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Revised History of HIV in Kenya – Part VII – Health Facilities


Part VI explored the possibility that family planning and Sexually Transmitted Infection (STI) services may have been provided in health facilities that would later be deemed unsafe in the context of HIV, involving reuse of syringes and other equipment with inadequate or no sterilization. Many determinants have been identified for STIs throughout the twentieth century, all over the world. They include poverty, poor education, unemployment, ‘promiscuity’ (Meheus, 1974), low prevalence of contraception and others. STI prevalence tended to be higher among men than women, high in both urban and rural areas, higher among unmarried than married people (Hopcraft, 1973) and fairly evenly distributed around a country such as Kenya. In contrast, HIV is more likely to be associated with relative wealth, better education, employment, proximity to roads and other infrastructure, higher use of contraception, urban dwelling, marriage and others. More women than men are infected, associations with sexual behavior considered unsafe are often not very strong and prevalence is unevenly distributed, with a few hotspots in Kenya and many ‘coldspots’. One might logically conclude that, while HIV can be transmitted sexually, it is often transmitted in other ways, and that is why patterns of infection for HIV differ so much from patterns of infection for other STIs.

However, there are important overlaps in these patterns of STI and HIV infection. For example, HIV prevalence was found to have reached 4% among Nairobi sex workers in 1981 and increased to 61% by 1985; this was established by retrospectively testing stored blood samples (Piot P, 1987). Females infected with non-HIV STIs in the past were generally found to be engaged in sex work or had a partner who had visited a sex worker. Prevalence of STIs was often high in certain occupational groups, such as transport workers, soldiers and those employed in extractive industries. As a result, these and other groups had long been targeted by STI eradication programs; sex workers had also been targeted by various family planning initiatives. This suggests that those facing high risks for infection with STIs, or assumed to face high risks, may have had increased non-sexual risk of being infected with HIV once that virus began to spread (having established itself several decades before). Although HIV prevalence went up to 81% among sex workers in Nairobi, it peaked in 1986 and declined steadily for nearly 20 years without any reasonable explanation being found for this trajectory (Kimani J, 2008). Oddly enough, neither Piot et al nor Kimani et al consider the very strong possibility that sex workers (and members of other targeted groups) were systematically infected with HIV through unsafe healthcare until this risk was eventually recognized (or perhaps changes in practices reduced the risk of transmission without anyone noticing the impact this was having on healthcare transmission until much later?).

In the early 80s, no precautions had been taken to prevent the transmission of blood-borne viruses such as HIV in health facilities, as the virus had only just been discovered. Throughout the 80s, as it became apparent that health facility transmission was (or could become) a significant risk, certain measures were taken to improve safety. But the changes would not have been adequate to eliminate transmission altogether. In the 90s, as mentioned in Part III, access to health facilities declined, which may have inadvertently protected many people from infection; HIV incidence in the general population peaked some time in the 90s, at a time when visitor numbers to health facilities would have been falling as a result of increasing poverty, the introduction of ‘user fees’, cuts in service provision and other factors. Sex workers and others thought to be ‘promiscuous’ must have faced a very high risk of being infected with HIV in STI and family planning facilities, although the risk must have decreased considerably some time in the 80s and continued to decline, without ever being completely eliminated.

As for those not considered to be so ‘promiscuous’, they would also have faced high risks in general health facilities. Family planning and STI facilities were often integrated into general healthcare services. Women attending antenatal care (ANC) services and giving birth may have faced higher risk than others (aside from sex workers and other groups targeted by STI and family planning programs). This makes it less surprising that very high HIV rates were found in ANC clinics from the late 80s onwards. HIV prevalence is often highest among women of childbearing age. While these same women may (or may not) be more sexually active that others among whom HIV prevalence is lower, they clearly face increased non-sexual risk of infection with HIV at ANC clinics that are not particularly safe. Family planning services were promoted widely, often aggressively promoted, and not just to those thought to be ‘promiscuous’. Family planning, ANC, contraception and even general health services tend to be more accessible and more utilized in urban areas, by wealthier, better educated people (Hopcraft, 1973), the very groups found to be more likely to be infected with HIV. So people with HIV are more likely to have faced various non-sexual risks, whatever about their sexual risks. Why do UNAIDS and the HIV industry seem only to consider their sexual risks? Piot et al and Kimani et al are not exceptional in completely ignoring the possibility of massive levels of healthcare transmission of HIV; the entire industry has grown out of denying that unsafe healthcare could have played a part in transmitting a virus that is a lot less efficiently transmitted through heterosexual sex.

For a long time in Kenya (and other developing countries), family planning had been seen as a means of ‘promoting economic development’, as well as ‘improving maternal and child health’. It wasn’t just highly intrusive and aggressively promoted because it was seen as beneficial to Kenyans and other Africans, but also because it was seen as a means of reducing population growth and averting an eventual global shortage of food, water and vital resources. In the same way that preventing and treating diseases in developing countries was a way of ensuring a ready supply of cheap labor in resource rich countries, family planning was seen as a way of controlling birth rates and population increases beyond what was needed for labor. For many NGOs operating in African countries now, family planning is development; and ‘maternal and child health’ consists of, pretty much, family planning. It is seen as something of a truism that maternal and child deaths can be reduced most readily by reducing fertility rather than, say, improving conditions in hospitals and elsewhere.

A 1973 paper reveals something about conditions in STI clinics in Uganda (Arya, 1973). For a start, it is pointed out that over 90% of the population lives in rural areas. Therefore, most of the population’s health needs are catered for by rural health centers, dispensaries and other minor facilities, staffed mainly by auxiliaries, rather than by more highly trained professionals. Whether it is because STIs were common or because the colonial and post-colonial administrations were exceptionally interested in them, Arya argues that “venereal disease played an important role in the organization of the medical services in Uganda in the beginning of this century.” Mulago Hospital, started in the second decade of the 20th century as an STI clinic, became and remains the largest referral hospital in the country. This is similar to Kenya, with specialist STI services being available in Mombasa and Nairobi for many decades. Health expenditure is low, estimated at around one dollar per year per person in the mid 70s, but basic health services were provided free of charge. Arya alludes to the lack of success of most STI programs, in both developing and rich countries, in bringing these diseases under control; he suggests that there are other diseases that may be in more urgent need of attention. Arya also notes that private practitioners provide STI services, mainly in larger towns, and that the quality of these services is unknown.

Arya published a paper in 1976 about the role of medical auxiliaries in STI control in developing countries (Arya & Bennett, 1976). In common with some other authors, Arya and colleague draw attention to the high disease burden faced by developing countries, coupled with the scarce resources, human, financial and material. These are particularly acute in rural areas, where most people live, but where well qualified professionals are reluctant to work. The authors also feel that STI services are mismanaged to the extent that they may be causing more problems than they are solving, with high prevalence resulting from “inadequate treatment, improper treatment or no treatment at all”. They mention high treatment default rates, find the contribution of private practitioners to STI control ‘questionable’ and conclude that the overall quality of services is poor. Diagnoses were unreliable (Burney, 1976), patients were receiving repeated injections of small doses of penicillin, which increased resistance, etc. Another paper notes the injection of large volumes of penicillin in some countries, which is likely to have involved the use of glass syringes and reusable needles in those days (Meheus, 1974). Contact tracing was generally beyond the capacity of STI service providers. Arya and Bennett recommend that medical auxiliaries specialize in STIs and that their training includes “knowledge of the local socio-cultural factors which largely determine traditional sexual mores” and note that STI patterns “differ from those in the western nations and may even vary from one area to another within a country”.

The papers cited above and in Part VI give a few insights into what things were like in terms of STI programs in Kenya and Uganda in the 1970s. Many of those said to be dying of ‘slim disease’ in Uganda in the early 1980s could have been infected with HIV as long as ten years before. If the rate of new infections peaked in the late 1980s, transmission would have been increasing throughout the 1970s, reaching its peak in the late 1970s. Why incidence peaked and then declined is another story. It may have had something to do with the 1978-1979 war with Tanzania (wars tend to be periods of low HIV transmission (Gisselquist, 2004)), the civil war from 1981-1986 or, much more likely, a combination of factors. Incidence began to increase a few years later in Kenya, perhaps in the mid 1970s, reaching a peak in the early 1990s, as discussed elsewhere. However, incidence started to increase earlier among certain groups, such as sex workers, transport workers and others who, significantly, had been targeted by STI eradication programs for decades. Incidence also would have peaked and begun to decline earlier in these groups.

Conditions in Kenyan health facilities in the 1970s, especially those providing STI and family planning services, were poor. If a blood-borne virus were to establish itself in one or more of these facilities, there would have been plenty of scope for it to be transmitted widely, not just among populations aggressively targeted by various health programs, but also among those requiring other health services, such as antenatal care. The risks of widespread transmission of HIV in health facilities were not recognized for a number of years and many more years had passed before any of these risks were addressed (some have yet to be addressed). But western HIV awareness campaigns were hijacked long ago by various parties who wished to present the virus as one transmitted almost entirely through ‘promiscuity’, and who wished to deny the possibility of transmission in health facilities. Because most of those infected in African countries were heterosexual, a different story about transmission needed to be created. Unfortunately, the same campaigns and strategies were exported from wealthy countries, where transmission was almost entirely a result of male to male sex or intravenous drug use. These campaigns were supremely unsuccessful in Kenya, but this was blamed on the failure of individuals to change their sexual behavior, rather than on any non-sexual mode of transmission.

If HIV transmission in health facilities and through other non-sexual modes continues, the virus will not be eradicated. More poignantly, if health facility transmission had been addressed in the 1980s, when it was realized that this was a very efficient mode of transmission, the virus would never have infected so many people. Some of the worst epidemics in the world only got going in the late 1980s or early 1990s, such as Zimbabwe, Botswana, South Africa, Swaziland, Mozambique and others. Many of the biggest players (bureaucrats, politicians, publicists, academics, industrialists, etc) currently driving the HIV industry have been in the business since the 1980s. Must Kenyans and other Africans wait till these ‘experts’ are gradually replaced by more enlightened personages? It is to be hoped that new generations of practitioners are not obliged to choose between adopting the deeply engrained institutional prejudices of their profession, or accepting the status of ‘dissident’ or ‘denialist’, unable to publish, teach or even present their views to the industry.

 

REFERENCES:

 

Arya, O. (1973). Changing patterns in the organization of the venereal diseases and treponematoses service in Uganda. Brit. J. vener. Dis, 134-138.

Arya, O., & Bennett, F. (1976). Role of the medical auxiliary in the control of sexually transmitted disease in a developing country. Brit. J. vener. Dis., 116-121.

Burney, P. (1976). Some aspects of sexually transmitted disease in Swaziland. Brit. J. vener. Dis., 412-414.

Gisselquist, D. (2004). Impact of long-term civil disorders and wars on the trajectory of HIV epidemics in sub-Saharan Africa. SAHARA J., 114-27.

Hopcraft, M. V. (1973). Genital infections in developing countries: experience in a family planning clinic. Bulletin of the World Health Organization, 581-586.

Kimani J, K. R.-A. (2008). Reduced rates of HIV acquisition during unprotected sex by Kenyan female sex workers predating population declines in HIV prevalence. AIDS, 131-7.

Meheus, A. D. (1974). Prevalence of gonorrhoea in prostitutes in a Central African town. Brit. J. vener. Dis., 50-52.

Pepin, J. (2011). The Origins of AIDS. Cambridge : Cambridge University Press.

Piot P, P. F.-A. (1987). Retrospective seroepidemiology of AIDS virus infection in Nairobi populations. J Infect Dis, 1108-12.

Revised History of HIV in Kenya – Part V – UNAIDS’ Rorschach Hypothesis


As I said in earlier posts, HIV arrived in Kenya and remained unnoticed until the 1980s. It is said to have spread rapidly throughout the 80s, especially in certain places (such as Nairobi, Mombasa, Nyanza province and perhaps a few others), but also to have remained low in other places (such as the North and Northeast). The rate of new infections, incidence, peaked in the early to mid 1990s and declined thereafter. So prevalence peaked in the late 90s or early 2000s, with high death rates, which may have peaked in the mid 2000s. The epidemic has a long early years tail (1950s-1980s), a humped back, possibly very humped, and a longish neck. Perhaps the curve resembles an outline of a diplodocus, complete with a little bump where the head should be, but just a small head.

With prevalence peaking at a little over 10%, but only for two or three years, the period of high transmission or incidence would have been six or seven years previously (going backwards again, for a moment). That suggests something catastrophic in the mid to late 1980s and early 1990s that was responsible for much of this rapid transmission. Whatever that something was, it didn’t result in rapid spread of HIV before the 1980s, and it ceased in the 1990s. It also ceased to result in rapid spread of HIV after a brief few years. Does that sound like sexual behavior to you? It does to the HIV industry, who have been trying to redescribe similar phenomena in all high HIV prevalence African countries.

So the diplodocus is not the only kind of epidemic curve; there are several dinosaur-like curves that you can spot using UNAIDS data. Many of them look very similar, but there are some whose backs rise two or three times higher than any of those found in East Africa, for example Zimbabwe. A few more countries show an epidemic that exploded in the 1990s but haven’t dropped yet, such as Swaziland and Lesotho. The Dinosaur is also a good metaphor for some of the institutions and international NGOs that have systematically resisted one of the best arguments for universal primary healthcare ever (HIV, that is), and continue to resist it to this day. HIV is almost all a matter of individual sexual behavior, they say.

But I did mention being drawn to spatial and temporal factors, rather than ‘populations’. Even in my first attempt at characterizing Kenya’s epidemic it was clear that there wasn’t really a ‘national’ epidemic. Instead, there were places where HIV prevalence was exceptionally high, and even more places where HIV prevalence was low. Over time, there were places, high and low prevalence, where the curves looked nothing like dinosaurs. They were more like pancakes in low prevalence areas, sometimes with a small piece of fruit under them, and Mexican hats in high prevalence areas. Could this data really describe sexual behavior over time? I was skeptical, not believing that almost all HIV could be sexually transmitted, as the HIV industry was claiming.

Then it was confirmed to me that HIV is frequently transmitted through unsafe healthcare, cosmetic and traditional practices, such as reused syringes and other equipment and practices in all three scenarios, with the second and third involving razors and other sharp objects that are used to pierce the skin, often the same ones over and over again, without any attempt at sterilization. Reasonable people were arguing that various kinds of bloodborne transmission were the only phenomena that could explain the Mexican hats. That accorded well with what I could glean from the literature. It just doesn’t accord with what the HIV industry insists: we know it’s all about sex, they insist, even when you present instances where it couldn’t possibly be.

I can give you about 50 reasons why I don’t believe HIV is entirely a matter of sexual behavior without even putting much thought into it (I’ve already written the list). But here are 10, with supporting links, so you can follow them up if you are interested. I’ll supply more in Part VI, perhaps even the rest, I’m not sure yet. Many of the reasons I give overlap with the factors involved in HIV transmission that I listed in Part IV, so if you wondered about any of them, you’ll probably be able to match the two lists, eventually. I may even merge them some time, but not now.

1 Prevalence is often higher among rich people. Consult the Demographic and Health Survey (DHS) for most African countries with serious HIV epidemics and you’ll find this. There is a table of HIV prevalence by wealth quintile that I drew up and it is available on a linked blog post I wrote recently.

2 Prevalence is often higher among better educated people. Again, the DHS gives data on this for all high HIV prevalence countries, but here’s a graph with some of the data in a table.

Education focus countries

3 High prevalence often clusters around transport infrastructure. Here’s a wonderful map of Africa where you can see why there are the several HIV regions I mentioned in an earlier part. But notice that ‘spatial accessibility’ or ‘friction’ that they mention do not explain all the regions. West Africa has a less serious epidemic than both East and southern Africa, yet there is good transport infrastructure there.

4 High prevalence often clusters around big employers, such as mines, plantations, etc. But miners and those employed in large numbers face other threats, such as employer supplied healthcare, public health programs, tests, checkups, STI programs and whatever else. Some may face additional sexual risks when they spend 11 months of the year in an all male hostel, but anyone who thinks that this sub-human treatment only impacts on victims’ sexual behavior needs psychiatric assessment.

5 Prevalence is usually higher in urban areas (where non-sexual risks are also higher). But there are multiple differences between urban and rural areas, only some of which relate to sexual behavior. The HIV industry loves going on about ‘sexual networks’, and not just in African countries. But what about the appalling conditions most urban dwelling people experience when they are born in a city or when they move to one? Slums are dangerous places, where children die of water borne diseases that cost a few cents to cure because what they need is clean water, to ensure they don’t get any of a multitude of waterborne diseases. Babies and children die of pneumonia and various respiratory problems, again, easily avoided and treated. But even if you pump a child full of available vaccines and send them back to the same environment, many of them will just die of something else. Adults die of all kinds of things as well, often as a result of the terrible living conditions. Many die or are disabled by road traffic accidents and other kinds of serious injury. Slums, where about 75-80% of Kenya’s urban dwellers live, are dangerous. Does anyone who has thought about it really think the only risks they face are sexual?

6 Prevalence is usually lower in rural areas (where non-sexual risks are also lower; have a look at any DHS). This is not to say that people don’t face hazards. They also don’t receive the benefits of public health programs that are available to people in the cities. Of course, this can protect them from healthcare associated HIV and other diseases but many vaccines work well, a lot of common diseases can be prevented or cured. However, when it comes to HIV, rural dwellers seem to be a lot better off, and inaccessibility of healthcare facilities may have protected them, at least in the recent past. My guess is that while some may be involved in ‘sexual networks’, just as people all over the world are, these do not explain everything.

7 HIV prevalence is not particularly closely related to ‘unsafe’ sexual behavior. For example, DHS figures for sexual behavior among young people in Zimbabwe show how tenuous the connection is. Even the authors were unable to interpret them. But a careful look at sexual behavior figures for many countries show that the numbers engaging in these behaviors tend to be a lot smaller than the numbers not engaging in them. These levels of ‘unsafe’ sexual behavior would not be able to explain the Mexican hat graphs in Nyanza and in Kenya’s major cities.

8 Prevalence is often lower among those who never use condoms. As the linked article shows, condom use is often associated with higher rates of transmission than non use. The authors try to imagine arguments to show why condoms look like they are failing more often than not, but they don’t come up with anything convincing. The figures in the article have been superseded and there’s a more up to date table in a blog a wrote a short time ago. My guess is that condom use is higher among urban dwelling, better educated, wealthier, employed people, and that’s why you get these same patterns for condom use in so many countries. Again, this strongly suggests that HIV is not purely a matter of sexual behavior.

9 HIV prevalence is low in areas where ‘intergenerational’ marriage and sex, that is, between people of very different ages, are more common. I’m linking to a blog post I wrote recently, no point in repeating the whole thing again. The data is from DHS for various countries.

10 HIV prevalence is low in areas where ‘traditional’ practices are more common, such as traditional medicine. These tend to be more common in rural and isolated areas. A possible exception to this is genital mutilation. There are two kinds, only one of which is ‘traditional’. The first kind takes place in a health facility, so that’s usually male genital mutilation. The second kind does not take place in a health facility and includes male and female genital mutilation. It’s hard to say which is more likely to transmit HIV. If mass male circumcision was being carried out in a health facility where infection control procedures were not followed properly, not an uncommon occurrence, then healthcare associated transmission could be very likely, and would be serious; some practitioners are carrying out twenty operations a day, apparently. Traditional circumcision, which has its own hazards, is carried out in entirely unsterile conditions and adverse events are common. But it may be less likely that a HIV positive person is being circumcised along with other initiates. Prevalence should be low among young uncircumcised males. Even if they engage in sex before the wound has healed, those with whom they have sex should also be less likely to be infected. But whether done in a clinic or in a field, genital mutilation is risky. Female genital mutilation generally takes place in unsterile conditions and the risks of some forms may be higher than those faced by males. But female genital mutilation is also more likely to take place in rural areas, where HIV prevalence is lower. It is said that almost 100% of Ethnic Somalis in Kenya’s Northeastern province, both male and female, are genitally mutilated, but HIV prevalence is very low.

HIV probably did very little for years in Kenya. But next to nothing for years is the way to go from being a species jump that should never have survived to being a pandemic. Perhaps a clearer history of how it survived and spread, to explode in the late 80s or early 90s, will tell us more about what is still driving transmission, in Kenya and elsewhere. But there are already many reasons for believing that HIV is not only transmitted through sex. One would want to be seriously disturbed to interpret every factor involved as evidence of sexual behavior.

Revised History of HIV in Kenya – Part IV – Diversity


Why is HIV spread so unevenly? In some parts of Kenya prevalence is at ‘hyperendemic’ levels, over 20%, almost 30% in one county. Yet in other counties it is low, 1% or lower. If, as we are constantly told, 80%, even 90% of HIV transmission is a result of unsafe sex (most of the remaining 10-20% being a result of mother to child transmission), what amazing sex lives people in some counties must have (or disgraceful, if you prefer). And what dull (or worthy) lives those in other counties must have, apparently only having sex for the purpose of procreation.

If, on the other hand, HIV is not always a result of sexual behavior, if many people may be infected through unsafe healthcare, even unsafe cosmetic and certain traditional practices, some of the factors involved in HIV transmission rates, low or high, start to make a lot more sense. The list of factors is long (over 40), but the italicized paragraphs are the kind of explanations given by the ‘it’s all about sex’ camp, so they are mostly the same. Yes, some HIV transmission is a result of sexual behavior, nobody is denying that, but some is not. Also, some areas where HIV transmission is high are in need of further study; a priori explanations for high and low prevalence have no place in science (though they seem to receive a warm welcome in a lot of papers on HIV epidemiology).

Christian

Prevalence is often higher among Christians than Muslims, and generally among males than females; not sure why this is so; the majority of HIV positive people in the world live in predominantly Christian countries, meaning that a lot more Christians than non-Christians are infected; why this is so is not clear, although both healthcare access and HIV prevalence are noticeably low in some Muslim dominated countries

Men less likely to be circumcised; also Christians are ‘less restrained’ in their sexual behavior than Muslims

Circumcision

There is no clear evidence that circumcision reduces HIV transmission and it could only influence sexual transmission, at best; however circumcision is risky if carried out in unsafe healthcare facilities or in traditional settings

Circumcision ‘cleaner’ or ‘more hygienic’, although this is a hypothesis, there is no unambiguous evidence

Colonization

The vast majority of HIV positive people live in countries that were colonized by the British. This may relate to healthcare facilities, access to healthcare, health seeking behavior, infrastructure, stability, etc

It’s somehow related to sex

Condom use

HIV prevalence is higher, often far higher, among people who sometimes use condoms than among those who never do, suggesting that HIV risk is not always sexual

Those who are already infected are more likely to use condoms

Culture

Cultural practices such as female genital mutilation (FGM) may increase the risk of being infected, although it increases both sexual and non-sexual risks; yet prevalence among people who practice FGM is generally low, which suggests that there are other factors involved

Increases HIV transmission; if prevalence is low this can be explained away by reference to attitudes towards extra-marital sex, etc

Depo Provera

Increased risk for women taking it and for their partners

Denies that this is a risk and claims that the benefits (prevent conception) outweigh any disbenefits, which don’t exist anyway

Education

Educated people may have better access to healthcare and be more likely to use healthcare

Educated people have access to bigger sexual networks

Employment status

People with a job can afford healthcare, although this may not be safe healthcare; jobs may include healthcare or health insurance; some occupations provide healthcare services;

People with a job have more money and therefore access to bigger sexual networks; despite prevalence generally being higher among employed people, some suggest that unemployed people have little else to do but have sex

Female

Prevalence is usually higher among women, possibly because they have more need to use healthcare services, especially when pregnant and giving birth; they are also more susceptible to sexual transmission

Women are more vulnerable and have less power to make choices; they are usually victims, otherwise they fall under one of the many categories of sex worker

Fertility

Higher fertility may increase healthcare exposure, although it is often associated with low prevalence areas, rural areas, etc

Higher fertility means more unprotected sex

Healthcare

Healthcare may not always be safe, which may explain why countries with good access to healthcare for everyone, such as Botswana, may result in higher HIV prevalence

Sick people, including people with HIV, seek healthcare, which is why healthcare may seem to be associated with higher HIV prevalence; this is especially true of STIs

Hepatitis

HBV and HCV are much more likely to be transmitted through non-sexual routes, such as unsafe healthcare, cosmetic and traditional practices, also injection drug use

Presence of HBV and/or HCV are signs that the person is either promiscuous or an intravenous drug user (or both)

Herpes

Rates can be extremely high in some populations because it is very easy to transmit, sexually and through other routes; it plays a role in being infected with and transmitting HIV but the role is complex

It is a sign that people infected engage in unsafe sex and increases risk of transmitting and being infected with HIV

Inequality

It is neither clear that inequality is associated with higher risk, nor why this may be so

People are more vulnerable to sexual risk, especially women

Infrastructure

Good infrastructure is often associated with high HIV prevalence, which may suggest better access to unsafe healthcare

Good infrastructure gives access to bigger sexual networks

Male

Prevalence is usually lower among men than women, which leaves a question mark over instances of higher prevalence among men when they are found, for example, Muslim men in Kenya; prevalence may be lower because of lower use of health facilities

Men are considered to be mere spreaders of sexually transmitted disease, whether they are rich or poor, urban or rural dwelling, etc

Marriage

Sometimes HIV prevalence is far higher among married than unmarried people and it is not clear why

Married people are less likely to use condoms; they also have extra marital sex, usually the men, then they go home and infect their spouse

Migration

Migration can be for work, which may involve work-related healthcare, which may be unsafe and may not be subject to levels of scrutiny faced by public facilities, however scrutinized  they may be

Migrants, being away from home, either have other sexual partners or visit sex workers; they then return home to infect their spouse

Mobility

Possibly increases access to health facilities, but mobility on it’s own doesn’t seem to explain high prevalence

Mobile people have access to bigger sexual networks

Muslim

Figures vary, with prevalence higher among Muslims than Christians in some countries (eg, Burundi, Rwanda, Mozambique, but not Kenya or Tanzania), also higher among Muslim men than women in others, eg Kenya; not sure why this is so

Men more likely to be circumcised; also Muslims are ‘more restrained’ in their sexual behavior than Christians

National borders

High HIV prevalence has been reported at border areas in the past and rates of unsafe sexual behavior may be higher; but the sex workers and long distance drivers who are said to be responsible for high rates have often taken part in STI eradication programs and may frequently use STI clinics

Long distance drivers have sex with sex workers, then they go home and have sex with their spouses

Occupation – armed forces

Members are unlikely to have any option as to whether they take part in various health programs, tests, etc; healthcare is likely to be free, which means usage is also probably higher

They have access to bigger sexual networks and frequently visit sex workers

Occupation – fishing

Prevalence is high in fishing communities, not necessarily highest among the fishermen; also, very high prevalence seems to be a feature of only some fishing communities, especially lakes; not sure why HIV prevalence is so high

Fishermen do risky work, therefore they are not bothered by sexual risk; also, they spend a lot of time away from home; also, they use sex as a bargaining tool

Occupation – mining

Artisanal mining is not so much associated with HIV so this probably applies to industrial scale mining; the work-related healthcare to which miners have access (they may even be compelled to receive certain health services and tests) may not be safe

Miners work a long way from home and don’t see their family much so they have extra-marital relationships and/or visit sex workers, then go home and infect their spouses

Occupation – teaching

Prevalence has been claimed to be higher and lower among teachers, at different times and places; they probably face similar risks to other public sector employees, whatever those may be

Teachers frequently have sex with their pupils (which may be true, and should be addressed, but it may turn out to have little to do with HIV transmission)

Occupation – transport

Transport workers may use health facilities more; also, they may have been persuaded to take part in STI eradication programs as they have been blamed for all sorts of things; these STI programs may not always have been safe

Transport workers are mobile, which means they have access to bigger sexual networks; then they go home and infect their spouses

Polygamy

Sometimes associated with higher transmission, sometimes with lower transmission, therefore not clear. It is not only practiced by Muslims but also by some tribes and even at least one Christian sect in Kenya

When prevalence is higher, this is because polygamy involves ‘concurrency’; when lower, it’s because men with more than one wife don’t need to have extra-marital sex, or not as much

Population density

Increases pressure on health facilities

Said to increase the size of sexual networks

Population growth

Increases pressure on health facilities

Said to increase the size of sexual networks

Poverty

HIV prevalence is often lower among poorer people, suggesting that they may face lower risk from, for example, unsafe healthcare because of reduced access; however, being poorer means that the only healthcare available may be unsafe

If prevalence is high, poorer women are more vulnerable (to sexual transmission) for various reasons;  if it’s lower, poorer people are less likely to be part of a ‘sexual network’ or their networks are likely to be smaller

Prisoners

There may be some kind of drug use that involves cutting or skin piercing (seems unlikely injection drug use would be common); healthcare is unlikely to be very comprehensive or safe; tattooing and traditional medicine may be additional risks, perhaps also scarification, blood oaths, etc

They have sex with other prisoners, the implication being that the sex includes anal sex; and/or injected drugs or drugs that involve skin piercing; condoms are usually not permitted

Rural

Rural dwelling people have less access to health facilities and infrastructure, which may go some way to explaining why prevalence is usually lower in rural areas

Rural dwelling people have access to smaller sexual networks

Schistosomiasis

This has been shown to increase susceptibility to infection and onward infection, which suggests that some people have sex, not very surprising; but endemic schistosomiasis, which is very cheap to treat, suggests weak healthcare systems

Lots of people having lots of sex with lots of other people all the time: schistosomiasis only adds to what is a ‘known issue’

Sex work

Prevalence among sex workers is low among some sex workers in Western countries unless they also engage in injection drug use but their biggest risk in countries with unsafe healthcare could be their frequent exposure to STI clinics and STI eradication programs; also, a lot of what is referred to as ‘sex work’ is in fact sex between people who are in a relationship or married; many people who are related, in a relationship or married also do business with their partner or relative; ‘gift giving’ is sometimes said to be a form of ‘transaction’ between two people who have sex; this is a very stigmatizing use of the term ‘sex work’ (a bit like the term ‘orphan’, which refers to children in developed countries who have lost both parents, but children who have lost one parent in developing countries; or the word ‘trafficking’ which seems to refer to just about anything that involves sex and that can attract funding to ‘rescue victims’ from)

Sex workers are forced into sex work by poverty, powerlessness, vulnerability, etc, but their consequent risks are high and entirely sexual, unless they are also injection drug users

STIs

STIs do not only suggest unsafe sexual behavior, they also suggest a health system that is failing; some are also transmitted through non-sexual routes, such as herpes and HIV

STIs are a sign that a person engages in unsafe sex

TB

TB is likely to be an occupational disease in deep mines, though mining operations deny this, as they don’t want to compensate those who contract it, pay for their treatment or improve conditions in mines; it increases HIV transmission in both directions

HIV positive people are more susceptible to TB

Tribe

Prevalence is high in some tribes and low in others (high among Luos, low among Somalis in Kenya, for example), which suggests that there may be several factors involved; there are ‘risky’ practices in tribal groups among whom HIV prevalence is low, as well as high (for example, female genital mutilation, which is widespread among Somalis)

‘Tribal’ practices and/or ‘traditional’ practices can be wheeled out on any occasion, either to explain high prevalence or low prevalence; they often involve sex or some form of brutality an are generally inflicted by men on women

Urban

Urban dwelling people have easier access to health facilities and other infrastructure

Urban dwelling people have access to bigger sexual networks

War/civil conflict/refugee camps

Prevalence is generally low during wars and only increases after the war has finished, perhaps because health seeking behavior changes during wars, health facilities become less accessible, money is short, infrastructure is destroyed, etc

If HIV is transmitted it is because people take advantage of the situation, rape and other forms of sexual violence being common; but as prevalence is usually lower it is claimed that sexual networks become smaller, people return to rural areas, etc

Wealth

Prevalence is often higher among wealthier people, suggesting that they may use healthcare more frequently; they may also face occupation related risks that are also non-sexual

Wealthy people can become part of larger sexual networks; they have more opportunities for sex and are more likely to avail of these opportunities

Widowhood

Prevalence among widows and widowers can be very high but it is not clear why

Widows are, in some cultures, inherited, having been widowed because their husband (obviously) died of AIDS; they are ‘cleansed’ (have sex with their inheritor) who may be the brother of the deceased, and infect him; he goes on to infect his other partners, including his spouse

The list above makes no claim to be exhaustive. When there is so much diversity in HIV epidemics within and between countries, why would anyone conclude that almost every factor is, ultimately, a matter of sexual behavior, or somehow relates to sexual transmission? It’s no wonder, given the above list, that HIV positive people are feared, even despised. It is the view that transmission is almost always sexual that results in the stigma UNAIDS and other institutions claim to abhor and pretend to be fighting; they are the source of the stigma. HIV ‘prevention’ programs that include some or all of the italicized arguments above merely spread the stigma.

Revised History of HIV in Kenya – Part III – Chronology


I mentioned some historical factors in Part II, so I’ve put together a timeline for Kenya’s epidemic, which seems appropriate in a history, especially a quick and dirty one. Some of the factors involved in HIV epidemic spread date back to the beginning of the century (or the beginning of humanity in the case of population). The table only lists some factors that have played, or are said to have played, a significant role; others will crop up later.

HIV Timeline Kenya

[Click on image to expand]

These factors would not have made it in any way inevitable that HIV would spread rapidly in certain places, more slowly in others and hardly at all in a few. That’s not what I’m arguing here. But there is an exception, a factor which doesn’t yet appear in the above table. Unsafe healthcare facilities to which the majority of a population has access render outbreaks of certain diseases more likely, and probably facilitate the exponential growth of some of those diseases more efficiently than any other factor possibly could. This is not true for HIV alone (or even MRSA in wealthy countries). TB can spread in health facilities (though deep mines are likely to be far more notorious in this instance), as seen in the case of Tugela Ferry in South Africa. Hepatitis C (and B) has often been spread widely through public health programs, such as in Egypt. Ebola is also very easily spread this way, and early accounts from some outbreaks are fairly explicit about this. Many of the people infected in the current outbreak are healthcare personnel. Many more were likely to have been infected by contact with other infected people in health facilities, perhaps even through contact with doctors and nurses (either because the doctors or nurses were infected or because their protective clothing was contaminated). Unsafe healthcare, as mentioned in Part II, is said to have ‘kickstarted’ the HIV epidemic. But conditions in healthcare facilities in African hospitals are appalling, so unsafe that the UN warns its employees not to use them. Tourists are warned to avoid injections and other procedures, even to carry their own injecting equipment. It’s only Africans themselves who are urged to go to health facilities and public health programs, without any warnings about unsafe practices or risks.

What is inevitable is that, if there is ever an outbreak of a disease that can be spread through unsafe healthcare, it will result in a serious epidemic in countries where conditions in healthcare facilities are unsafe. Such outbreaks have been documented in the case of HIV in Libya, Kazakhstan, Kyrgyzstan, Romania and other countries. But the possibility of such outbreaks in sub-Saharan African health facilities has not been investigated. Or, if such an occurrence has been investigated, the findings have never been published.

So there were political, economic, environmental, ecological, demographic and various other factors in play long before HIV first reached Kenya, said to be some time in the 1950s. They are briefly mentioned in the above table because they need to be explained, which requires some historical detail (more than a superficial account is beyond the scope of this post). Therefore, I shall jump to the end of the colonial period right now and address remaining issues another time.

The first 10 or 15 years of independence saw a lot of progress in Kenya, especially in education and healthcare. Spending increased to provide these and other services for everyone, rather than the select few who would have had access to them before independence. The relative prosperity of this period was short lived. Global and more local economic and political events in the 1970s and 1980s would have already begun to interrupt progress. But the need to accept loans from the World Bank and the IMF, which had strict ‘austerity’ conditions attached to them, spelled the end of improved access to health and education, cuts in all public spending, wage freezes, spiraling unemployment and a severely reduced public sector, including health and education, which are among the biggest employers.

In 1978 Moi took over from Kenyatta, the first president after independence, and was happy to comply with the stringent conditions demanded by these international financial institutions through their structural adjustment policies, as long as it meant he could get his hands on a lot of money. He remained president for 26 years, during which time the population went from 16 million to about double that figure, while health, education, infrastructure and other sectors were held, nominally, at around 1980s levels, although these sectors declined rapidly during the Moi regime.

This is where the story becomes surprising (if you think it’s all about sex). HIV had been around for a few decades, albeit unnoticed. But it spread rapidly from some time in the 80s and prevalence probably peaked in the late 90s, at 10 or 11%. Very high death rates, peaking in the early to mid 2000s, helped ensure that prevalence was halved by 2012 or 2013, according to the latest figures (although that’s 5% of a population that is increasing at over 2.5% per annum). But why would HIV prevalence decline when the worst effects of structural adjustment policies were being felt, from early in the 1990s onward, as it appears from my (admittedly rough) chronology? The annual rate of new infections, incidence, is said to have peaked in the early 90s, which would account for a peak in prevalence a few years later, and a subsequent drop. But we associate increased levels of spending on health, education, infrastructure and the like on development, better education, and better levels of health. How could the epidemic appear to be receding at precisely this time? The country had done nothing to deserve improvement in any area of health, let alone HIV, which Moi refused to acknowledge for most of his term of office.

When I wrote the brief account of HIV in Kenya five years ago, I was still busy questioning some of the completely unexpected findings I had uncovered for my dissertation, most or all of which the HIV industry was already aware. Why were wealthier people often more likely to be infected? Why were urban dwelling people also more likely? Why were ‘unsafe’ sexual behaviors often little more associated with HIV transmission than an absence of such behaviors, or the presence of ‘safe’ sexual behaviors? In Kenya, almost all development indicators were at their lowest in the Northeastern province, but HIV prevalence was also lowest there. Condom use was minimal, fertility rates were high even for Kenya, gender inequality was high, polygamy was common, as was female genital mutilation, intergenerational sex and marriage (large differences in age between partners, usually older men and younger women) were far more common than anywhere else in the country, and many people had little knowledge of HIV.

The list continues. Population was growing rapidly in some of these areas, several were undergoing urbanization (or something similar) and population density was increasing in others. Shortly after I started studying HIV it was clear to me that it couldn’t possibly be all about heterosexual behavior, I just didn’t know what could account for very high prevalence figures in some places and low figures in others. Upon visiting Kenya in 2002, when everyone told me about ‘traditional’ practices and all manner of factors that resulted in high rates of HIV transmission, they were also talking about how ‘abstaining’ (a word I associated with religion), ‘faithfulness’ (a word I associated with courtly love) and ‘condomizing’, a word I didn’t associate with anything at all, were resulting in declining prevalence figures. How could this be, and weren’t high death rates already explaining these drops in prevalence?

Obliged to exclude certain modes of HIV transmission from my dissertation to keep it focused and within size restrictions, I was advised to lose sections on non-sexual HIV transmission. It took me a about a year to get back to that, but when I did, all the previously unexpected findings started to make sense: I was sure that HIV wasn’t solely transmitted through sex, I just didn’t know that the HIV industry had been so strenuously denying the proportion that unsafe healthcare, cosmetic and traditional practices had been contributing in the past, and were still, obviously, contributing. It became clear that the industry somehow resembled an old boy network infused with a kind of freemasonry, a fair amount of evangelical zeal, and a good helping of neo-eugenicism acquired from some of the big NGOs that got in on the HIV act early on.

HIV is transmitted through heterosexual sex, that’s not in question. But people in Northeastern province don’t have much access to healthcare, infrastructure, education or many other benefits, and that is what may have protected people living in that province from HIV. In contrast, people living close to better developed infrastructures, people in cities (especially Nairobi, Mombasa and Kisumu), wealthier people and people living closest to health facilities may have, where conditions in health facilities were not adequate, faced very high risks. They are not ‘at risk’ populations, so much as ‘populations put at risk’ by the institutions that persuade them to avail of their services but can’t always provide these services safely. There are, indeed, certain behaviors that increase the risk of being infected with HIV, but they are not all sexual behaviors, they are not all individual behaviors and they are not all the behaviors of poor, uneducated, powerless people, either.

It’s not that health, education and infrastructure are not benefits, they are. Kenyans and people of all underdeveloped countries need more healthcare, more education and more (appropriate) infrastructure, lots more than they have ever had. But unsafe healthcare can be a lot worse than no healthcare. When structural adjustment policies reduced access to the benefits of health, education and others, they may also have reduced the exposure of most people in Kenya to an important, but rarely discussed, HIV risk.

An estimated 1.6 million people are living with HIV today, but that’s a relatively small percentage of the population. HIV prevalence in countries with far better and more equitable access to health facilities, such as Botswana, is among the highest three in the world. The HIV region where the epidemic is said to have begun, with relatively poor infrastructure, also has a far less serious epidemic than the southern region. Where road networks are almost entirely absent, such as in the Northeastern province of Kenya (and some countries in low prevalence North Africa), there are few health facilities, and access to these facilities is low. But along Kenya’s best road networks (which are certainly nothing to boast about) HIV prevalence is higher. The best health facilities are not found in isolated areas, of course. But nor are the best health facilities likely to have been safe places in the 1980s and 1990s. Some of them are still unsafe, we just don’t know how unsafe, and exactly what proportion of HIV is transmitted through unsafe healthcare.

Infrastructure alone didn’t result in rapid transmission of HIV, much of that was built during the colonial period. Nor did the existence of health facilities, or even public health programs, guarantee that a HIV epidemic would be severe. But increased access to health facilities where safety standards sometimes (often?) fell below par might explain the huge increases in HIV prevalence that occurred inside very short periods. People outside of the HIV industry would wonder how a virus that is difficult to transmit through heterosexual sex could appear ti occur in ‘explosive’ outbreaks, with prevalence doubling in less than a year. The industry would assure them that ‘Africans’ clearly engage in levels of unsafe sex that is beyond what any non-Africans could manage. Those whose prejudices already matched those of the HIV institutions accepted this explanation. Anyone who continued to question such a racist view of HIV was accused of denialism and shunned by their professional colleagues (unless they didn’t have any professional colleagues, or a profession).

Much of the evidence collected over the last 30 years, even evidence collected by the HIV industry itself, points to a rule of thumb: you can not work out levels of sexual behavior from HIV prevalence; and you can not work out HIV prevalence from levels of sexual behavior. But the HIV industry, outrageously, insist that high HIV prevalence in African countries is evidence for high rates of ‘unsafe’ sexual behavior, and  that high rates of sexual behavior ‘explain’ or predict high rates of transmission.

When I turned my attention to non-sexual HIV transmission I came by a small group of people who are still questioning the orthodoxy, as they had been doing for many years. Some have retired, others don’t depend on HIV related funding for their work, most are doing it for free. There are those who had been involved in HIV related work, and they are either ignored or treated with contempt for even talking about unsafe healthcare, or anything else that makes the sexual behavior paradigm look like the institutional racism that it is. The mere mention of some names involved can end a conversation, or elicit  no more than a peremptory gesture, which is the only evidence the HIV industry has yet been able to muster against the possibility that non-sexual modes of transmission may make a significant contribution to the most severe HIV epidemics in Africa.

In Kenya, people will still tell you about how much ‘Africans’ love sex. If you ask why prevalence in Homa Bay, bordering on Lake Victoria, is 135 times higher than it is in Wajir, not far from the border with Somalia (though not very close to anything else worth speaking of), they will say that people around Lake Victoria love sex. Beyond that, they have no credible explanation. Every now and again there’s a flurry of activity around some issue that attracts the media’s attention and this can crop up in conversations. For example, in 2002 some people were still talking about ‘devil worship’, for which a well publicized commission was set up, and which never published the results of its inquiries. But HIV stories drowned out even stories as titillating as devil worship. People around Lake Victoria will tell you with great relish about the sexual behaviors of fishermen, ‘barmaids’, transport personnel, Ugandans, Luos (the predominant tribe around Lake Victoria) and various other groups that have at various times been held up for scrutiny by the HIV industry and, as a result, thoroughly stigmatized.

HIV has been in Kenya since just after the middle of the 20th century and it was recognized from the early 1980s. It has spread around the country, though very unevenly, perhaps over a period of 40 years. The HIV industry has convinced Kenyans that it is individual sexual behavior that ‘spreads’ HIV. But transmission rates declined before any effort was made to address the epidemic, something the HIV industry are unable to explain. So the epidemic is still very much alive, and unexplained by the orthodox story. Kenyans still don’t know what is driving the epidemic, therefore they don’t know how to prevent it from continuing.

There’s more, a lot more. Hopefully I’ll have time soon.

Revised History of HIV in Kenya – Part II – Spaces and Times


It might sound reasonable to start a history of a virus that was only identified in the 1980s in the same decade, or perhaps the decade before, just to be safe. But many of the phenomena that are said to be involved in the HIV pandemic go back a long way. There’s no need for me to start with the earliest known historical accounts, nor even with the time the virus ‘jumped species’, from chimps to humans. That history has been well described elsewhere. But I have chosen to start at around the beginning of the 20th century for several reasons.

HIV itself can be dated to the early part of the century using genetic dating techniques, for one thing. But also, Britain had established Kenya as a protectorate in 1895. Christianity was already on the way to becoming the predominant religion (although there had been Christian Kenyans for several hundred years). Nairobi and other cities were only ‘trading posts’, but some of them eventually became heavily (and densely) populated. Several of the most important exports in Kenya today were already significant parts of the economy many decades ago. Even international social, health, educational and financial institutions that were eventually to play an important (though by no means always positive) role in Kenya’s development have been around for over half a century. Some environmental and ecological issues that only came to a head later had already begun, and much of the country’s current infrastructure was developed early on in the British occupation, to facilitate the extraction of resources, move large numbers of workers and soldiers around, etc.

I think it will become apparent why these issues are worth looking at. There is a potentially huge list of other issues that may be relevant, but I’m concentrating on the ones that I believe are in need of greater attention. Most official accounts of HIV epidemics, from the likes of the WHO, UNAIDS and others, obsess about labels, various ‘vulnerable’ groups, specific populations said to exemplify certain kinds of behavior (almost always sexual and generally presented as somehow illicit or ‘deviant’), people engaged in certain occupations and others. Examples from UNAIDS’ latest offering (The GAP Report 2013), another multi hundred page, multicolored, expensively produced document, with some well chosen photographs are: “People living with HIV, Adolescent girls and young women, Prisoners, Migrants, People who inject drugs, Sex workers, Gay men and other men who have sex with men, Transgender people, Children and pregnant women living with HIV, Displaced persons, People with disabilities [and] People aged 50 years and older”; but other groups can easily be generated, and no doubt are, as and when required.

Naturally, we are concerned about human beings, people, their health, rights, welfare and wellbeing. But people are not the one dimensional entities denoted by the labels spewed out by international institutions (‘international’ generally meaning wealthy countries). Instead, I would draw readers’ attention away from these ‘populations’, which almost all African people could be shoehorned into at some time in their lives; many would fall into several. I think it is far more fruitful, as well as a lot less demeaning, to pay some attention to places, for example, large-scale mines in southern Africa, ecological zones, such as Lake Victoria, certain hospitals and facilities that provide various health related services, perhaps even places where people go for cosmetic services and even various traditional practices, such as circumcision. As mentioned, HIV prevalence is low in the North African region, higher in the East African region and highest in the southern region. There are many spatial factors, and the HIV industry does consider them sometimes, but they always view them in terms of what kinds of sexual behavior may be practiced in high HIV prevalence areas.

In his book on the origins of HIV, mainly in Francophone African countries, Jacques Pepin talks about colonial health programs, which he and others sometimes refer to as ‘well meaning’. But, like infrastructure in general, health services were probably intended to enable the smooth running of armies, mines, companies exporting raw materials, such as timber and textiles, also high value goods such as tea. In other words, these ‘benefits’ were not developed, originally, for Africans; they were for colonials, for the colonial power. Mining companies and other big employers may find it good for business to be able to treat endemic illnesses that would otherwise threaten production (just as today, some might argue, funding is provided for diseases that we think may threaten wealthy countries, which was the case with HIV, and perhaps even ebola). Occupational and other private health services, also, may not be subject to the kind of (generally fairly superficial) scrutiny potentially faced by public health services. Pepin argues that healthcare transmission was very important early on in the pandemic, before AIDS was identified and the virus causing it was discovered. But he argues in the introduction that unsafe healthcare has long ceased to be a major factor in African countries. He also argues that almost all transmission, after a certain point in history, became sexual. For him, in a sense, there was an explosion of unsafe sexual behavior, although such a phenomenon has never been empirically described (sensationalist accounts based on high transmission rates, which have been empirically described, do not show that all or most transmission is a result of sex).

Despite the popularity of HIV related PR materials pointing the finger at certain people and their sexual behaviors, disease epidemics, HIV included, are not entirely determined by what individuals do. There are important environmental factors, ‘environmental’ being a very inclusive term indeed; and there is the pathogen itself, which I have less to say about. I have been concentrating to a large extent on spatio-temporal factors of the kind hinted at above because theories about ‘populations’ don’t seem to be very helpful, in addition to being highly prejudiced. Fishermen, miners, migrants, transport workers, teachers, soldiers and various others have at some time had the finger of blame pointed at them by the HIV industry. But often, a little background reading suggests that there is something other than their individual behavior, even their sexual behavior, that relates to high HIV prevalence. For example, HIV prevalence is very high in fishing communities, but it is not clearly highest among the fishermen themselves. Some research has suggested that proximity to and contact with Lake Victoria is associated with very high prevalence, not so much the occupations or behaviors of the people infected. Sex workers in some countries are unlikely to be infected, or at least, a lot less likely than sex workers in African countries (and infections are often a result of injection drug use). Sex workers in African countries may face elevated non sexual risks, such as frequent visits to sexual health clinics, where safety may not be prioritized. Also, some early reports of high rates among transport workers, teachers and healthcare workers may not have paid much attention to non-sexual risks, or they may have exaggerated sexual risks. Even some of the figures for prevalence have been exaggerated at times.

The HIV industry does, as I have said, pay attention to some of the factors that I would argue are important. It’s just that their starting point is how various phenomena clearly relate to people’s sexual behavior, without demonstrating that HIV is almost always transmitted sexually. People close to Lake Victoria may be more susceptible to HIV because of an endemic parasite called schistosoma. This means that sexual transmission of HIV is very significant, but there is no need to impute any kind of ‘deviant’ sexual behavior or any kind of ‘traditional’ practices that may (or may not) impinge on people’s sex lives. Just ordinary sex would be enough, sex in ordinary quantities, with ordinary people. Of course there are sex workers in Africa, just as there are sex workers everywhere. There are people who have a lot of sex in Africa, just as there are such people everywhere. But most people don’t have a lot of sex, and some have none at all. Regression to the mean doesn’t cease when you reach sub-Saharan Africa and sex is one of those things that most people can’t engage in to extreme levels. Whereas it is hard to imagine a limit to the amount of money one person can earn, there are several limits to how many different people one can have sex with, what kinds of sex, how often, etc. (I’m following Nasim Taleb’s concepts of Extremistan and Mediocristan; sexual behavior is probably not susceptible to black swan events.)

To finish Part II, HIV in Kenya is not just about individual behaviors, it is also about places, such as Lake Victoria, Turkana, Nairobi and other cities, and parts of those cities. The obsession with ‘African’ sexual behavior, which seems to have started with the eugenics movement, not with the discovery of HIV on the continent, has been entirely fruitless and highly stigmatizing. But the knowledge that certain places are clearly dangerous has yet to be translated into a similar obsession with healthcare safety, education about bloodborne HIV or a bit of effort to alleviate the most urgent concerns in the lives of ordinary people.

It’s also important also to consider certain temporalities in Kenya’s HIV epidemic. Pepin and others often mention things like societal breakdowns, urbanization, rapid population growth and the like, often with the implication that these ‘obviously’ explain massive increases in unsafe sexual behavior. But societal breakdowns did not start in the 1980s, no more than sex did (or even media fantasies about ‘African’ sexuality). Some societal breakdowns, such as wars, result in very low HIV transmission (for example, Mozambique, Angola, Sierra Leone, Somalia and others). Many societies are broken down but none of these breakdowns, that I have heard of, have been shown to result in widespread levels of unsafe sexual behavior. Urbanization and high population growth, too, have occurred at many times in many places. In Kenya there have been population growth rates as high as 8 or 9% per annum during the period 1969-2009. But often these high rates of growth were in areas where HIV prevalence never went very high, such as Mandera; some places where HIV prevalence is (or was) high experienced low population growth, such as Mombasa. Kenya’s epidemic is old enough to show that factors involved in the spread of the virus go back a long way and are still extant. Those factors, whatever they are, have eluded UNAIDS, WHO, CDC and other august institutions. But that doesn’t mean they can never be identified and successfully addressed.

Revised History of HIV in Kenya – Part I


[Note about tree graphs/maps/diagrams/charts used in this blog post: the best way to understand them is to try them out on Google Charts. They must be called ‘tree’ graphs because the data they display can also be represented in a tree diagram or organizational chart, in other words, hierarchical data. I think of them as Mondrian graphs, but they have already been named!]

It’s over five years since I wrote a Short History of HIV in Kenya and I have read, written and thought a lot more about the subject than I needed to then for my MA dissertation. So it’s time I updated things a bit, even though a thorough history would be an entire book. Sorry this history is quick and dirty, I don’t have time to do it the justice it deserves. If anyone needs links for any particular claim they will have to get in touch. I’ll try to supply them here at a later date. This is Part I, with Part II coming as soon as I can get around to it.

The history of Kenya’s HIV epidemic is very different from those of southern African countries, such as Swaziland, Lesotho, South Africa and Botswana, where prevalence is several times that found in East African countries, and where political, social, economic, demographic, industrial, environmental, infrastructural and other factors also differ greatly. Kenya’s epidemic history also differs from those of Namibia, Zambia, Zimbabwe, Mozambique and Malawi. All those southern African countries form the southern African HIV region, with the highest prevalence countries in the world.

Kenya is part of a different HIV region, the east African region, where national prevalence figures are usually below 10%. It just happens to coincide with East Africa as well! Epidemics in the East African region are older than those in the southern region, but they are not as old as those in the west central HIV region. Phylogenetic analysis shows that HIV probably originated in Southern Cameroon in the early 20th century and spent a long time in and around Kinshasa, in DRC. Various HIV (Type 1, Group M) subtypes emerged and some spread to other countries. For example, subtypes A and D, we are told, spread to East Africa in the 1950s and 1960s, respectively, and are still the dominant subtypes there.

Subtype C spread to southern Africa in the 1970s to completely dominate all the southern region epidemics (and Rwanda, although other evidence suggests the epidemic there is older than those in southern Africa, and therefore ‘eastern’). There is very little genetic diversity in the southern region, so the epidemic there is said to be newer than others. In East Africa there is a bit more diversity than in the southern region. But the greatest diversity is found in west central countries, Democratic Republic of Congo, Republic of Congo, Angola, Gabon, Cameroon, etc. There are also distinct West African and North African HIV regions, but I shall limit myself to the East and southern African ones, as I haven’t had the opportunity to study the remaining regions in much detail yet. Suffice to say, prevalence is lowest in North Africa, higher in West Africa and the west central region, higher still in East Africa and highest in southern Africa.

The following tree graph of prevalence in 14 East and southern African countries (percentage of HIV positive people aged 15-49) shows how much variation there is, ranging from less than 5% to over 20%. But all the highest prevalence countries are in the southern region (which makes some people wonder why some of the biggest countries by HIV funding are in East Africa and places other than southern Africa).

Focus countries prevalence tree graph

This can be compared to a tree graph of the numbers of people living with HIV (PLH) in each country, which also shows a lot of variation. In both graphs the two separate regions are very clear, with prevalence of over 10% in all the southern African countries and over 20% in three of them, and less than 10% in all the East African countries in the prevalence graph. However the graph for PLH shows that South Africa has the biggest epidemic, in fact, the biggest in the world, with over 6 million people living with HIV, more than in the whole of East Africa. It is of note that some of the countries with the highest prevalence have small populations (such as Swaziland, Botswana and Lesotho), and therefore relatively small numbers of PLH. If this graph were to include all countries by PLH, many of the countries below would be squeezed out, with Nigeria, India, the US and several others contributing more than the East Africa region.

Focus countries PLH tree graph

These are huge generalizations, and here’s another one: HIV has been around for a long time, perhaps a hundred years, and it must have continued spreading from the epicenter (otherwise it would have died out). Sometimes the virus is depicted as a massive ‘explosion’ in the 1980s, but it had probably been spreading, albeit very slowly, in most countries in East and southern Africa for several decades before such explosive outbreaks occurred. Also, when they occurred, they did so in certain parts of countries; prevalence remained low in most parts of most countries, or else the period of very rapid increase occurred later. The tree graph of prevalence by county in Kenya (the percentage of people aged 15-49 infected with HIV), below, will have to serve as an example of a country with high levels of HIV in some areas but low levels in others (similar patterns are clear in many high prevalence countries, but not all).

Kenya prevalence tree graph

National prevalence is said to have peaked in the mid 1990s in Kenya, reaching a little over 10% before dropping at the end of the 90s and gradually settling at around half that figure in 2013. Prevalence in Uganda, in contrast, became high in the late 1980s to peak somewhere between 10 and 15% in the early 1990s. Therefore, Uganda’s epidemic is a bit older and a bit more severe than Kenya’s. This may be because Uganda is closer to the epicenter of the epidemic, but there are probably also other reasons. Distance from the epicenter alone does not determine the eventual severity of an epidemic (prevalence in most west central African countries is lower than in most East and all southern African countries, for example).

In Kenya death rates probably peaked in the early 2000s. So, working backwards, if prevalence peaked in the mid to late 1990s, incidence (the annual rate of new infections) must have peaked several years before. A peak in the number of new infections would give rise to a peak in death rates about 10 years later, that being the average time someone infected with HIV would survive before dying from some AIDS related illness (and I must emphasize, these figures are rough).

So far, this is about a time that predates mass treatment for HIV. Treatment means that many HIV positive people can live a long time, perhaps as long as HIV negative people. However, few people would have been receiving treatment in African countries before well into the 2000s. The picture of Kenya’s epidemic is still grainy, but it should be clear that HIV spread far and wide over a longer period of time than some accounts suggest, and is probably close to 50 years old in the country (maybe plus or minus 10 years). More importantly, the picture is grainy because national prevalence figures suggest a fairly evenly spread epidemic, with a large sector of the population infected in each administrative or political unit.

But figures used to create the graph above, released a few months ago, allow us to bring the picture into better focus in Kenya (hopefully). The country recently went through various political changes that have resulted in the generation of prevalence figures for 47 counties, instead of the 8 provinces, which is all that was available previously. A quick look at some of these figures show just how blurred the picture was, for so long! (The graph below is prevalence by Kenyan province, the percentage of people aged 15-49 infected with HIV. If you compare these provincial level figures with the provincial figures for 2003, they are almost identical.)

Kenya prev provinces tree graph

 

The last graph is of the five Kenyan counties that border with Lake Victoria. Four of them are in Nyanza province and the fifth is in Western province, on the border with Uganda. Prevalence in Nyanza has remained around 15% for many years, with the highest figures in Homa Bay, Kisumu, Siaya and Migori and low rates in Busia. This graph is of numbers of people living with HIV in each county. But there is quite a range, with over 140,000 in Homa Bay and only 16,000 in Busia. There are more PLHs in Homa Bay than in the whole of Burundi (90,000). Also, there are more HIV positive people in Kenya than there are people in Swaziland.

Lake Victoria Counties

 

Because more detailed figures are available now, but figures for earlier periods are hard to find, unreliable and not easy to compare with others, I’m starting the history at the end. How did an epidemic that began so far away, and such a long time ago, come to be as it appears now in Kenya? Prevalence in certain areas is lower than in some US cities. But in other areas it is as high as the three countries with ‘hyperendemic’ HIV, at well over 20% prevalence (Swaziland, Lesotho and Botswana).

The HIV industry that has developed around this lucrative disease continues to insist that the virus is transmitted almost entirely through heterosexual sex in African countries. This is despite the fact that it is mostly transmitted among men who have sex with men in the US (which has the highest number of people living with HIV outside of sub-Saharan Africa), injection drug being use a somewhat distant second mode of transmission in most western countries. Prevalence is low, even very low, among heterosexuals in most countries in the world, so why would it be high in certain parts of certain African countries? This is the central question for me. I believe that a history of the epidemic in Kenya will shed some light on how the virus infected, and continues to infect, so many people in some places and far fewer in others.