HIV/AIDS World Health Organization
Key features of the epidemic
A number of points can be drawn from this brief survey. There are differences between and within countries in terms of the size, timing, and location of the epidemics, they are not homogeneous; prevalence rates have risen to levels believed impossible a decade ago; and the epidemic does not respect national borders.
The timing varies. Where the epidemic was reported early, such as in Uganda and Thailand, by 1990 HIV prevalence had peaked and was declining; whereas in Southern Africa, HIV did not begin spreading among the general population until the 1990s, and in the former Soviet Union, a rapid increase in prevalence began in the late 1990s. In some countries HIV has plateaued, although deaths may have been simply replaced by new infections. In other settings the small numbers of infections in particularly vulnerable populations are remaining stable. Given the ‘right’ change in circumstances, a broader spread might occur.
The maximum possible extent of the epidemic is uncertain. In 2002, UNAIDS, reporting on Southern Africa, noted that HIV prevalence had reached levels ‘considerably higher than had previously been thought possible’. There is a ‘natural limit’ beyond which prevalence will not grow, when everyone who is likely to be infected has been. The highest national prevalence recorded so far was Swaziland’s 42.6% among antenatal clinic patients in 2004; in 2006, prevalence had fallen to 39.2%.
Location refers both to physical geographic (spatial) location and particular population groups. There are epidemic hotspots. For example, in Brazil national prevalence is well below 1%, but in some cities infection levels of over 60% have been reported among IDUs. African prevalence is higher in urban areas, near major transport routes, and at trading centres than in the rural areas, and some of the highest localized prevalence rates have been recorded at border posts.
Sometimes clearly defined groups can be identified, usually those on the margins of society and who face legal or social stigmatization: sex workers, drug users, and men who have sex with men. In China’s central provinces many cases are due to the sale of blood. Peasants sold their blood, the plasma was extracted, and what was left was pooled and transfused back, a practice that prevented anaemia in the donors but ensured rapid spread of HIV, hepatitis, malaria, and other blood-borne diseases.
In other provinces of China there is primarily an IDU-driven epidemic. The international dimension of the epidemic is not always appreciated. It can be illustrated with two examples. In South East Asia, the ‘golden triangle’ is the main opium-producing area and covers the mountainous region where Myanmar, Laos, and Thailand meet and has links into southern China, the states of eastern India, and northern Vietnam. Drugs are a major illegal export and the area is home to many addicts and hence infected people. If the golden triangle were a country, it would have a high prevalence and be a major source of concern to ‘its’ government.
The second example concerns the UK, where, since 1996, there have been 29,357 HIV diagnoses. Year after year the number of new diagnoses has risen steadily, from 2,014 in 2000, to 4,474 for 2003, the last year for which there are complete data (the Health Protection Agency reports 4,287 cases in 2004 but expects numbers to rise as more data are received). The vast majority of new HIV infections worldwide – 92.5% – were heterosexually contracted. Of these, 78.6% were infected in the developing world, most in Southern and Eastern Africa. Some of these people are political or economic refugees, others have been recruited to work in fields with skills shortages.
Migration and refugee flows are contributing to the continued increases in HIV prevalence in many European countries. It is a complex and difficult problem, and reaffirms HIV/AIDS as a global dilemma even for countries where prevalence is low.
Key concepts: prevalence and incidence
Prevalence and incidence are key concepts in epidemiology and are important for understanding the spread of HIV and associated data. Prevalence is the absolute number of people infected. The prevalence rate is the proportion of the population that has a disease at a particular time (or averaged over a period of time). With HIV, prevalence rates are given as a percentage of a specific segment of the population, for example adults aged between 15 and 65, antenatal clinic patients, blood donors, or an ‘at risk’ group. HIV prevalence data come from surveys: in the early years, surveys were done among blood donors, STI clinic patients, people with TB, and pregnant women.
Incidence is the number of new infections over a given period of time. The incidence rate is the number per specified unit of population (this can be per 1,000, per 10,000, or per million for rare diseases) and period of time (in the case of cholera, for example, this can be per day or week). Measuring HIV incidence is complex and expensive.
People infected with HIV remain so for the rest of their lives; the only way they leave the pool of HIV infections is to die. This means the prevalence can continue rising even after the incidence has peaked, and the introduction of ART makes understanding data more complex as people live longer. In this example, incidence peaks in year 6, and prevalence continues to rise, then the introduction of ART in year 9 means that it rises even more rapidly.
Where information comes from
In the early days AIDS cases caught the headlines and provided an indicator of the spread. The number of people falling ill and dying rose relentlessly; no one knew who was at risk or how far the disease would spread. Each country counted the number of AIDS cases and sent this information to the World Health organization (WHO), which then reported on the state of the global pandemic.
AIDS case data are no longer routinely collected, except in well-resourced countries. The most commonly used and reported information is HIV prevalence; the estimated number of infections; and the number of orphans due to AIDS. HIV prevalence is given as the percentage of those infected of all adults (until recently this was given as people between the ages of 15 and 49).
Data sources
The best source of information, other than looking at each country individually, is UNAIDS, which produces a biannual report including a statistical annex. These data are mainly based on what is collected and reported by each country. This gives rise to problems, and in some instances, we simply do not know what the situation is. There are few data from states in conflict, such as the Democratic Republic of the Congo or Sudan, or those without a functioning government to collect, collate, and disseminate information, for example Afghanistan and Somalia. Data may simply not be credible due to inefficiency and government failure. An example is Nigeria: data reported by UNAIDS in 2006 for Nigeria came from surveys done in 2001, at only 10 urban and 70 rural sites. In Zimbabwe it is hard to believe reliable HIV data are being collected as the health system is overstretched and the economy is collapsing.
Data are sensitive. UNAIDS was unable to publish an estimate of the numbers of people infected with HIV in India in 2004 as the government would not agree to a figure (although they were allowed to put in an estimate: 2,200,000 to 7,600,000 infections). In July 2007, new estimates were released by the Indian Government, UNAIDS, and the WHO, putting the figure at between 2 and 3.1 million infections. For political reasons, the UN finds it difficult to make negative comments on the quality of the data with which they are presented.
The 2006 UNAIDS report notes the global estimates of people living with HIV/AIDS are lower than previously reported. This is because of genuine declines in prevalence in some settings and because new data are available from population-based surveys.
The 2006 report looks at all adults, whereas previously only those aged 15 to 49 were included. More HIV-infected people are living beyond 50, and ART will increase this further.
The most consistent prevalence data come from women in antenatal clinic (ANC) surveys. Originally this population was chosen because they provided the best sample: blood was routinely taken for other tests; the women had been sexually active; and the surveys could be done on an anonymous basis, meaning the sample could not be linked to individual women, so informed consent was not required.
ANC data give a reasonable picture of the epidemic provided biases are recognized. The main biases are that men are excluded; younger women are over-represented (as they are more sexually active and likely to fall pregnant); HIV-positive and older women are under-represented as HIV infection and age reduce fertility; and surveys usually draw on women attending public antenatal clinics. This last point means women who are too poor to access the government clinics and also those who get private health care will be excluded.
Once data are available, it is possible to estimate the number and percentage of all women, men, and adults who are infected, as well as the number of children who will be born HIV positive, by using models that adjust for the biases. Some models are in the public domain and accessible through the Internet.
New data are becoming available through population-based surveys of HIV prevalence, which collect nationally representative information on HIV prevalence and provide data on characteristics associated with infection and risk. Most have been done as part of the Demographic and Health Surveys (DHS). Since 2001 there have been 13 surveys carried out and published by the US-based Macro International Inc., and a further 20 are in various stages of completion at the time of writing in 2007. A comparison between the recent DHS results and UNAIDS estimates showed that in three cases UNAIDS estimated adult prevalence was higher, in four instances lower, and in the remaining six the rates were the same. Both DHS and ANC data sets can be used provided they are treated with care.
Two population surveys in South Africa were carried out for the Nelson Mandela Foundation by the Human Sciences Research Council, in 2002 and 2005. The entire population, except children under 2, was sampled. The 2002 survey found a prevalence rate of 17.7% among women aged 15–49. By 2005, it had increased to 20.2%. The survey allows us to locate the epidemic by age and gender. This figure is typical of the heterosexual epidemics. If a graph of prevalence were drawn for Russia, it would show more men than women infected, as their epidemic is being driven by IDUs.
In addition to surveys among ANC patients, specific risk groups, and population-based studies, there are other data sources. Most common are of specific occupations such as the military, teachers, health workers, and employees of particular companies (although these may not be in the public domain). A survey of teachers in South Africa in 2005 showed HIV prevalence was highest in the 25–34 age group (21.4%), followed by the 35–44 age group (12.8%). This has policy implications, as teachers are crucial for economic and social development. In Nigeria, HIV prevalence among army troops was estimated to be less than 1% in 1989/90, it increased to 5% in 1997, and 10% in 1999. Among Nigerian troops in Sierra Leone, prevalence increased from 7% after one year to more than 15% after three years of duty in the operational area.
In Botswana, Debswana, the diamond-mining company, carried out its first survey in 1999 and found HIV prevalence across all employees was 28.8%. The company decided to provide ART for staff and spouses, re-target their prevention programmes, and requires ‘AIDS compliance’ from contractors. They maintained their policy of testing scholarship applicants for long-term training abroad and refusing those who were HIV positive.
The 2003 survey showed HIV prevalence had fallen to 22.6%: in permanent employees it was 19.9% and among contract employees 28.3%.
In 2006 there were cautious suggestions that global HIV incidence might have peaked, perhaps even in the late 1990s. The 2006 UNAIDS epidemic report revised the global number of people living with HIV slightly downwards from its 2005 figures. However, HIV data must be seen against a backdrop of the three curves. In 2002, it was estimated that HIV/AIDS caused 4.9% of deaths globally and a quarter of all deaths from infectious and parasitic diseases. The WHO estimates that in 2015 AIDS will still cause one in six deaths in Africa.
