HIV infectivity: high, low, or non-existent?

Analysis of essentially all published results of HIV tests in the USA reveals properties unlike those of an infectious agent (The Origin, Persistence and Failings of HIV/AIDS Theory, McFarland 2007).  In every social sector, the same regularities are seen: rates of testing positive vary by US official “racial” and ethnic classification (black >> native American > Caucasian > Asian); rates of testing positive decrease drastically from birth into the teens and increase from the late teens into middle age and then decline again; in early teens, females are more likely to be HIV+ than are males but by the 20s that is reversed (see references cited in section 3.3.5 in The Case against HIV).

In cloned HIV virions, only between 1 in 10,000 and 1 in 10 million were infectious (Layne et al., “Factors underlying spontaneous inactivation and susceptibility to neutralization of human immunodeficiency virus”, Virology, 189 (1992) 695-714).

The instructions that come with HIV test kits warn that a positive test is not proof of infection.

Innumerable conditions produce HIV+ results (see references cited in section 3.2 in The Case against HIV), so all claims to have measured infectivity or transmission are at best dubious and at worst — or more accurately — meaningless. There is no valid published evidence of transmission or infectivity (see references cited in section 3.3 in The Case against HIV). The Office of Medical and Scientific Justice successfully defended more than 50 individuals http://www.omsj.org/human-rights/52nd charged with transmitting HIV because the prosecution could not prove HIV to be transmissible.

Researching phantoms

It can take a long time before researchers realize that they have been on a wild-goose chase, pursuing phantoms (“Phantom phantoms”, pp. 110-116 in Fatal Attractions: The Troubles with Science, Paraview Press 2001); even “an unknown phenomenon [that] towered 6 standard deviations above the mundane background of known physics — enough to satisfy a 99.9999% confidence level that it wasn’t a fluke” and that had been reported in more than a dozen experiments turned out to be non-existent.

Given that HIV/AIDS theory is wrong (The Case against HIV), observations and experiments and clinical trials will continually throw up what seem to be conundrums, which serve as the basis for yet more research. To date, mainstream HIV/AIDS researchers have failed to recognize the accumulation of conundrums and absurdities  as being in reality the hard evidence that HIV/AIDS theory is simply wrong: HIV is not infectious, and “HIV” doesn’t cause AIDS.

Mainstream science sticks to theories that had once been accepted by ignoring anomalies, conundrums, absurdities for as long as possible (Thomas S. Kuhn, The Structure of Scientific Revolutions, University of Chicago Press 1970 [2nd ed., enlarged; 1st ed. was 1962]). Things that don’t fit an existing theory are accommodated by ad hoc adjustments (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), just as Ptolemy long maintained belief in the circular perfection of heavenly motions by adding epicycles upon epicycles, wheels within wheels, to avoid acknowledging that the movements are not really circular after all.

So too HIV/AIDS researchers create new hypotheses to bolster their belief whenever they seem unable to explain what they observe. Since all the data point to HIV not being infective, or being apparently infective to so low a degree as to be incapable of producing an epidemic, auxiliary hypotheses were suggested which have become accepted as shibboleths:

1. The epidemic in Africa is said to have come about because of an incredible rate of promiscuity. Sexually active South Africans (black South Africans, that is) are postulated to have an average of 10 sexual partners at any give time and to change them about annually (pp. 63-65 in James Chin, The AIDS Pandemic, Radcliffe 2007).
2. Soon after initial infection, there is an “acute phase” where large amounts of HIV are present, and intercourse during that phase makes transmission much more likely: infectivity is very high during these short periods, so overall measurements of transmissibility are deceiving.

The first suggestion is absurd, since such behavior would be so visibly evident that it could not be overlooked; yet it is not observed.

The second suggestion has been undermined by a careful re-analysis of the single study on which it had been based: the “excess hazard-months attributable to the acute phase of infection” is about 5.3, not the previously estimated 31-to-141 (Bellan et al., “Reassessment of HIV-1 acute phase infectivity: accounting for heterogeneity and study design with simulated cohorts”, PLoS Medicine, 12(3):  e1001801).

HIV/AIDS research is chasing red herrings, phantoms, in a decades-long wild-goose change that has been enormously expensive in lives and in dollars. But the interests vested in this state of affairs — drug-company profits, research careers, administrative careers, honors and awards — are so widespread and powerful that the actual evidence is given little or no chance of speaking for itself. Try to imagine what it would take for Anthony Fauci to shed cognitive dissonance and admit that he has been so disastrously wrong.

 

Census Bureau supports Duesberg

Duesberg et al. (“HIV-AIDS hypothesis out of touch with South African AIDS – A new perspective”)  had debunked the claim by Chigwedere, Essex, et al. (“Estimating the lost benefits of antiretroviral
drug use in South Africa”, JAIDS 49 [2008] 410-5) that antiretroviral treatment could have saved about 330,000 lives in South Africa between 2000 and 2005 — or 2.2 million person-years — were it not for the misguided theories of Peter Duesberg taken seriously by President Mbeki.
So threatening to the HIV/AIDS Establishment was the Duesberg refutation of Chigwedere et al. that Nobelist Barre-Sinoussi was enlisted to lead-sign a protest against the Duesberg publication, which led eventually to the demise of Medical Hypotheses as a credible vehicle for innovative ideas (“Elsevier-Gate”): the journal’s new editor claimed it possible both to  “publish radical new ideas” and at the same time “not . . .  get into controversial subjects” (Martin Enserink, “New Medical Hypotheses editor promises not to stir up controversy”, ScienceInsider, 25 June 2010).
Duesberg et al. had resorted to Medical Hypotheses only after JAIDS — the journal that had published the Chigwedere article — had refused, counter to all standard practice not to say common decency, to allow a response in  its own pages.
Despite Elsevier’s withdrawal of the Duesberg article, it has been freely available  on the Internet, but it seemed proper and useful to have it in the mainstream literature indexed as other than “withdrawn”. Independent peer review led to the recent publication of the Duesberg arguments in the Italian Journal of Anatomy and Embryology , and the abstract is now in PubMed:

Of course the HIV/AIDS vigilantes were beside themselves at this turn of events, and even more that it was brought to widespread attention by a piece on the Nature website. Subsequent fury was expressed in comments to that piece, leading to rather comical machinations by Nature editors attempting to cleanse its site by “losing” those comments owing to an alleged software glitch, see “NATURE and science journalism”.
That blog posting brought a highly informative comment  from Jean Umber: Dr. Willy Rozenbaum, who had given Montagnier the first samples in which “HIV” was supposedly found, had published in 2007 a presentation which showed projections by the US Census Bureau of how the population of South Africa would grow if AIDS were present or if AIDS had not been present:

This is precisely one of the arguments made by Duesberg et al., that the actual population growth in South Africa is what had been projected to happen if AIDS were not present:

According to the official doomsayers of the HIV/AIDS faith, AIDS should have capped the South African population at about 45 million around the year 2000; instead the population has continued to grow in steady fashion.
The defenders of HIV/AIDS theory had ventured a couple of substantive criticisms of the original Duesberg article, among them that this comparison of actual with projected population growth is not convincing. Yet it is the US Census Bureau that published the projections with and without AIDS, and what actually happened is precisely what the Bureau projected if AIDS were not decimating the population.
Rozenbaum’s slide does not give details (other than the date of 2004) for the actual Census Bureau documents from which he extracted these projections. It may well have been The AIDS Pandemic in  the 21st  Century, issued March 2004, tagged WP/02-2, described as an International Population Report by  Karen A. Stanecki, and given the imprimatur not only of the US Census Bureau but also of the Office of HIV/AIDS, Bureau for Global Health, U.S. Agency for International Development. That document does give copious details of projections with and without AIDS, in numbers and histograms and graphs. It also provides even further support for the validity of the case made by Duesberg et al.:
One of the persistent criticisms made by HIV/AIDS vigilantes is that numbers for the prevalence of “HIV-positive” used by Duesberg et al. came from pre-natal clinics and that data on pregnant women was not a valid proxy for the rate of “HIV-positive” in the general population of South Africa. To the contrary, the Census Bureau points out that it is a very good proxy, and why that is the case:

Although this particular figure refers to data from Zambia, the Census Bureau describes it as representative for all of sub-Saharan Africa:
“In Sub-Saharan Africa,  More Women Than Men  Are HIV Positive
At the end of 2001, UNAIDS estimated that 58 percent of all HIV infections in Sub-Saharan Africa were among women.  Peak HIV prevalence among women occurs at a younger age than among men: around age 25 compared to age 35-40.  As Figures 3 and 4 show for Rwanda and Zambia, younger women tend to have higher levels of HIV infection than men of their same age. Several studies have shown that HIV prevalence among pregnant women attending antenatal clinics provides a reasonable overall estimate of HIV prevalence in the general adult population, although it underestimates the rate among all women while overestimating it among men.  This is shown for Zambia in Figure 4.”

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Note that the Census Bureau Figure 4 above is also yet another illustration of the demographic fact that, in all populations for which data have been published, prevalence of “HIV-positive” rises from the mid-teens and falls again at higher ages, and that females test “HIV-positive” more than males at the younger ages while the opposite is seen at higher ages. The exact ages at which the ratio reverses, and at which “HIV-positive” reaches a maximum, varies not only with sex but also with race; African genes are associated with a longer age-span during which females test positive more than males. For details see a number of earlier blog posts confirming all the trends pointed to in The Origin, Persistence and Failings of HIV/AIDS Theory.

Must read

There is a great deal worth reading about HIV and AIDS and dissent from the mainstream view, and impossible to keep up with it all. So I’m very grateful when I’m alerted to particularly important items. Here’s one:

“Exclusive: A Gut Instinct about AIDS” by Russell Schoch, at reducetheburden.org

When Tony Lance first told me of his idea that intestinal dysbiosis could explain much about HIV/AIDS, I was immediately interested because it was the first explanation I had come across as to why gay men are so prone to test “HIV+”, even when they are not exemplars of the fast-lane drug-abusing lifestyle and even when they turn out to remain quite healthy while “HIV+”, i.e. are “long-term non-progressors” or “elite controllers”.

Since then Tony has turned up a staggering volume of mainstream publications that make his idea, in my view, progress from “plausible” to “compelling”. Russell Schoch’s article provides convincing context to Lance’s work. It is absolutely a MUST read.

What do CD4 counts mean?

The level of CD4 cells in peripheral blood is a prime criterion for diagnosing AIDS (in the United States in particular) and for monitoring antiretroviral treatment. However, these applications of CD4 counts stem from the initial and unhappy coincidence that when “AIDS” appeared around 1980, the counting of immune-system cells was in its infancy. By now it is known that CD4 levels are extremely variable in healthy individuals, and that a variety of physiological conditions other than “HIV” may profoundly influence CD4 counts. There seems to be no fundamental evidential warrant for the manner in which HIV/AIDS diagnosis and treatment rely on CD4 counts. Juliane Sacher among others has pointed out that the levels of CD4 cells in peripheral blood are not a meaningful measure of immune-system status, since these cells move around the body according to where they seem to be needed [Alternative treatments for AIDS, 25 February 2008].

An obvious question: what is the range of CD4 counts in healthy individuals and in a variety of illnesses? (I’m grateful to Tony Lance for alerting me to some of the intriguing sources mentioned in the following).

One of the striking aspects of CD4 counts is how enormously they vary among individuals, including healthy individuals. Here, for example, are data from HIV-negative Senegalese:

C. Mair, S. E. Hawes, H. D. Agne, P. S. Sow, I. N’doye, L. E. Manhart, P. L. Fu, G. S. Gottlieb and N. B. Kiviat. Factors associated with CD4 lymphocyte counts in HIV-negative Senegalese individuals. Clinical and Experimental Immunology 151 (2007) 432-440

In any normal distribution, the standard deviation (s.d. or σ) describes the degree of scatter around the average (or mean) value. Only about 2/3 of a sample are within (±) 1 σ; in other words, about 1/6 are further from the mean on both the higher and the lower sides. In the Table above, among the men with mean CD4 count of 712, σ = 333, about 1 in every 6 men have CD4 counts below 379 or above 1045; and about 2% have counts more than 2σ above and below 712 , that is >1378) and <50. CD4 = 200 is about 1.5σ below the mean, which corresponds to about 6-7% (~1/15) of the sample. In other words, about 1 in every 15 healthy HIV-negative Senegalese men has CD4 counts below the 200 that, in HIV-positive people, is taken to be a sign of AIDS.

Of course, CD4 counts may not follow a normal distribution, especially at upper and lower levels; but since this article reports means and standard deviations without specifying a different distribution, the authors themselves are presuming it is normal. Moreover, a similarly wide range of CD4 counts and an approximation to normal distribution is shown in other data sets as well. For example, healthy North Indians were reported to have a mean CD4 count of 720 with σ = 273 and an actually observed range of 304-1864 among 200 individuals; 10% were below 400, consistent with a normal distribution which would have about 16% below 450 (Ritu Amatya, Madhu Vajpayee, Shweta Kaushik, Sunita Kanswal, R.M. Pandey, and Pradeep Seth. “Lymphocyte immunophenotype reference ranges in healthy Indian adults: implications for management of HIV/AIDS in India”. Clinical Immunology 112 [2004] 290-5). Actual distributions for several African populations, however, show a skewing toward higher CD4 counts, which indeed seems highly plausible a priori — one might expect to see a definite lower bound to CD4 counts in healthy individuals (Williams et al., “HIV infection, antiretroviral therapy, and CD4+ cell count distributions in African populations”, J Inf. Dis. 194 [2006] 1450-8).

Worth particular note is the comment in Amatya et al. that “These low counts could be due to physiological lymphopenia potentially caused by protein energy malnutrition, aging, antigenic polymorphism of the CD4 molecule, prolonged sun exposure, circadian rhythm, and circannual variation [9,10]”. The use of contraceptive pills by women has also been reported to influence CD4 counts (M. K. Maini, R. J. Gilson, N. Chavda, S. Gill, A. Fakoya, E. J. Ross, A. N. Phillips and I. V. Weller. “Reference ranges and sources of variability of CD4 counts in HIV-seronegative women and men”. Genitourin Med 72 [1996) 27-31]. Most of those circumstances do not represent illness. So CD4 counts can be low for a variety of fairly normal, not seriously health-threatening conditions. It follows that reliance on CD4 counts as diagnostic of “HIV disease” increases the danger that some unknown number of “HIV-positive” individuals are being told on the basis of laboratory tests — sometimes SOLELY on the basis of laboratory tests — that they are actually sick even though they feel and actually are healthy; and these people are then at risk of being consigned to toxic “treatment” for this imaginary illness. The risk is greatest if the blood tested for CD4 counts happens to have been drawn in the morning, or in the wrong season of the year, because CD4 counts vary appreciably with both those variables: T. G. Pagleironi et al., “Circannual variation in lymphocyte subsets, revisited”, Transfusion 34 [1994] 512-6; F. Hulstaert et al., “Age-related changes in human blood lymphocyte subpopulations”, Clin. Immunol. Immunopathol. 70 [1994] 152-8. Maini et al. (above) report a 60% variation during the day with lowest counts at 11 am. Yet another report describes a similarly large diurnal variation, from 820 at 8 am to 1320 at 10 pm (Bofill et al., “Laboratory control values for CD4 and CD8 T lymphocytes. Implications for HIV-1 diagnosis”, Clin. Exp. Immunol. 88 [1992] 243-52).

Just as with the tendency to test “HIV-positive”, CD4 counts are influenced by demographic variables: “race, ethnic origin, age group, and gender” (Amatya et al.). Bofill et al. also report a steadily decreasing CD4 count with increasing age. The contrary has been reported, however, by Jiang et al. (“Normal values for CD4 and CD8 lymphocyte subsets in healthy Chinese adults from Shanghai”, Clinical and Diagnostic Laboratory Immunology, 11 [2004] 811-3). The discrepancy may be owing to differing attitudes toward statistical significance: the raw numbers in Jiang et al. do show an increase with age for men and a decrease with age for women but, as with the data of Bofill et al. and all others, the standard deviations are so large, on the order of one third of the mean values, that differences and trends would have to be very considerable if they are to be statistically meaningful.

Again, Jiang et al. report no difference between Chinese men and women, whereas several sources cite women as having higher CD4 counts than men: in Britain (Maini et al.) and in more than dozen other countries in Africa, Asia, and Europe (Mair et al.). Caucasians have higher CD4 counts than Asians or Africans, according to Amatya et al. and Jiang et al., but not according to Maini et al.

All these variations under the influence of several factors would make the diagnostic application of CD4 counts problematic even if “HIV” or “AIDS” had been shown to be the salient influence on CD4 levels. However, just as with the tendency to test “HIV-positive”, CD4 counts may be “low” in a wide range of conditions; perhaps most relevant to HIV/AIDS, in tuberculosis and general trauma, as well as with primary immunodeficiency, early acute phases of such viral infections as influenza, or Dengue fever (Bofill et al.) or recent respiratory infections (Maini et al.).

Not only are CD4 counts dubious for diagnosis or prognosis; just as with the tendency to test “HIV-positive”, CD4 counts generate a number of conundrums if interpreted according to HIV/AIDS theory: the counts are often HIGHER rather than lower in conditions generally regarded as associated with poor health. For example, smokers have higher CD4 counts than non-smokers (Maini et al., Mair et al.) and prostitutes have higher counts than other women (Mair et al.). Another “striking paradox” is in “co-infection” with “HIV” and herpes:
“We observed no effect of HSV-2 status on viral load. However, we did observe that treatment naïve, recently HIV-1 infected adults co-infected with HSV-2+ at the time of HIV-1 acquisition had higher CD4+ T cell counts over time. If verified in other cohorts, this result poses a striking paradox, and its public health implications are not immediately clear” (emphases added; Barbour et al., “HIV-1/HSV-2 co-infected adults in early HIV-1 infection have elevated CD4+ T-Cell counts”, PLoS ONE 2(10) [2007] e1080).

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There seems to be no clear warrant for diagnosing AIDS by means of CD4 counts, which may be why other countries have not followed the US example of taking <200 as a criterion. Similarly, there seems to be no clear warrant for assessing the progress of antiretroviral treatment by means of CD4 counts. Two practical illustrations of that are the fact that CD4 counts do not correlate with (or, changes in are not predicted by)  “viral load” (Rodriguez et al., JAMA, 296 [2006] 1498-1506), and that the NIH Treatment Guidelines distinguish immunologic failure (no increase in CD4 counts) from virologic failure (no decrease in viral load) and from clinical progression (does the patient’s health improve?).

A somewhat related illustration of the failure of HIV/AIDS theory is that “AIDS” patients with Kaposi’s sarcoma may have quite high CD4 counts: see for example Maurer T, Ponte M, Leslie K. “HIV-Associated Kaposi’s Sarcoma with a High CD4 Count and a Low Viral Load”. N Engl J Med 357 (2007) 1352-3; Krown SE, Lee JY, Dittmer DP, AIDS Malignancy Consortium. “More on HIV-Associated Kaposi’s Sarcoma” N Engl J Med 358 (2008) 535-6; D.G. Power, P. J. Mulholland K. J. O’Byrne. “AIDS-related Kaposi’s Sarcoma in a Patient with a Normal CD4 Count”. Clinical Oncology 20 (2008) 97; Stebbing J, Powles T, Bower M. AIDS-associated Kaposi’s sarcoma associated with a low viral load and a high CD4 cell count. AIDS 22 (2008) 551-2. Mani, D., Neil, N., Israel, R., Aboulafia, D. M. “A retrospective analysis of AIDS-associated Kaposi’s Sarcoma in patients with undetectable HIV viral loads and CD4 counts greater than 300 cells/mm3”. J Int Assoc Physicians AIDS Care (Chic Ill) 8 (2009) 279-85.

But then it has also long been known that “AIDS” Kaposi’s sarcoma is not caused by HIV, it’s now attributed to KSHV or HHV-8, which just happened — by the sort of extraordinary coincidence or oddity that is so common in HIV/AIDS matters — just happened to appear at the same time among the same risk groups as “AIDS” and “HIV” did; and then just as mysteriously went a separate path, so that KS declined from about 40% of all “AIDS” case in 1982 to well under 10% from 1987 onwards (Table 30, p. 128 in The Origin, Persistence and Failings of HIV/AIDS Theory).

More sales in the offing for snake oil and Brooklyn Bridges.

Italy: Demographics of HIV and AIDS

Professor Ruggiero has sent recent official data about HIV and AIDS in Tuscany as well as in Italy as a whole. Both sets of data illustrate once more that HIV/AIDS theory is incapable of explaining salient demographic features of HIV and of AIDS.

For example, in Tuscany the male-to-female ratio for the incidence of AIDS has been essentially constant from 1985 to 2008 at ~3.6:

whereas the purported mode of transmission changed drastically: from ~8% of “HIV” being transmitted heterosexually to ~44% being transmitted in that way — see red curve in figure below:

Those data place a very curious constraint on how infection via dirty needles occurred in males and in females respectively: it must occur in precisely the same relative manner as sexually transmitted “HIV infection” occurs in males relative to females. Otherwise the M/F ratio for the consequences of “HIV”, namely AIDS, should have changed in some manner.
HIV/AIDS apologists can surely find a scenario to satisfy that constraint, while unprejudiced observers will recognize any such scenario as the usual attempt by HIV/AIDS theorists to sell a scientific analogue of snake oil or Brooklyn Bridges.
(American idiom and popular culture include such icons of public gullibility as that snake oil is a panacea for illness and that the Brooklyn Bridge could be bought.)

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Another remarkable phenomenon in the Tuscan data is the upward drift in the median age for an AIDS diagnosis:

The stochastic fluctuations reflect the small numbers involved in each year but do not mask that the difference in median ages between men and women was seemingly constant at about 3 years, while both increased from 1987 to 2008 by about 2/3 of a year per year.
Such an upward drift of the median age of AIDS diagnosis (as well as of the median age of first “HIV-positive” test and median age of AIDS deaths) is also present in US data, albeit of somewhat smaller magnitude (Deaths from “HIV disease”: Why has the median age drifted upwards?, 18 February 2009). The drift in the US data is partly explainable by a changing racial composition of those affected by AIDS. In Tuscany, the drift may be associated with the shift away from predominantly drug abusers (from ~54% to ~19%, see above): “HIV-positive” is a very non-specific indication occasioned by a wide variety of physiological conditions, certainly by serious illness and by drug abuse, and it seems plausible that serious drug abuse brings illness at an earlier age.

The Tuscan data also show quite clearly that AIDS incidence declined significantly after 1995, something that UNAIDS has belatedly acknowledged overall in the world (Not with a bang but a whimper, 2009/12/27).

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The national data from Italy, too, display trends that are incompatible with HIV/AIDS theory. Thus the relative rates of “HIV-positive” among men and women has remained the same

while — as in Tuscany — the supposed mode of becoming “HIV-positive” changed from ~75% drug-related to only ~5% drug-related and sexual transmission supposedly increased from less than 10% to ~80%:

And just as in the Tuscan and the US data, the median age of first “HIV-positive” test has drifted upward over the years:

Whatever the reasons may be for these drifts — changing composition of the populations being tested, changes in the tests themselves — they are certainly inconsistent with what one expects for a sexually transmitted condition about whose dangers the propaganda has been intense. As people become older and less at the mercy of pheromones and hormones, and as they learn from experience to behave less self-destructively (or as the more self-destructive die off), they surely become less and not more likely to contract this particular sexual disease.
But HIV/AIDS theory demands that we believe that all the panic and propaganda of the last 25 years has led mature adults, people exposed to that propaganda for all that time, to behave more foolishly as to sex than do adolescents and young adults. Let’s have some more of that great snake oil, please, and I’ll take another Brooklyn Bridge as well.

Then there’s that shibboleth about the dangers of mother-to-child transmission. Italy reports a total of 62,000 AIDS cases from 1982 to 2009, 27% of whom were women, therefore some 16,700. Yet only 716 cases of mother-to-child transmission have been recorded — in Tuscany, the region with the highest prevalence of “HIV-positive”, not a single pediatric AIDS case since 2001. Since the median age of “HIV-positive” women is right in the prime child-bearing years, this is so low as, once again, to throw into ludicrous question the tenets of HIV/AIDS theorists.

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As in the US data, the Italian data show astonishingly regular trends — astonishing, that is, for a sexually transmitted pathogen. Regular trends is another way of saying reproducible, predictable. The incidence of a sexually transmitted infection varies over time, by region, by sex, by age . . . as illustrated copiously in The Origin, Persistence and Failings of HIV/AIDS Theory (for example, Figure 5, p. 32, and Table 5, p. 34 for gonorrhea, and Figure 4, p. 32, Figure 7, p. 33, Figure 8, p.35 for syphilis). By contrast, “HIV-positive” is ALWAYS at a maximum in early middle age; ALWAYS greater among those of African ancestry than among those of Caucasian ancestry, among whom it is ALWAYS greater than among people of Asian ancestry. In the United States, Hispanics on the West Coast are ALWAYS much less “infected” than Hispanics on the East Coast, be it among gay men or among child-bearing women or among soldiers or any other tested group.

Please explain those regularities as compatible with sexual transmission; and pass that snake oil again while you’re at it.