'Promiscuous African' Explanation of HIV Falls Flat Again

It seems odd to compare Botswana with Sweden and to conclude that, because cross-generational marriages, usually referring to marriages between teenage girls and much older men, are common in Botswana but not Sweden, that must explain why HIV rates are high in Botswana and low in Sweden.

For a start, I expect there are many stark differences between Botswana and Sweden, including ones that may shed light on why HIV rates are so high in Botswana and so low in Sweden. But why compare those two countries? And why pick out cross-generational marriages, in particular?

Well, cross-generational marriages are just one of the many factors that have been said to increase HIV transmission over the years. Part of the reasoning is that teenage girls are unlikely to be very sexually experienced, but older men are, and so they are more likely to be HIV positive. The hypothesis on its own seems to be enough for the phenomenon to be the culprit.

But in most high prevalence countries, rates of discordance are very high. In other words, many HIV positive people have a HIV negative partner. And, although men are often said to be the main drivers of HIV transmission, especially in long-term partnerships, women are just as likely to be the HIV positive partner.

This means that, where both parties are infected, it may have been either the male or the female partner who became infected first. And this raises questions about how the female partner was infected, if she wasn't infected by her partner.

UNAIDS and the HIV industry have a ready explanation: if the female partner is African, then she is promiscuous. According to the orthodox view, this is just a fact. It may not stand up to scrutiny, but it is the lynchpin of pretty much all HIV prevention policy: Africans are promiscuous, and that's it.

Why so many more women than men are infected is not really clear if HIV is, as the orthodoxy claims, mainly sexually transmitted. HIV researchers often say that women are usually infected earlier and men later, often because of cross-generational marriages. But the figures just don't add up.

Men, on the whole, are far less likely to be infected, so there still remains a question as to who infects all the women where the ratio is something like 1.5 men infected for every 10 women, as is the case among the Luhya of Western Kenya.

Kenya's eight provinces were originally divided on ethnic lines and cross-generational marriage rates vary considerably between provinces. But the province with the highest HIV prevalence, Nyanza, doesn't have the highest rates of cross-generational marriage, not even the second highest. And the province with the second highest HIV prevalence, Nairobi, has almost the lowest rates of cross-generational marriage.

In contrast, the province with the highest rates of cross-generational marriage, North Eastern, has the lowest HIV prevalence. Prevalence there, at less than 1%, is lower than that found in many US cities. The diagram below is rough, but it shows that cross-generational marriage does not correlate with HIV prevalence. Interestingly, in North Eastern province, male and female prevalence figures are also very similar.

A lot more work needs to be done to show why some females in African countries face such high risk and why most males do not. Women may be more 'susceptible' to infection, as the industry never tires of telling us, but who is infecting them? It is unlikely to always be men, even if the promiscuous African 'theory' (in reality, a crude prejudice) so beloved by the industry is even vaguely true.

Rather than focusing on sexual behavior and marriage patterns, the author should have considered the relative quality and accessiblity of health services in Botswana and Sweden. He might have noticed that in places where many pregnant women visit hospitals and clinics in high prevalence countries, they seem to be far more likely to be HIV positive. If men tend to be infected later in life, perhaps women infected in hospitals are infecting them, another possibility not raised in this or most other articles.

The idea that HIV prevalence is higher in places where access to health services is higher and that HIV prevalence is lower in places where access to health services is lower is well attested and has been for some time. Indeed, Kenya's North Eastern province is a very good example. And elsewhere, urban and peri-urban areas have far higher prevalence figures than the most isolated areas, which often have very low rates indeed. Perhaps Dr Flamholc would like to develop his 'observations' a bit further.