Dr. Weeks’ Comment: Let brilliant lawyer Paul Cook explain the math in this superb article – the math explain reality. Here is the source and entire article.
Coronavirus No More Dangerous Than Natural Causes of Death? The Math Says So. By Paul Cook
Tuesday, March 31, 2020
Galileo Galilei Demonstrating His New Astronomical Theories
At The University Of Padua is a painting by Felix ParraAfter applying statistics and equations to this alleged Covid-19 (Coronavirus) pandemic, it appears clear to me that this viral epidemic is no more dangerous than dying from natural causes – the kind we face in every day life – like a drunk driver or the flu. Originally, I proposed two theories. My first hypothesis was that this was a new kind of virus. Then my second theory was that this could be caused by 5g radiation technology, and I explained the physics and how it could harm white blood cells. But I kept wondering, which one was it? Or perhaps it was a combination of both, or perhaps there were locations where the super virus hit and other locations where it was 5g driven. Maybe it wasn’t even real.
Given all the information and misinformation out there, it was frustrating to get to the truth for me. There’s so much speculation and theories and fear panhandling out there. Conservative economists, like Martin Armstrong maintained that this was no more dangerous than the standard flu. Yet, all the news and government were telling us that people were being infected and dying every day. Even when they didn’t know, the media said this 17 year old boy MAY have died from corona. How irresponsible is that to spread panic without having that fact verified first? That’s not journalism.
Even CBS had to admit they made a mistake when they aired that hospital beds in New York were overcrowded, when they recycled an image of an Italian hospital, instead.
Since the outbreak of the alleged pandemic, conspiracy theorists have stated that this virus was made in a Wuhan virology lab.
And it’s a fair theory. If there was some new super germ out there, it plausibly could have been transformed in a laboratory. In 1928, Frederick Griffith announced to the world that he engineered his first bacteria – taking a harmless bacterium and splicing into it a deadly gene. He then injected it into mice – which later killed the mice. It was the first transformational experiment the world knew of, and so, it’s plausible that biological weapons can be created in labs.
In fact, Dr. Arthur Boylston argued in his book, Defying Providence, that the British unleashed both smallpox against the Native Americans and colonists in the Revolutionary War to conquer them both. Had the colonists been ignorant of inoculation, the Queen might be ruling us today.
Then there’s the xenophobic and anti-Chinese theory that people in Wuhan eat bat soup, and that’s what gave the world corona. One, if you boil any animal that kills anything living. So; it doesn’t make much sense. Next the media will tell us that maybe they were eating them alive in the seafood market. (Not believable.) I haven’t been to Wuhan, but I’ve been to a lot of Chinese seafood markets and have not seen a bat for sale. By the way, the Lancet stated that alleged Patient Zero never even went to the seafood market, and some of the first 13 people who caught Corona, had nothing to do with it.
Fire in a crucible tests golds.
The truth must be tested too.So; how do you know what’s true? The Scripture is clear, it states: “Put all things to the test: keep what is good”. (1 Thess 5:21). This is a command, but Christians are some of the worst in putting this to practice. How do you design such a test?
The challenges of doing this, given the information out there was incredible for me. I can’t go to the field, like a hospital, because if this was real, then I could risk infecting family members. But there’s no substitute for firsthand observation. I’ve learned this over and over again as an IT analyst, scientist, and attorney. But without it, how do you filter out who’s telling the truth and what is true?
On March 26, 2020 – I even emailed the Director of the Center for Disease Control, Robert R. Redfield and asked him how Covid-19 testing worked. I wrote:
Dear Dr. Redfield:
I‘m a journalist and need some help understanding the testing for Covid-19, particularly the tests you sent to California. (1) Is this a PCR or an antibody test? (2) If this is a PCR test – what genes are you sequencing? And how did you identify these genes? How are these genes different than other genes present in other coronaviruses? (3) If this an antibody test – which strain of Covid-19 was used for this test? Will an antibody test work on different strains of Covid-19, which have been identified?
As expected, no response. I was running 7 miles in my hill, and my owl, who I named Ruru (Maori for owl) came to me. And then it hit. I had to return back to my work in statistics and math applied to biology.
After comparing the statistics and applying Reverend Thomas Robert Malthus’s equation on the corona epidemic, this disease (if one exists) is no more dangerous than life before corona.
The Statistics and Logarithmic Equation
The first question to answer was whether Covid-19 was killing anymore people than natural causes. I already knew it wasn’t, but there was a criticism that viruses grow exponentially. Therefore, the argument went that in its early stages it needed to be contained before it got worse.
The application of math to biology.
To test whether Covid-19 was anymore dangerous than the regular flu, I determined the rate of Covid-19’s related virus SARS (Severe Acute Respiratory Syndrome). Then by using the statistics that the media was reporting on regarding the Coronavirus, I determined the rate that this virus was and is spreading. Covid-19’s rate of infection and rate of mortality is far less than that of SARS and may be exactly that of the common cold or flu. The problem with calculating the rate of proliferation with the flu is it’s hard to estimate how many people actually are infected each year and how many die alone from it.
I picked six populations to conduct my study. Populations were selected by those most infected. They were New York City; Los Angeles County(because I live here); Lombardy, Italy; Madrid, Spain, the Diamond Princess Ship; and Wuhan. Wuhan was problematic, because critics allege that the numbers are much higher than the government of China was reporting. Therefore, I took the highest numbers to make the point.
I started with the reported date of Patient Zero in each population and made the cut off date either today or yesterday.
Here’s what I found. With the exception of the Diamond Princess – the death rates by Coronavirus are much lower than the daily mortality rate per city. For instance and on average, 129 people die every day in New York City. (I even included the negligible numbers – such as deaths from murders, traffic accidents, and suicide.) Take a look at the chart below.
RegionStartEndDays elapsedInfectedDeath RateDeadNatural Deaths ExpectedNatural deaths Annual Mortality RateTotal Population in (M)Median AgeFor this period.Expected per day.
[JG: Easier to read the table in the link of the story.]
if you look, places like Lombardy and Madrid just have higher death rates. It probably has something to do with the fact that there median age is a lot higher than ours. In short, more people are dying in Lombardy than other regions, even before Corona hit. The statistics were taken from 2017.
Therefore, less people are dying from Covid-19 then is supposed to die per day. Now, I don’t have the non-Covid-19 deaths. But it appears to me, that these numbers look like that the flu can be killing the sick and elderly.
The Statistics and Logarithmic Equation
To compare the rate, I decided to use the rate of growth from SARS – which killed on average 17-21% of the people it infected. I excluded China’s data, because there were too many reports of it not being accurate. Note that Hong Kong had the highest growth rate – perhaps because it was the origin of the disease and quarantine measures were not yet in place.
Here’s what I found out about SARS.
CountryStart DateEnd DateDays elapsedInfectedDeadMortality rateRate of InfectionRate of Mortality
In contrast, the Covid-19 rates of infections and death are significantly lower than SARS, suggesting it is not as contagious.The average time required to contain the epidemic took about 100 days. The average rate of death is 17.1%. The rate is about .06 for infection and .043 for mortality.
Even the mortality rates fall for New York City, Los Angeles County, and the Diamond Princess fall much lower than the rate of SARS. In the United States, the death rates are below 2.5% in contrast to the average mortality of 17.1% of SARS. Although Lombardy and Madrid have higher death rates from the virus, as already mentioned earlier, most probably because of their aging population, they already had higher mortality rates compared to the United States.
It’s interesting to know that the Diamond Princess had the highest rate of infection over time. Furthermore, 10 people had died, instead of the expected rate of 2 (and 2 is using the aging population death rate; it would’ve been zero with a younger population death rate). But on Diamond Princess the median age was 69. It would be useful to know how many people die on cruise ships that have an average age of 69.
Anyways, here’s my chart on the rates of infection and mortality. They are nothing like that compared to SARS. Diamond Princess, nonetheless, has the highest infection rate.
RegionInfection rateMortality rateDeath RateNY City0.360.242.4%Los Angeles0.120.061.8%Lombardy0.230.1916.2%Madrid0.170.1412.3%Diamond Princess0.390.141.4%WuhanN/AN/A
Final Thoughts and ConclusionIn comparing the statistics with the annual mortality rate and against rates of growth from SARS, this Covid-19 virus doesn’t appear to be more dangerous than SARS. In fact, it’s lethalness and infection is much milder compared to that of SARS.
It’s also important to stress that this paper doesn’t say that a Covid-19 virus doesn’t exist. One may exist, but it doesn’t appear to be the pandemic that the government and media is constantly repeating and hammering at us. It even appears that this disease may not be any more deadly than disease or the natural rate of death each population has.
I admit, a number of assumptions had to be relied upon, since the data is not accessible to me at this point. More data can be useful in knowing how many people are dying in these regions per day – not just those who have fell because of Covid-19.
I’ve decided to keep my old theories on my blog – instead of take them down. A thorough scientist and lawyer drafts up the most number of plausible explanations and crosses them off the list, as I’ve done over the last few weeks.
One useful statistical information that could help is accurate data on the flu on a large population. From there, an infection rate and mortality rate might be calculated. But it’d still be difficult, because to calculate, since it appears that the CDC data fluctuates a lot. According to it, in 1976 only 6,309 people died of the flu. Now, estimates can be as high as 60,000. Why the big jump in data?
Finally – the Diamond Princess ship had higher than normal deaths and the highest infection rate compared to the other populations. More needs to be investigated as to why. Was it because people were so close to the new 5g technology on board? Was it the aging population? Was it a mutated virus?
To me – the factors from the other populations are not suggesting to me this was a new super virus. But who knows? Some new data may come out, and I’ll be revising what I believe yet again. That’s where I am with my thinking for now.