people infected, and in general, N years later 1 + 3 + 32 + 33 + 34 + … + 3N people infected. This expression for the number of people infected by the Nth year is the sum of a geometric series, a sum which is given by the formula (3N+1 – 1) / 2.

So as you would expect, this formula indicates an exponential increase in the numbers infected. And clearly, if we start with S people infected at year zero, then N years later there will be a total of S x (3N+1 – 1) / 2 people infected.

So taking the beginning of 2010 as our year zero, when we have assumed there were S = 30,000 people infected in the United States, this means that N years later there will be 30,000 x (3N+1 – 1) / 2 people infected. So let’s see how this exponential increase in the numbers of infected people pans out, using our formula.

In 2010, we are assuming 30,000 people infected with this virus, so:

by 2011 (N = 1), we have 30,000 x (31+1 – 1) / 2 = 120,000 people infected with this virus
by 2012 (N = 2), we have 30,000 x (32+1 – 1) / 2 = 390,000 people infected with this virus
by 2013 (N = 3), we have 30,000 x (33+1 – 1) / 2 = 2.2 million people infected with this virus
by 2014 (N = 4), we have 30,000 x (34+1 – 1) / 2 = 3.6 million people infected with this virus
by 2015 (N = 5), we have 30,000 x (35+1 – 1) / 2 = 11 million people infected with this virus
by 2016 (N = 6), we have 30,000 x (36+1 – 1) / 2 = 33 million people infected with this virus
by 2017 (N = 7), we have 30,000 x (37+1 – 1) / 2 = 98 million people infected with this virus
by 2018 (N = 8), we have 30,000 x (38+1 – 1) / 2 = 295 million people infected with this virus

In fact, as the infection prevalence gets closer to population saturation, the rate of increase will be slower than the figures given above, since with the majority of people infected, it becomes harder to find uninfected individuals to infect (mathematically, the increase then become sigmoidal rather than exponential). Nevertheless, this calculation suggests that by around say 2020, most of the US population will have this virus (and likewise in other countries). This is of course a very approximate calculation, more for illustrative purposes, rather than for providing very precise figures. That is to say, the spread of this virus may be faster or slower than calculated here; but this calculation does indicate that it might be wise to instigate research into this virus right now, rather than wait until it may have become significantly more prevalent.

Advertisements