April 22,
2020 "Information
Clearing House"
- Posted on the Internet yesterday is a study dated
11 April 2020 that finally addresses a type of
investigation avoided by the energetic creators of
hype and fear on television and elsewhere about an
illness resulting from a virus called SARS-CoV-2.
Using a sample from Santa Clara County, California,
home of Stanford University, the study tested the
blood of 3,330 people, using a new testing technique
to look for antibodies that are expected to exist if
the virus has been inside a person, whether they had
any symptoms or not.
In this
case, by using the math of statistics, the attempt
is made to extend the observed results to the
population of a specific area, to try to figure out
how many people in the area had the virus in them at
some point, even if they have shown no symptoms.
Then -- using the population of the area, the
statistical number of persons who had been exposed,
the number who are thought to have the virus by
other testing and clinical observation, and the
number whose death was caused by the virus (a
difficult determination) -- better opinions can be
developed. This use of statistical sampling can try
to describe reality in a more correct way than the
so-called "mathematical models" promoted in the
media that whipped up hysteria about the virus, and
those models could politely be called wild
speculation. The models were used to justify
draconian and illegal orders by governors and mayors
that destroyed incomes, closed businesses, and did
not accurately and constructively address the
problems that may be caused by the virus.
When you
have an idea about how many people have developed
antibodies and are still alive, whether having had
symptoms or not, you can begin to see the status and
effect of the virus. Furthermore, people who have
naturally developed antibodies have usually become
immune. You can also calculate the fatality rate of
the virus in a better way.
One of the
authors of the study is John P.A. Ioannidis, who is
a professor at the Stanford University Medical
School [1]. He kicked up some controversy in an
article in March when the hype about the virus was
escalating by saying, "The
data collected so far on how many people are
infected and how the epidemic is evolving are
utterly unreliable" [2].
Santa Clara
County, California, is said to have a population of
about 1,943,411. The study estimated that between
48,000 and 81,000 people had been infected there.
And, "The
reported number of confirmed positive cases in the
county on April 1 was 956, 50-85-fold lower than the
number of infections predicted by this study".
Using the results from the sample, an estimate was
made about a fatality rate (page 7)--
"If our
estimates of 48,000-81,000 infections represent the
cumulative total on April 1, and we project deaths
to April 22 (a 3 week lag from time of infection to
death [reference note 22]), we estimate about 100
deaths in the county. A hundred deaths out of
48,000-81,000 infections corresponds to an infection
fatality rate of 0.12-0.2%. If antibodies take
longer than 3 days to appear, if the average
duration from case identification to death is less
than 3 weeks, or if the epidemic wave has peaked and
growth in deaths is less than 6% daily, then the
infection fatality rate would be lower. These
straightforward estimations of infection fatality
rate fail to account for age structure and changing
treatment approaches to COVID-19. Nevertheless, our
prevalence estimates can be used to update existing
fatality rates given the large upwards revision of
under-ascertainment".
Dr.
Ioannidis has said that the death/fatality rate for
seasonal influenza is about 0.10 percent. Thus, if
this study presents the situation realistically, the
fatality rate for COVID-19 is similar to a flu
season, at least in that part of California.
Are You Tired Of
The Lies And
Non-Stop Propaganda?
The text of
the study is eight pages long, before the references
and graphics. It has detail like a study of its
type should. As in all statistical studies, there
are side issues, such as how complete and
representative the sample of persons is, how valid
the testing method and statistics used are, etc. In
this one a new testing technique was used that has
not yet been approved by the Food and Drug
Administration (FDA), but the article describes how
the test kit was tested for the study. Even though
it contains some statistical terminology, the study
is worth reading--
A respected
scientist in Germany became so frustrated with the
lack of scientific discussion about the virus and
the restrictions imposed in the country, that he
wrote an open letter to the Chancellor of Germany
and discussed it in a video on 29 March. Dr.
Sucharit Bhakdi states that he is a microbiologist
and infectious disease epidemiologist who for 22
years was chairman of the Institute of Medical
Microbiology and Hygiene at Mainz University, where
he researched the pathogenesis, diagnosis, and
therapy of infectious diseases. He presents five
questions. Dr. Bhakti speaks in German, but if you
click on the "cc" button at the bottom of the video
display area, it will show some subtitles in
English--
In his
video, Dr. Bhakdi says that two years ago there were
20,000 flu deaths in Germany (a very large number
for that country), and no stringent preventive
measures were implemented at all. Germany's
population is around 80 million. The U.S. population
is estimated to be around 330 million.
Around the
second week of March, the situation here about the
virus changed into one of bureaucratic, media,
political, and financial interests. The presentation
in mass media has shifted into a version of
agitating propaganda (agitprop). Politicians and
bureaucracies do not want to admit they made a
mistake or did something wrong. Because mayors and
governors jumped to conclusions and issued
unnecessary and destructive orders, they are now
stuck, and do not want to cancel their decisions
that destroyed incomes and harmed the well-being of
people. I tried to figure out unemployment
insurance claim numbers, but charts by the federal
Department of Labor are unclear and numbers in
similar categories do not match. And of course
unemployment insurance claims are less than the
number of people who have lost income, business, and
work.
In accordance
with Title 17 U.S.C. Section 107, this material
is distributed without profit to those who have
expressed a prior interest in receiving the
included information for research and educational
purposes. Information Clearing House has no
affiliation whatsoever with the originator of
this article nor is Information ClearingHouse
endorsed or sponsored by the originator.)
