Reprinted from RedFlagsWeekly.com June 23, 2003
By David Crowe
"Tests indicate you may have a chance of being infected.
There is a probability that, if infected, you will become ill within
the next 10 years and a possibility that you never will. If you
take the drugs, there is a significant risk of great decline in
your quality of life, and a possibility that the drugs will kill
Although it might be the truth, you are unlikely to hear a doctor
saying any of the above, because neither the doctor nor the patient
can deal with the uncertainty that it admits.
Technology is the practical application of science, and one of the
major distinctions is its need for certainty. Studying semiconductor
physics can be a beautiful thing, but it remains pure science until
a discovery results in products that can be reliably manufactured
and used. Biological systems, especially human beings, are far more
complex and less predictable than inorganic systems. Medicine, being
the practical application (technology) of human biologic science,
requires a high degree of certainty before new discoveries can be
Unfortunately, a feeling of certainty can be manufactured, and there
are many motivations to do so.
On October 12, 2001, a CDC scientist phoned then mayor of New York
City, Rudolph Giuliani, to tell him that, "with a high degree
of probability", a sample of skin from an NBC employee in Manhattan
was positive for cutaneous anthrax. The CDC scientist had this confidence,
because he had confidence in a test that a colleague had previously
developed. But this was not good enough for Giuliani. "Don’t
give me that stuff. Is it anthrax or not?" An unqualified "Yes"
from the CDC scientist kicked off the anthrax crisis in New York
City. [Altman, 2001]
A "No," under the circumstances, would have been almost
impossible. The consequences for the CDC and Giuliani, if others
had later confirmed anthrax, would have been devastating to their
careers. While reporters might have questioned the accuracy of a
"No," there was not a whisper of dissent on the "Yes."
Medical tests are a common way to manufacture certainty. A test
usually measures a ‘surrogate marker’ for a condition,
something that is otherwise invisible, or at least much more difficult,
expensive and time consuming to find directly. A nicely packaged
test can instill confidence and, in a sense, create a disease when
a positive test result is accepted without any symptoms being present.
An HIV test is perhaps the best example. A positive test is devastating
to most people, particularly those who are outside the traditional
risk groups and completely unprepared. Feelings of doom come, not
surprisingly, even to those who are perfectly healthy at the time
of the test [Gala, 1992].
Desperate feelings lead to desperate actions, and, for HIV, the
desperate action is to take AIDS medications. Antiviral drugs have
fatal side effects, and even those who avoid that are likely to
experience a destruction of their quality of life, even if they
were completely healthy at the time of the test [Goodman, 2002].
Obviously, the doctor and patient must feel certain that tests are
accurate. If the patient was told that there was only a 90% certainty
that the test was accurate they might be much less likely to take
medications carrying such risks.
The almost universal impression among scientists, the media, governments
and the general public that HIV tests are accurate enough to stake
your life on is, strangely enough, so strong because there is no
absolute measure against which the tests can be validated. Instead
of accepting this as uncertainty over whether the tests are meaningful,
it is accepted as lack of proof that they are not highly accurate.
All that Robert Gallo’s and Luc Montagnier’s research
teams found was a high correlation between their antibody tests
and AIDS. People with AIDS had a high probability (88% in the case
of Gallo [Sarngadharan, 1984]) of testing positive, and people without
AIDS had a very low probability of testing positive. A huge conceptual
leap over a chasm of uncertainty was to conclude from this evidence
that a positive test in a healthy person proved they had a condition
that would inevitably kill them.
The science of HIV testing has progressed since then, but only in
technological ways (such as the use of monoclonal antibodies); the
original logical uncertainties still exist. Almost every scientific
paper concerning HIV tests still uses antibody tests as the "gold
standard." This is unusual because antibody tests, even if
one ignores the possibility of cross reactions, can only prove past
exposure to a virus, not current infection.
HIV antigen tests, which are more direct, are only positive in about
half the people who are HIV-antibody positive [McKinney, 1991; Semple,
1991]. This finding is explained away through an immune reaction
that masks the antigen. But, this implies that the HIV infection
is conquered, which is not compatible with the notion that HIV infection
is incurable. Virus cultivation, often erroneously called 'isolation'
is an even older method than antibody testing for HIV, but apart
from being time consuming, expensive and difficult to perform, it
also is negative quite frequently, and a positive antibody test
usually trumps a negative culture [Layon, 1986] (and vice-versa
[Eur Coll, 1991; Imagawa, 1989]).
The major new test since the early days of AIDS is the Polymerase
Chain Reaction, often called 'viral load' when used for HIV tests.
This also takes a back seat to antibody tests [Roche, 1996], likely
because it is so ultra-sensitive that the risk of a false positive
is high. Furthermore, detecting a snippet of genetic material (RNA
or DNA, depending on the type of test) does not prove that the entire
genome is present, and obviously does not prove that infectious
virus particles are present. This test is particularly uncertain
because the genetic material does not come from purified virus.
Even accepting the test’s ability to specifically detect HIV
DNA or RNA, one research team estimated that only one infectious
virus particle was present for every 60,000 measured by viral load!
[Piatak, 1993; Roche, 1996]
All HIV tests are indirect, even virus 'isolation' by culturing.
Consequently, some 'gold standard' is necessary to validate them
[Cleary, 1987; Abbott, 1997; Meyer, 1987; Daar, 2001; Papadopulos,
2003]. The only standard that is reasonable for a virus is actual
purification direct from body fluids of people who are HIV infected
and the inability to purify from people who are not. Virus purification
would allow the proper characterization of the virus, so that antigens,
antibodies, DNA and RNA that are generally believed to be from HIV
could be proven to be from HIV (or not).
Without a ‘gold standard’ for HIV infection the only
way to validate the test is by repeating the test or by comparing
it against different (also unvalidated) tests. This can establish
the reproducibility of the test, but not its specificity (ability
to react with the target and therefore avoid false positives) or
sensitivity (ability to react to cases of infection and therefore
avoid false negatives).
US army researchers claimed that the specificity of HIV antibody
tests was only 1 false positive out of 135,187 tests [Burke, 1988].
However, although they claimed to have established a high specificity
for antibody tests, they were actually verifying only reproducibility,
and the researchers did not actually prove that the 15 people from
this low risk population who were deemed to have had true positive
tests actually had the virus in them.
Modern diseases that are blamed on a virus are often little more
than the test because the disease can exist without clinical symptoms.
There is an average of 10 years between becoming HIV positive and
the first signs of AIDS in both rich countries [Munoz, 1995] and
poor [Morgan, 2002]. In that time the HIV test is the only sign
that anything is wrong. Worse yet, a low CD4 cell count test can
result, in the United States, in a diagnosis of AIDS (not just HIV
infection), again without any clinical symptoms. But even without
symptoms a diagnosis of HIV infection or AIDS will still often result
in treatment because of everyone’s confidence in the tests.
Other viral diseases might not have a long incubation period, but
the test still plays the prime role in defining the condition. West
Nile disease, for example, is associated with no illness in the
majority of people who test positive, and serious illness in only
about 1 out of 150 [Petersen, 2002]. The symptoms, when they do
occur, are indistinguishable from many other viral diseases [CDC,
2002]. This has not resulted in a call to question the accuracy
of the tests. Instead, the certainty that any symptoms found along
with a positive test are due to the virus is so great that when
the symptoms are uncharacteristic scientists want to add them to
the definition, rather than to ask whether the tests are accurate
and whether presence of a virus is proof of pathogenicity [Glass,
2002; Leis, 2002]
One of the strange phenomena with HIV and AIDS science was overwhelming
feeling of certainty that crept over scientists in the mid-1980’s.
Only 3.4% of papers in 1984 associated a reference to Gallo’s
original 1984 papers on HIV (HTLV-III) with "explicit and unqualified"
assertions that HIV caused AIDS but this increased to 25% in 1985
and 62% in 1986, even when these papers were referenced alone. [Epstein,
Kary Mullis, who received the 1993 Nobel for Chemistry (ironically
because of his invention of the Polymerase Chain Reaction) has asked
many scientists for a set of references that constitute proof that
HIV causes AIDS [Duesberg, 1996] and has not yet received them.
Yet, even without this proof being written down in a scientific
paper, certainty still reigns.
SARS illustrates how quickly researchers can manufacture certainty
today. The mainstream media (which claim to be "responsible")
have ensured us that everyone knows SARS is caused by a Coronavirus.
Reports from Dr. Frank Plummer, one of Canada’s top virologists,
that a diminishing percentage of patients (30% by mid-April) are
testing positive do not dissuade them from this belief [Altman,
2003]. Everyone knows that there is no possible explanation for
all the patients having some connection with the original cases
other than an infectious agent, even though for some outbreaks there
was no solid connection, and tautologically, the epidemiologic connection
is supposed to be present before diagnosing SARS (as opposed to
some other disease with similar symptoms). And, everyone also knows
that there is no other explanation for the severity of the disease,
certainly not the new phenomenon of aggressive prescription of steroids
and the antiviral ribavirin that occurred as the fear of the outbreak
spread [Koren, 2003].
What HIV/AIDS science took two years to do, SARS science took only
two months to accomplish. I predict that a Coronavirus test will
soon become part of the SARS case definition, which will immediately
create a 100% correlation between the Coronavirus and SARS symptoms.
Just as with AIDS, the same symptoms without a positive test will
be another disease, and not taken nearly as seriously.
People demand simple answers to complex problems and modern medical
science delivers. We are told that tests are highly accurate, that
drugs will cure conditions or, if that is not possible, that they
are the best bet. We are told that environmental conditions play
little role in modern, emerging diseases. Alternative therapy is
scoffed at because it has not been ‘proven’ effective
through randomized, placebo-controlled clinical trials.
The fundamental reason why this confidence game continues to be
played is because of human laziness. It is much easier to learn
about science by rote than by examining evidence and making up one’s
own mind. Obviously, not every pronouncement on science can be taken
seriously, so the status of a person or publisher becomes the way
to distinguish between "good science" and "junk science."
Many people do not believe that they have the ability to understand
scientific papers. The media, even most science reporters, are much
more productive if they also adopt this attitude. Among scientists,
there is a hierarchy that is constructed from the anonymous peer
review system for publication and grant support. This allows longer-serving
officers of science to anonymously subvert the attempts of younger
scientists (and outsiders) to reappraise current dogmas, by denying
them the ability to publish and obtain research funding.
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