HIV/AIDS ILLUSTRATES COGNITIVE DISSONANCE

Oh that one would hear me! … and that mine adversary had written a book
King James Bible, JOB 31:35

As a target of debunking, a review may serve as well as a book, especially when it happens to be a review of what’s [not!] known about HIV/AIDS: “The spread, treatment, and prevention of HIV-1: evolution of a global pandemic”, by Myron S. Cohen, Nick Hellmann, Jay A. Levy, Kevin DeCock, and Joep Lange, Journal of Clinical Investigation, 118 [2008] 1244-54; doi:10.1172/JCI34706. The authors are heavyweight white-coated HIV/AIDS gurus, at least two of whom (Levy, DeCock) have been in this business from the beginning. The review is a textbook case of cognitive dissonance or, using Thomas Kuhn’s term, incommensurability (1).

Cognitive dissonance is the inability to “see”, or to comprehend the implications of, evidence that—objectively speaking—disproves a belief. Popular parlance might describe it as a state of denial. In Festinger’s classic study (2), when the predicted end of the world did not come on the calculated date, the believers concluded only that they had gotten something in the calculations a bit wrong, and their basic belief hardened rather than weakened.

“Incommensurability” signifies that researchers get so vested in the prevailing paradigm (i.e., dogma) that they cannot understand—quite literally cannot understand—how data could be interpreted in any other fashion than the one dictated by their belief.

Imre Lakatos (3) identified a strategy researchers use quite routinely to preserve belief in the face of contradictory evidence: they invent ad hoc explanations for each new piece of data that their theory cannot accommodate. They do not modify at all the basic belief (the “core theory”); rather, they attach to it ad hoc extensions that are not genuine corollaries because they are not inherently demanded by the theory, and they are not necessarily consistent in any natural way with other such ad hoc extensions of the theory.

This aspect of science is not part of the conventional wisdom about “science”; the popular myth, oversimplified and reverential, holds science to be trustworthy under all circumstances (4, 5). But illustrations of the fallibility of science abound, and HIV/AIDS dogma offers some cogent examples of cognitive dissonance, for example:

— The prediction that the AIDS outbreaks in major American cities would be followed by a spread into the general population was almost immediately falsified; yet the belief that HIV is sexually transmitted hardened rather than weakened.

— The prediction that a vaccine would be available within a couple of years after 1984 has been falsified over and again, despite the deployment of every conceivable strategy for design of such a vaccine, not to speak of untold millions of dollars expended. These failures have brought only increasingly strident calls to continue the attempts.

— The finding that the observed apparent rate of sexual transmission is far too low to explain the observed distribution of “HIV-positive” people was met by the ad hoc postulate that there must be some higher rate of infectivity during short periods; and this unobservable and unobserved infectiousness is nowadays dogma without the benefit of proof.

The cited review by Cohen et al. of the state of the art of HIV/AIDS offers further illustrations of accepting as fact, and disseminating as fact, things that are plainly not true, or that are unproven or unprovable, or that border on the absurd. As well, interpretations are invoked or implied that in other contexts would be immediately recognized as unwarranted, and racist to boot.

Simply wrong:

“[M]ale circumcision provides substantial protection from sexually transmitted diseases, including HIV-1”
Four references are given, but left unmentioned is the study by the Centers for Disease Control and Prevention (6), which found no such effect.
Even were such an effect to be suggested by correlations (which are the only available evidence), one might question a causal interpretation for its extreme implausibility with respect to “HIV-1”: how could circumcision protect males from an agent whose apparent transmission from female to male is already significantly lower than the apparent transmission from male to female, which itself is only about 1 in 1000? And given those almost immeasurably small apparent rates of transmission, how massive a set of trials would be needed to gather potentially convincing evidence?
As to circumcision protecting against known STDs, there is controversy extending over centuries and still not resolved to the satisfaction of all researchers, see http://www.circumcision.org/. For example, Professor Andrew Grulich (National Centre in HIV Epidemiology and Clinical Research [Australia]) reported recently at the Australasian Sexual Health Conference (Gold Coast, 11 October 2007) that there was no association between infection and circumcision status for any disease apart from syphilis (Thaindian News, 14 November).

Hardened belief in face of contrary facts:

“28 years after AIDS was first recognized…, HIV-1 requires continued global focus and investment”
Required, presumably, only because researchers want the money; for in the very same paragraph, Cohen et al. acknowledge that “global HIV-1 prevalence seems to have been stable since around the turn of the 20th century; and HIV-1 incidence peaked worldwide in the late 1990s and has been declining ever since”.

“Perhaps one of the most surprising aspects of the HIV/AIDS pandemic is the unequal spread of HIV-1”
Exactly; “surprising” because no infectious agent behaves like that.
On the one hand, “HIV-1 does not respect social status or borders”—because no sexually transmitted agent does—yet on the other hand, “racial and ethnic minorities, especially African Americans and Hispanics, are disproportionately affected… in Europe … many infections today are found among immigrants from sub-Saharan Africa”. The obvious contradiction between “no borders” and “racially discriminatory” can only be resolved by recognizing that HIV is not sexually transmitted; but those hewing to the dogma are incapable of that recognition, as Festinger, Kuhn, and others have pointed out.

“Africa has witnessed the full devastation of the HIV/AIDS pandemic”
but the population there has continued to grow at an annual rate of a few percent!

Swallowing improbabilities:

“DNA sequences of viruses in distinct clades can differ by 15%-20%”
and yet all of them are supposed to do about the same thing, with only minor differences in efficiency of transmission and “pathogenic potential”.
But in other contexts we’re told that human and chimp genomes differ by less than 1%, which suffices to produce quite major differences in the products of those genes.

“In Eastern Europe … brisk and severe epidemics emerged among injecting drug users in the late 1990s”
Grant—for the moment—that HIV can be transmitted via infected needles: how to conceive “brisk and severe epidemics” from shared needles? Try to picture the orgies of needle-sharing that would be required, particularly when two decades of experience have revealed that catching “HIV-positive” from needle punctures is even less probable than the 1 in 1000 chance via unprotected intercourse.

How HIV is transmitted in different parts of the world:

Since this figure sports precise percentages, the casual observer might be tempted to regard this as scientifically established fact, instead of pausing to recognize how absurd it is on its face. Marital sex responsible for half of all infections in the most affected area, and for a quarter of them in Asia—but not at all in Eastern Europe? Casual sex more significant in Eastern Europe than transmission among men who have sex with men, who remain in the United States the group most regarded as at risk?! Mother-to-child transmission (MTCT) virtually unknown outside Africa, including in Asia where “marital sex” represents a quarter of all transmission?? Doesn’t marital sex in Asia ever lead to pregnancy?!? Medical injections, too, virtually unknown outside Africa; and in Africa allowed just a few percent, ignoring the numerous publications by Gisselquist, Potterat et al. that indict such injections as a more plausible source of the “pandemic” than sexual intercourse?!?! Sex workers a substantial risk in Asia and Latin America, but far less dangerous than marital sex in Africa, and no risk at all in Eastern Europe?!?!?
To believe all this, one would have to also believe that these various regions of the globe are characterized by cultures and lifestyles so different as to bespeak the presence of altogether different species of Homo.
The text of the review article notes that “the US epidemic remains a paradigm of HIV/AIDS in the developed world”, indicates that sex among males is the greatest source of infections there, and suggests something similar for Western Europe. Those are the regions for which the data are most copious and reliable; and moreover North America is the region where HIV/AIDS originated, the veritable “mother of all HIV/AIDS regions”; so why are Western Europe and North America absent from the figure, whose source is “Bringing HIV prevention to scale: an urgent global priority”?

Subterranean racism:

“even in settings of generalized epidemics [i.e., self-sustaining in the population], the risk of infection with HIV-1 is … increased in persons with higher rates of partner change or who acquire classical … STDs … [or] who experience other significant exposure(s) to HIV-1, such as injection drug use”
— those people who also happen to be endowed with black skin, in other words, because all our data has shown for a couple of decades that they, everywhere in the world, are the most likely to test “HIV-positive”: “In the US, racial and ethnic minorities, especially African Americans and Hispanics… in Europe … many infections today are found among immigrants from sub-Saharan Africa”.

Note how the term “minorities” is deployed as a euphemism in mainstream discourse about HIV/AIDS (and in many other contexts too). In the United States, Asians constitute a much smaller numerical minority, and Native Americans an even smaller minority again, than either blacks or Hispanics. But Asians are significantly less affected by “HIV” than are white Americans, and Native Americans are affected not much more than Caucasians and significantly less than Hispanics, let alone blacks. “Minorities” serves as a euphemism for both “liable to reprehensible behavior” and “black”.

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This review article constitutes a goldmine of additional opportunities to debunk HIV/AIDS theory. It is replete with unproven assertions, for instance about “acute viral syndrome”, and contains the occasional nugget of acknowledgment that the most fundamental, central, matter of all remains as mysterious as when it was first declared that HIV destroys the immune system:

“To date, the destructive properties of HIV-1
have not been completely unraveled”.

If one omits the misleading euphemistic weasel-word, “completely”, this statement is demonstrably true. None of the many suggested mechanisms have stood the test of reality. No plausible mechanism for the destruction of the immune system by HIV has been discovered in a quarter century, following more than $100 billion spent on research.

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References:
(1) Thomas S. Kuhn, The Structure of Scientific Revolutions, University of Chicago Press (1970, 2nd ed., enlarged; 1st ed. 1962)
(2) Leon Festinger, Henry Riecken, & Stanley Schachter, When Prophecy Fails: A Social and Psychological Study of A Modern Group that Predicted the Destruction of the World, University of Minnesota Press (1956)
(3) Imre Lakatos, “History of science and its rational reconstruction”, pp. 1-40 in Method and Appraisal in the Physical Sciences, ed. Colin Howson, Cambridge University Press (1976)
(4) Henry H. Bauer, Fatal Attractions: The Troubles with Science, Paraview Press (2001)
(5) Henry H. Bauer, Scientific Literacy and the Myth of the Scientific Method, University of Illinois Press (1992)
(6) Millett GA et al., “Circumcision status and HIV infection among Black and Latino men who have sex with men in 3 US cities”, JAIDS 46 (2007) 643-50

Rethinking AIDS Day

The Group for Rethinking AIDS decided to name April 23rd “Rethinking AIDS Day” to commemorate Robert Gallo’s announcement of the pseudo-discovery of “HIV” on that date in 1984. A press release was issued, and there was tentative agreement on a “Green Ribbon” icon:

A fine video was created for the occasion.

An earlier PR venture in New York had taken advantage of an art auction in connection with the Bono “RED” campaign, informational leaflets were offered to people entering the auction:

(thanks to Darin Brown for gatherng the links and information)

HIV: IT MUST HAVE BEEN TRANSMITTED BY BITE!

The unshakable belief that testing “HIV-positive” denotes infection by a virus transmitted from another “HIV-positive” individual sometimes makes it necessary to draw inferences that outsiders and lay people might find hard to accept, indeed outlandish. So it is with the “evidence” that a man infected his daughter by biting her finger.

The following piece (“Rare causes of HIV transmission“)  comes from Professor Courtenay Bartholomew, Executive Director of the Medical Research Foundation in Trinidad & Tobago.

“Our case report on human bites: a rare risk factor for HIV transmission was published last year. . . . in the American Journal of AIDS, which . . . accepts only about one in 20 submissions. . . . In a review of such cases . . . Richman and Rickman . . . stated that ‘transmission of HIV through human bites is biologically possible but remains epidemiologically insignificant and as yet not well documented.’”

However, in June 2004 a heterosexual man with “very late stage AIDS” was found to be HIV-positive; he died in September 2007. He had a history of “dental caries and bleeding gums”. His wife was found to be HIV-negative, but their 7-year-old child tested positive. The wife was assumed to have remained negative “because sexual intercourse was infrequent”.

“Problem! How could the child be HIV-positive when the mother was HIV-negative seeing that childhood infection is usually from mother to child? We tested and retested the blood from the mother and the child but the results were the same. We also excluded any history of sexual abuse by the father and of blood transfusion to the child. It was then that the mother recalled an incident when at age three the child was bitten on her finger by her father, who was in a tantrum. Since we excluded all other modes of HIV transmission, her HIV infection had to be a direct result of the bite from her father four years ago.”

SOME OBSERVATIONS ON HIV/AIDS EPIDEMIOLOGY

In my post of 19 March, “HIV DISEASE” IS NOT AN ILLNESS, I treated changes over time in an over-simplified way to make the qualitatively sound point. Darin Brown sent a long comment that I thought too important, too instructive, to be hidden among “comments”, so I prevailed on him to let me use it as a direct post. It follows below (revised late 22nd); it’s also available as a pdf here: darinpdf0804232.

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Darin Brown, “SOME OBSERVATIONS ON HIV/AIDS EPIDEMIOLOGY”:

The mighty wall, atop which sits what I and a few other “insurgents” call the Humpty Dumpty of all biomedical hypotheses, was made from two kinds of bricks — fashioned from the stuff of virology and epidemiology, and held by what we contend is scientific cement of the most dangerously thin consistency. — Harvey Bialy

Epidemiology is like a bikini: What is revealed is interesting; what is concealed is crucial. — Peter Duesberg

We thought that we had the answers; It was the questions we had wrong. — U2, “11 O’Clock Tick Tock”

It’s no secret that the strongest evidence, if not the only evidence, in favor of the HIV hypothesis is epidemiological.

In his 1991 book Virus Hunting, Robert Gallo gave 7 reasons why he and his group of researchers in early 1984 concluded “HIV is the sole primary cause of the epidemic called AIDS” (1). All but one (#6) of Gallo’s 7 reasons are based purely on epidemiology and correlations:

1. “Finding of a new virus in AIDS patients…”
2. “The virus was also found in…’pre-AIDS cases’ and [in groups] at high risk…but only rarely in healthy heterosexuals…”
3. “[HIV] was a new…virus. AIDS as an epidemic was clearly new.”
4. “Wherever the HIV was found, AIDS was present…Conversely, no HIV — no AIDS.”
5. “Studies of blood donors showed…[a] perfect correlation.”
6. “The virus infected T4 lymphocytes.”
7. “We commonly found HIV in the brains of people who had died of AIDS.”

When challenged by Peter Duesberg in the pages of Science in 1988, William Blattner, Robert Gallo, and Howard Temin flatly admitted, “The strongest evidence that HIV causes AIDS comes from prospective epidemiological studies that document the absolute requirement for HIV infection for the development of AIDS.” (2) Note that this quote was made a full four years after HIV was announced as the cause of AIDS.

“The Evidence That HIV Causes AIDS”, an anonymous document produced by the National Institutes of Health, relies almost entirely on epidemiological arguments (3). The only direct claim of virological evidence is the following vague plea:

CD4+ T cell dysfunction and depletion are hallmarks of HIV disease. The recognition that HIV infects and destroys CD4+ T cells in vitro strongly suggests a direct link between HIV infection, CD4+ T cell depletion, and development of AIDS. A variety of mechanisms, both directly and indirectly related to HIV infection of CD4+ T cells, are likely responsible for the defects in CD4+ T cell function observed in HIV-infected people. Not only can HIV enter and kill CD4+ T cells directly, but several HIV gene products may interfere with the function of uninfected cells.

Recent investigators have not been as sanguine about our knowledge of HIV’s pathogenic mechanisms:

We still do not know how, in vivo, the virus destroys CD4+ T cells…. Several hypotheses have been proposed to explain the loss of CD4+ T cells, some of which seem to be diametrically opposed. (4)

Despite considerable advances in HIV science in the past 20 years, the reason why HIV-1 infection is pathogenic is still debated…. There is a general misconception that more is known about HIV-1 than about any other virus and that all of the important issues regarding HIV-1 biology and pathogenesis have been resolved. On the contrary, what we know represents only a thin veneer on the surface of what needs to be known. (5)

Twenty-five years into the HIV epidemic, a complete understanding of what drives the decay of CD4 cells — the essential event of HIV disease — is still lacking…. The puzzle of HIV pathogenesis keeps getting more pieces added to it. (6)

It is thus necessary to confront epidemiological arguments directly. One immediately faces a problem — all the evidence is presented in the context of a web of assumptions concerning the ontological status of HIV and the meaning of antibody, viral load and lymphocyte count tests. Consequently, this web of assumptions itself frames epidemiological data collection and questions.

For example, it is now impossible to answer, “What is the distribution of AIDS-indicator diseases among different risk groups?” because the data needed to answer this question are no longer routinely tallied. Similarly, it is impossible to answer, “What is the relationship between specific protein band patterns on the Western blot test and HIV/AIDS demographics?” because data on such patterns are not routinely tallied, let alone related to other demographic data.

The philosopher of science Paul Feyerabend posited that sometimes the only way to demonstrate the irreparable inadequacy of a theory is to collect and interpret data within the context of a completely incompatible set of assumptions regarding the most fundamental ontological and epistemological issues (7). My own opinion is that this is the current case with regard to HIV — the hypothesis will never be rejected until a comprehensive, substantial theory giving a positive explanation for the data gains widespread acceptance. (See footnote 1.)

Nevertheless, some of the epidemiological arguments put forward in favor of HIV can be dismissed by a few thought exercises. Here, I want to address what is perhaps the most common epidemiological argument one hears: “The drugs are working. Death rates have fallen. People are living longer.” (See footnote 2.)

First it should be noted that epidemiological evidence by its very nature is indirect and weak, particularly when evaluating drug therapies. Epidemiology establishes associations which require additional criteria to be met to demonstrate causation (8). It is strongest when combined with other forms of evidence. In this case, the form of evidence is that much weaker, since it is not based on the proposed pathogen itself but on therapies given. One has to be especially vigilant of not committing the classic post hoc fallacy: B follows A; therefore, A causes B.

I expounded much the same argument in my previous article, “AIDS Case Fatality Rates” (9), and here I want to extrapolate my observations to a few hypothetical thought experiments, in order to expose the essence of the faulty logic.

Consider the following hypothetical disease, for which I will give the incidence for each calendar year, and deaths/survival for those year-specific cases. In Table 1, “INC” means annual incidence, the total number of cases diagnosed that year, “Dn” means the total number of deaths occurring in year n out of all cases diagnosed that year, and “D15+” means the total number of AIDS patients remaining alive at the end of year 15 out of all cases diagnosed that year. I am also assuming, without loss of generality, that all diagnoses occur on 1 January.

Suppose that two therapies are given for our hypothetical disease: Therapy X, which is introduced and available to all on 1 January of year 6; and Therapy Y, which is introduced and available to all on 1 January of year 9.

First let’s look at the annual mortality rates of this hypothetical disease, assuming 1,000,000 people in the susceptible population, constant over all years. (This would not be true in practice, due to population growth and other factors, but this would not affect the overall trend much.) The units are “deaths per hundred thousand”:

From the data in Tables 1 and 2, it would appear the epidemic “peaked” in year 8. Proponents of the therapies would point to the fact that both annual incidence and mortality fell dramatically immediately following introduction of therapy Y, and that although mortality increased after therapy X, it might have been much greater than it turned out, and anyway we shouldn’t be too hard on therapy X, because it was our “first attempt” and its toxicities were much greater than therapy Y.

But wait a minute. Go back and look at the data in Table 1. The annual incidence increased 15-fold and then decreased 3-fold. Does it therefore really make sense to consider absolute mortality rates?

Now let’s look at one-year “case-fatality rates”. By “case-fatality rate” in this instance, I mean 100% minus the 1-year survival rate, in other words, out of all cases diagnosed in a given year, the proportion of deaths in that cohort after a single year times 100%. For example, in year 10, there were 8000 cases diagnosed, and of those, 2000 died within one year, so the one-year case-fatality rate for year 10 is 2000/8000 = 25%. (See footnote 3.)

Here are the one-year case-fatality rates:

This certainly paints a different picture of the epidemic. The severity of the epidemic reached its peak around year 2 to year 3, when survival was lowest and case-fatality was highest. Ever since then, except for some minor blips, severity has been decreasing steadily. Note that the peak severity of the epidemic was reached long before either therapy X or therapy Y was put on market, so any appeal to “falling death rates” as support for these therapies is shaky.

Now let’s put on our magic-hats and pretend we work for a hypothetical government agency, and we want to really give the impression that therapy Y is a life-saver (or at the least, a life-extender). Let’s conjure up 4 survival rates. Here “survival rate” means 100% minus the case-fatality rate. In other words the one-year survival rate is the proportion of patients surviving one year after diagnosis, the 2-year survival rate is the proportion of patients surviving 2 years after diagnosis, and so on.

Group 1: Diagnosed “pre-therapy Y”, say, years 1-7.

Group 2: Diagnosed immediately around and following therapy Y, say, years 8-11.

Group 3: Diagnosed after therapy Y was available for a substantial period, say years 12-13.

Group 4: Diagnosed during years 14-15.

We get the following numbers:

Group 1 Survival Rates after 1, 2, and 3 years respectively: 42%, 27%, 14%

Group 2 Survival Rates after 1, 2, and 3 years respectively: 62%, 51%, 45%

Group 3 Survival Rates after 1, 2, and 3 years respectively: 88%, 80%, 76%

Group 4 Survival Rates after 1, 2, and 3 years respectively: 90%, N/A, N/A

Based on these data, as well as the annual incidence and mortality rates above, it certainly seems like therapy Y has been a smashing success: just look at those plummetting incidence and mortality rates and steadily increasing survival rates, all of which occurred immediately following introduction of therapy Y.. Anyone who denies therapy Y is working must be a “therapy Y denialist” who thinks the earth is flat and the moon landings were faked. The only data which cast doubt on therapy Y are the case-fatality rates.

So which should we believe, the mortality rates and survival rates above, or the case-fatality rates?

I’ve already discussed why the absolute mortality rates are not too meaningful: the incidence of the disease has varied by more than an order of magnitude over the years, increasing and then decreasing, so comparing absolute mortality rates over a period of several years is like comparing apples to oranges to kumquats. The problem with the survival rates is clear once you look closely at the case-fatality rates: by lumping the first 7 years together into a single group,

(1) it obscures the fact that survival reached a low point around year 2 to year 3; and
(2) it disproportionately favors those diagnoses made in year 6 and year 7, because there were simply many more of them.

Together, the annual incidence and absolute mortality rates and the group-generated survival rates above give the false impression that therapy Y is working. Or to be more precise, they give the false impression that they are valid evidence that therapy Y is working.

POSTSCRIPT:

There is one other way around considering absolute mortality rates, and that is to scale the mortality rates to the population consisting only of AIDS patients. This is essentially the approach I took in my article a year ago (9), when I scaled death rates to AIDS prevalence, and it is the same measure that appears in some papers examining changes in death rate from the mid-1990s, with the units being “deaths per person-year” and the populations being cohorts of AIDS patients, not the total population. Again, in these papers, they note that death rate declined dramatically while HAART was rolled out and conclude HAART caused the decline. They fail to consider that the decline may have begun far earlier, even before AZT monotherapy was available. My analysis a year ago concluded that this is in fact the case: the AIDS epidemic, as measured by mortality rate among AIDS patients, peaked in the US around 1984-1986. It is instructive to see what a similar analysis yields for my hypothetical disease above.

To compute mortality rate scaled by AIDS prevalence, look at Table 1. Consider year 6. The total of all the numbers in the columns D7 to D15+ at or above the row of year 6 represent those patients who were alive at the beginning of year 6 and remained alive throughout year 6. They are thus each weighted with a single person-year. There are 100 + 1000 + 100 + 500 + 500 = 2200 such patients, so they contribute 2200 person-years. The total of all the numbers in column D6 represent those patients who were alive at the beginning of year 6 but died during year 6. Assuming that deaths are uniformly distributed throughout the calendar year, these patients are thus each weighted with half a person-year. There are 100 + 400 + 3000 = 3500 such patients, so they contribute 3500/2 = 1750 person-years. The numbers in columns D1 to D5 represent patients who died before the beginning of year 6 and are thus do not contribute to either deaths or person-years. For year 6, therefore, we get 3500 deaths divided by 2200 + 1750 = 3950 person-years, yielding 3500/3950 = 89% deaths/person-year. Calculating this for each year gives the following table:

Again, for our hypothetical disease, it is clear the severity of the epidemic peaked around year 2 or year 3. And because of the wide variation in incidence over the years, either this measure of mortality rate scaled to disease prevalence, or of survival rates among patients diagnosed in a given year, must be used rather than absolute mortality rates. It is true that mortality among patients declined and survival among patients increased after therapy Y was introduced, but in both cases, these trends were already occurring long before therapy Y was put on market.

The numbers for my hypothetical disease are not much different in terms of general trends from US AIDS data. The time period is stretched out over a few more years, and mortality isn’t quite as high as my hypothetical example, but the general pattern is qualitatively the same. And so the same argument applies to AIDS mortality throughout the years: the severity of the epidemic peaked around 1984-1986, before AZT and HAART, in other words, the trends in declining mortality, as measured by mortality scaled to prevalence or by survival rates, began long before HAART was introduced and even before AZT was introduced, so these cannot be used as even indirect evidence for the HIV hypothesis.

The general conclusion is quite sobering: Without the expansions of the definition of AIDS and the introduction of AZT in the late-1980s and early-1990s, the AIDS “epidemic” in the US clearly would have petered out on its own by the mid-1990s. For the past 15 years, “AIDS” has largely been prolonged by iatrogenic factors, in other words, the viral hypothesis itself has prolonged the epidemic.

FOOTNOTES:

1. An extended passage from Feyerabend is especially relevant here: “The concentration upon the theory will now be reinforced, the attitude towards alternatives will become less tolerant. Now if it is true…that many facts become available only with the help of such alternatives, then the refusal to consider them will result in the elimination of potentially refuting facts. More especially, it will eliminate facts whose discovery would show the complete and irreparable inadequacy of the theory. Such facts having been made inaccessible, the theory will appear to be free from blemish… By now the success of the theory has become public news. Popular science books…will spread the basic postulates of the theory… More than ever the theory will appear to possess tremendous empirical support. The chances for the consideration of alternatives are now very slight indeed. At the same point it is evident…that this appearance of success cannot in the least be regarded as a sign of truth and correspondence with nature. Quite the contrary, the suspicion arises that the absence of major difficulties is a result of the decrease of empirical content brought about by the elimination of alternatives, and of facts that can be discovered with the help of these alternatives only. In other words, the suspicion arises that this alleged success is due to the fact that in the process of application to new domains the theory has been turned into a metaphysical system. Such a system will of course be very ‘successful’, not, however, because it agrees so well with the facts, but because no facts have been specified that would constitute a test and because some such facts have even been removed. Its ‘success’ is entirely man-made. It was decided to stick to some ideas and the result was, quite naturally, the success of these ideas. If now the original decision is forgotten, or made only implicitly, then the survival will seem to constitute independent support, it will reinforce the decision, or turn it into an explicit one, and in this way close the circle. This is how empirical ‘evidence’ may be created by a procedure which quotes as its justification the very same evidence it has produced in the first place.” [italics as in original] (7)

2. I will not address here in detail the clinical evidence proposed in favor of combination therapy. There are many shortcomings of this evidence (inadequate trial duration, inadequate study size, reliance on dubious surrogate markers), but the most important point to remember is that a particular combination therapy is always tested against another “standard care” therapy, most often by simply adding another drug to an existing therapy. For example, a combination of 3 drugs is tested against a standard care combination of 2 drugs. The combination of 2 drugs is presumed to be standard care because it, in turn, has been previously tested against a standard care of monotherapy, which itself has been previously tested against a “true placebo” (inert drug). The point is that the claim that a combination therapy of 3 drugs is better than true placebo is dependent upon a chain of clinical comparisons, just as the proof of a mathematical theorem is dependent upon a chain of logical implications. So if even a single clinical comparison is invalid, the entire chain falls apart, as a mathematical proof falls apart if even a single logical implication is invalid. What this means for HIV therapy is that we must look very closely at the original studies comparing AZT monotherapy to true placebo. If we find these original studies to be unsound or fraudulent, then we have no basis for claiming combination therapy is better than true placebo.

3. One important note for those who choose to read the previous article “AIDS Case Fatality Rates”: There I use a different definition of “case-fatality rate”. Part of the problem is that after reading some standard university epidemiology textbooks, I’m a bit mystified about the precise definition of “case-fatality rate”, as you can find out by reading the “Notes on Definitions and Computations” from that article. This confusion compels me to make my own computations, spelling out precisely what it is I’m computing. If my choice of using the term “case-fatality rate” in both that article and this one causes confusion, I don’t care to accept the charge it’s my fault. If you wish, just ignore the term “case-fatality rate” everywhere you see it, and go by my own explanations of my computations, which are not imprecise at all.

REFERENCES:

1. Robert Gallo, Virus Hunting: AIDS, Cancer, and the Human Retrovirus: A Story of Scientific Discovery, Basic Books, 1991.
2. William Blattner, Robert Gallo, and Howard Temin, “HIV Causes AIDS”, Science 241: 514-517, 29 July 1988.
3. National Institutes of Health, “The Evidence That HIV Causes AIDS”, updated 2003, http://www.niaid.nih.gov/Factsheets/evidhiv.htm
4. Joseph McCune, “The dynamics of CD4+ T-cell depletion in HIV disease”, Nature, 2001 Apr 19; 410 (6831): 974-9.
5. Mario Stevenson, “HIV-1 Pathogenesis”, Nature Medicine, HIV Special. July 2003. Vol.9, No. 7. 853-861.
6. WK Henry et al., “Explaining, Predicting, and Treating HIV-Associated CD4 Cell Loss: After 25 years Still a Puzzle”, JAMA, 27 September 2006; 296: 1523-1525.
7. Paul Feyerabend, Against Method: Outline of an Anarchistic Theory of Knowledge, Verso, 1975.
8. Austin Bradford Hill, “The Environment and Disease: Association or Causation?”, Proceedings of the Royal Society of Medicine, 58 (1965), 295-300, http://www.edwardtufte.com/tufte/hill
9. Darin Brown, “United States AIDS Case Fatality Rates 1981-2005”, 25 May 2007, http://www.reviewingaids.com/awiki/index.php/Document:AIDS_Case_Fatality_Rates

DECONSTRUCTING HIV/AIDS in “SUB-SAHARAN AFRICA” and “THE CARIBBEAN”

Sub-Saharan Africa is being ravaged by HIV/AIDS, so we are incessantly reminded by the media, UNAIDS, the World Health Organization, the World Bank, innumerable charities named for or supported by prominent celebrities, and innumerable activists and activist groups. Disseminating global and regional numbers, UNAIDS invariably refers to “sub-Saharan Africa” as though it were an entity analogous to Asia, Eastern Europe and Central Asia, Latin America, North America, Western Europe, Oceania, or Middle East and North Africa.

But those incessant expressions of grave concern may be the only thing that unites “sub-Saharan Africa”, because little if anything is really common to every one of those 40-odd countries, HIV/AIDS perhaps least of all. In sub-Saharan Africa, as also in the Caribbean, the reported “HIV prevalence” varies widely— indeed wildly—from country to country; whereas in the rest of the world, HIV prevalence is rather uniformly distributed within and between the regions of Asia, Eastern Europe and Central Asia, Latin America, North America, Western Europe, Oceania, Middle East and North Africa—where, at significantly less than 1%, “HIV” is also much less than in “sub-Saharan Africa” and “the Caribbean”.

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Caribbean

The UNAIDS report for 2006 gives the “HIV-positive” rate for the Caribbean as 1.6% (± 0.6), but for individual islands what’s reported is between 0.1% and 3.8%. There is no obvious reason why the average of such widely varying numbers should mean anything. Looking at the countries separately, there appears once again something like a correlation with race, in particular African ancestry:

Note particularly the differences between Haiti and the Dominican Republic, which share a land border but differ drastically in levels of “HIV” and in their proportions of people of African ancestry.

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Sub-Saharan Africa

“Sub-Saharan Africa” displays a similar non-uniformity of “HIV”-positive rates, ranging from highs of 38.8% and 37.3% in the south [sic–these extraordinary numbers are not typos] to 1% or less in Senegal in the West and Somalia in the East:

These variations in “HIV” are more clearly discernible if country names are omitted:

and the trends may be seen even more readily if numbers are replaced by varied intensity of shading (≤ 1%; 1-3%; 3-6%; 6-9%; 9-13%; 13-20%; 20-25%; ≥ 25%; no data were found for Western Sahara; the 3 white blots in the mid-eastern section are bodies of water):

This does not look much like the distribution of something infectious or contagious, something supposed to spread primarily via sexual intercourse; particularly not when the purported agent of infection is said to have affected human beings for the first time in West Central Africa http://mbe.oxfordjournals.org/cgi/content/short/24/8/1853 or Cameroon (Keele et al., Science, 313 [2006] 523-6) early in the 20th century, jumping in some manner from chimpanzees; the highest frequencies of positive tests–by far–are in the extreme south, not around Cameroon.

Whereas this distribution does not look like the spread of an infection, it does look rather plausible as the distribution of human genetic haplotypes. Certainly it bears a resemblance to the distribution of language families in Africa:

There has been considerable controversy over the purported connection between language and human genetics, but there may well be a correlation over time-spans on the order of centuries or a millennium or two. In this instance, there is a plausible similarity with the great Bantu migration that began a millennium or two ago:

Overall, there seems to be a correlation between the distribution of “HIV” in Africa and the genetic connections suggested by Cavalli-Sforza (Genes, People, and Languages, North Point Press [Farrar, Straus & Giroux], 2000):

Note particularly the distance between Bantu and West African, and even more between those and Ethiopian, and especially San, the “Bushmen of the Kalahari”, who have a low rate of “HIV-positive” yet dwell in the region of (Bantu-populated) Botswana and Swaziland where “HIV” ≥ 35%.

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In the United States, the geographic distribution of “HIV-positive”—which has remained constant since testing began—can be calculated with good accuracy from the regional variations in racial composition of the population (see p. 66 ff. in The Origin, Persistence and Failings of HIV/AIDS Theory). With only 4 levels of shading in each of the following two maps, by chance just 12 states (48/4) would have the same color in both maps; but here, 31 states are shaded the same in both figures, much better than chance. This is consistent with the conclusion that the racial composition of the population is the chief determinant of rates of testing “HIV”-positive.

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The geographic correlations described in this post are perhaps suggestive more than probative. However, there is obviously no justification for talking about HIV/AIDS in “sub-Saharan Africa” as though something were common about it throughout that region. “AIDS in sub-Saharan Africa” is a sound-bite useful for propaganda; but like so many sound-bites, it is drastically misleading.

It is not just suggestive, however, but quite solid fact, acknowledged in innumerable official reports and mainstream publications, that “HIV” in the United States affects people in the officially used racial and ethnic groups quite differently, and persistently in the sequence

Asian < white < Native American < Hispanic < black

There is evidently some sort of genetic basis for the tendency to test “HIV”-positive. Or one might put it like this:

“HIV” tests are racially biased.