Logical inconsistencies on Covid-19 and the need for a vaccine?


It's all about the data?

There are two schools of thought on this. Every individual matters, every life matters and protecting just one life should be paramount? Then there is the collectivist brush of "The Greater Good", where we are selfish and uncaring if we want to go about our lives risking others? Once data is used it dehumanises individuals into statistics. At the same time, to react to every single story with horror and upset disproportionately distorts the real story.

Data can be made to lie, but what is known as multivariate analysis, running different dimensions through models should be able to separate the wheat from the chaff. There is a saying in finance - "History never repeats, but it rhymes." There should be more than enough history for the so-called experts to have a far better response to this Covid-19 than what we have seen. 

Once this has unfolded, a lot more experts will question and analyse this and publish it. If you are not technical or a data person, at least try to read more into it.

My thoughts on Covid-19

I tend to read a lot and watch a lot of YouTube. I also force myself to read mainstream media and occasionally watch Regular news media - it is really hard to do because the whole experience is designed to control your thoughts and perceptions. One way to start to understand how mainstream media is so pervasive, is to force yourself to read a different political paradigm. If you are left-wing and say socialist, read the Times and the Daily Express. If you are right wing and watch Fox News, watch MSNBC and the BBC. What you will find is a completely different narrative on exactly the same events, yet certain commonalities resonate.

For me, it was more to do with the financial media. I often read financial media as I worked in finance. Often, what was being said in the more common financial press was entirely incorrect, distorted, untimely or if accurate - inaccurate in their conclusions. Other times the reasons given to an event could never be proven.

The financial industry though paid little attention to that media because that wasn't what mattered to them. There is no conspiracy here, but this is kind of how media works - the real news is never in the real news and this seems to be the case with Covid-19.

I knew a lot of bad about the Coronavirus and was exceptionally fearful before it was officially announced as a pandemic by the WHO. As I have looked more at the data, run various calcs on it - simple stuff to be fair, I now don't take it seriously at all. It doesn't mean I am going to start hugging random strangers as these people are petrified.

My goal is to write a series of models to really dive into this and then publish this information.

The following can be held as being my opinion at this moment in time. It is subject to change as more information comes in - this is what scientists do.

There is no need for a vaccine

  • Many people have survived from the alleged Covid-19 (which stands for Certificate of Identification Artificial Intelligence). Boris Johnson himself has survived Covid-19.
  • We cannot predict how viruses can mutate in the future.
  • Whilst am not an anti-vaccinator per se, a lot of data shows that testing undertaken by the WHO, Gates Foundation has maimed (paralysed) hundreds of thousands of children in Africa and India. Read it for yourself.
  • Vaccines don't have a 100% success rate either.

There was no Covid-19 virus

This seems incredible to hear, but it seems almost impossible that Covid-19 exists as a new strain of Coronavirus by the methodologies for testing. Just read the points without jumping up and down like Yosemite Sam;

  • Covid-19 was never isolated.
  • Covid-19 doesn't fulfil Koch's postulates of what an infectious disease is (remember - viruses are dead).
  • There is not a valid test for Covid-19. 
  • Most deaths are being misreported or tagged as Covid-19.

What about the number of doctors and nurses who have died in the UK?

My understanding is there were 300,000 doctors in the UK in 2019? I was reading that there are 300,000 doctors registered by age. I read that 58 doctors have died from Covid-19. That is a 0.0001% mortality rate. We could assume the percentage of doctors who had direct contact with Covid-19 patients, but they travel to work, they can often work long hours, could have depleted immune systems? Indeed, many doctors have super immune systems as they are continually exposed to pathogens. Remember the doctor who unfortunately passed away who was 58 and worked at Moorfields Eye Hospital - he was 58. Isn't 58 within the age group Boris Johnson is going to tell people to stay in their homes for longer in the coming days?

In the US alone - 99000 people die from being inside hospital environments. A percentage of those will be doctors and nurses.

I attached a chart at the end of this post.

What about the number of bus drivers and frontline staff who are dying of Covid-19?

What we find is, that as unfortunate as any death is. There is no significant difference between different people dying/surviving whether they do or don't have Covid-19. What would be very interesting would be to know the number of police officers with Covid-19, who seem to love getting into vans and range-rovers in very tight spaces and invading the public's personal space whenever they can? There doesn't seem to be a more happy bunch of people to cramp themselves up and annoy this shit out of people.

But Boris Johnson got it - many people are critically ill in Intensive Care Units?

There is something and it is probably (yes, I say probably) a form of coronavirus or some flu-strain which is severely affecting a small percentage of people. The reason everybody is so upset about it is because it is often, not treatable. Indeed, more success has come from not following government guidance and World Health Organisation dictates.

Unfortunately, some people are going to catch and die from all kinds of diseases every year. Because Boris Johnson got it, and survived - a mid-fifties unhealthy specimen, it means other people can get it and survive? This level of cognitive dissonance is never greater than in the all fearing general public.

Would you kiss somebody with Covid-19, or sit in a room of Covid-19 people?

Am pretty choosy to be honest and restricted through matrimony. However, we normally sit on planes, undergrounds, supermarkets, trains, ski-lifts with all kinds of disgusting specimens. Picking up my kid from nursery is where I probably got what I think was Coronavirus back in January. I wouldn't have a problem visiting a covid-19 ward in a pair of beach shorts a t-shirt.

You deserve to get Coronavirus and not get treated?

Thanks for understanding.

What about 5G?

I really don't know about that. My feeling is what we do tend to see is a small number of people affected by environmental shocks. Remember Leukaemia and Electricity pylons? There was apparently no link found between them and yet to the people who lived near them and suffered and died blame these pylons. My feeling is, we don't have the language to interpret these types of occurrences - artificial intelligence and machine learning can find unrecognised patterns, but hasn't got the language to explain it to humans. Statistics cannot at this moment in time explain why there does seem to be epicentres of events, yet when normalised across a wider cohort, these events don't seem statistically significant.

Could it be the same with the vaccination treatments on children in Africa? In today's money, there are 472 million children in India under the age of 18. If we imagine that say when Bill Gates started vaccinating those kids in India - did they vaccinate all 300 million (at the time) or just run trials?

What about Social Distancing and the wild-predictions now no longer being that significant - did social distancing work?

I am going to say. Under no circumstances has social distancing been proven to work. I will propose a fairly simple model to explain how.

  • Identify which countries undertook social distancing versus those who didn't.
  • Try to identify some data on pre-existing conditions and normal health incidents (mortalities). For example, NHS data exists for many years previous.
  • Adjust for age cohorts against the infection rates, mortality rates, and asymptomatic.
  • We have heard that ethnicity plays a part also.
  • Run statistical variance and significance on this data and also run clustering to try and see if there are groups where this exists.

If we do this, we will run into the same problem drugs companies have proving their drugs cures or treats a condition.



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