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The impact of HIV/AIDS on Southern Africa's Children
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| 2. The HIV/AIDS Epidemic in the Southern African Development Community |
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In June 2001 the HIV/AIDS pandemic was described by Secretary-General Kofi Annan at the United Nations General Assembly Special Session on AIDS as the greatest threat to global health since the Black Death of the 14th century. But attention to the global HIV/AIDS pandemic does not change the fact that it has been, and still is, primarily an African issue. Of the 40 million people currently living with HIV/AIDS, 28.5 million are African (71.25 percent); Africa currently has an adult HIV prevalence rate of nine percent, globally this rate is only 1.2 percent.
If Africa is badly affected by HIV/AIDS, then Southern Africa is the epicentre. One third of the global population living with HIV is in the Southern African Development Community (SADC)
countries2.Here the latest data from UNAIDS estimates that 13.79 per cent of the adult population is infected with HIV, although there is great variation among countries: from 0.1 per cent in Mauritius to 38.8 per cent in Botswana. The most recent antenatal clinic surveys of women attending state clinics show rates are continuing to rise: ANC HIV prevalence rate is 24.8 per cent in South Africa [Department of Health, South Africa, 2001] and 34.2 per cent in Swaziland [Kingdom of Swaziland, 2000]. In Botswana, consistent prevalence rates of over 40 per cent have been recorded in some antenatal centres [Government of Botswana, 2001].
That HIV prevalence continues to rise in Southern Africa is cause for very serious concern. Even more worrying, the spread is far more uniform between urban and rural areas than was the case in East Africa, which previously had the highest rates of HIV infection. A review of the data from the (SADC) region is given on Table 1.
Table 1: HIV Prevalence, Infections, Orphans, and Deaths in the SADC Region in 2001 Compiled from UNAIDS, 2002
| Country |
Estimated Adult Prevalence % |
No. of adults & children living with HIV/AIDS |
AIDS orphans (cumulative living) |
AIDS deaths(adults and children) |
Population |
| Angola |
5.5 |
350 000 |
100 000 |
24 000 |
13 527 000 |
| Botswana |
38.8 |
330 000 |
69 000 |
26 000 |
1 554 000 |
| D R Congo |
4.9 |
1 300 000 |
930 000 |
120 000 |
52 522 000 |
| Lesotho |
31 |
360 000 |
73 000 |
25 000 |
2 057 000 |
| Malawi |
15 |
850 000 |
470 000 |
80 000 |
11 572 000 |
| Mauritius |
0.1 |
700 |
No data |
<100 |
1 171 000 |
| Mozambique |
13 |
1 100 000 |
420 000 |
60 000 |
18 644 000 |
| Namibia |
22.5 |
230 000 |
47 000 |
13 000 |
1 788 000 |
| Seychelles |
No data |
No data |
No data |
No data |
No data |
| South Africa |
20.1 |
5 000 000 |
660 000 |
360 000 |
43 792 000 |
| Swaziland |
33.4 |
170 000 |
35 000 |
12 000 |
938 000 |
| Tanzania |
7.8 |
1 500 000 |
810 000 |
140 000 |
35 965 000 |
| Zambia |
21.5 |
1 200 000 |
570 000 |
120 000 |
10 649 000 |
| Zimbabwe |
33.7 |
2 300 000 |
780 000 |
200 000 |
12 852 000 |
| Total/average |
13.7 |
14 690 700 |
4 964 000 |
1 180 000 |
207 031 000 |
Notes:
1. there are no data in the 2002 UNAIDS report for Seychelles
2. Totals are calculated by the author for the SADC region.
Although for the countries comprising SADC the main mode of HIV transmission is heterosexual,
the epidemics are far from uniform. Understanding how each epidemic is different, what the driving
forces are and how the epidemic fits the basic epidemiological curve is important when considering
management and mitigation strategies for current and future impacts of the epidemic. The graph below
shows the progression of HIV over time for 133 of the 14 SADC countries.
Figure 1: Estimated adult4 HIV prevalence in the SADC region (1997—2001)
(Source: UNAIDS, 1998,1999,2002.)
There have been models developed to project HIV prevalence such as those of the POLICY Project,
www.policyproject.com. These projections assume past trends in transmission, incubation period, medical interventions and behaviour continue into the future. Figure 2 gives HIV prevalence as projected by the POLICY Project in October 2001. Both Botswana and Malawi have already levelled off at 37 percent and 15 percent respectively, but the epidemics as a whole in the region will only begin to peak and then plateau from 2005.
Figure 2: Projected HIV Prevalence (1980—2010)
(Source: The POLICY Project, 2001).
Understanding HIV/AIDS
HIV/AIDS is a long wave event as compared to other epidemics. The true death toll cannot be estimated until the full wave form of the epidemic has been seen. It may be as long as 20 years before we can say that the world epidemic has peaked and/or begun to decline. If we take into account the social and economic impacts of the epidemic, in particular HIV/AIDS related poverty, it is clear that this will get very much worse over the coming years and decades unless there is a concerted effort to address it.
The long wave nature of the epidemic can be simply understood by making reference to Figure 3, which shows HIV prevalence and cumulative AIDS cases. The key concept is the epidemic curve. HIV, indeed any disease, will move through a susceptible population infecting some, missing others. Epidemics follow an “S” curve as shown in the Figure. They start slowly and gradually. If a critical mass of infected people is reached then the growth of new infections accelerates thereafter. The epidemic then spreads through the population until those who are susceptible and exposed have been infected.
In the final phase of an epidemic—where the “S” flattens off at the top, and turns down—people are either getting better or deaths outnumber new cases so that the total number alive and infected passes its peak and begins to decline. With most diseases the curve will decline rapidly. HIV and AIDS are different. What sets HIV and AIDS apart from other epidemics is that, as shown there are two curves. With other diseases, infection is followed by illness with in a few days or weeks. In the case of HIV the infection curve precedes the AIDS curve by between five to eight years. This reflects the long incubation period. This is why HIV/AIDS is in some ways such a lethal epidemic compared to, say, Ebola Fever. In the latter case people fall ill quickly and visibly, putting the general population and public health professionals on their guard.
Figure 3: The Two Epidemic Curves
(Source: Whiteside and Sunter, 2000.)
HIV infection moves through a population giving little sign of its presence. It is only later—when substantial numbers are infected—that AIDS deaths begin to rise. People do not leave the infected pool by getting better as there is no cure. They leave by dying (of AIDS or other causes). The effect of life-prolonging ARVs is, ironically, to increase the pool of infected people. In Figure 3 the vertical axis represents numbers of infections or cumulative illnesses and the horizontal axis time. At time T1, when the level of HIV is at A1, the number of AIDS cases will be very much lower, at B1. AIDS cases will only reach A2 (i.e. the same level as A1) at time T2. By then years will have passed and the numbers of infected people will have risen even higher.
Understanding the HIV Curve
The HIV epidemic curve is the line that goes to point A1.
Very often this is the only data we actually have. In most countries all we actually “know” is the data
from surveys on HIV prevalence in AN Clinics. Figure 1 shows the ANC HIV epidemic curves for a number of
SADC countries. It is these data that are used to calculate the adult prevalence rate, number of
infections, illnesses, deaths and orphans and to make projections of future HIV prevalence. There are
a number of models that are used to do this. Most accessible are the Spectrum models developed by The
Futures Group International www.tfgi.com as shown in Figure 2, but South Africa has its own models and
modellers, in particular the Actuarial Society of Southern Africa (ASSA) www.assa.org.za Modellers and
actuaries have regular review meetings and UNAIDS has a Modelling Reference Group. In developing this
scenario paper the minor differences between the models are not considered significant.
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Key point: We can change the shape of the future curve, we can prevent more infections from occurring and this is the first challenge for an organisation such as Save the Children.
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Understanding the AIDS Curve
Despite the high levels of HIV infection, the consequences of this disease are only beginning to be felt in Southern Africa. This is because HIV has a long incubation period before people begin to fall ill. Thus is we refer back to Figure 3 and set time T1 as mid-2002 then the number of cases at HIV prevalence of A will only be B, and these cases represent infections that took place some four to eight years earlier. However we can be sure that the number of AIDS cases and deaths will occur. To give an example according to projections made in 2000 [Whiteside and Sunter, 2000], in 2002 South Africa would have about 4.5 million people living with HIV, but only an estimated 331 000 AIDS cases and 245 000 deaths. By 2010, 6 million South Africans are projected to be living with HIV; there will be 813 000 AIDS cases; and, 551 000 deaths. The cumulative number of deaths will have risen from fewer than 750 000 at the beginning of 2002 to about 4 million in 2010. The number of orphans will have risen from 425 000 to close to 2 million over the same period.
Adequate care and treatment can prolong life and improve its quality and productivity, but even the most advanced triple-drug anti-retroviral therapy (ART) does not cure HIV/AIDS. The increased morbidity and mortality from this disease has far reaching consequences.
Perhaps the starkest impact is on life expectancy, which in some countries will fall to levels below those seen fifty years ago. This, in turn, has a dramatic and negative impact on one of the few composite measures of development: the United Nations Development Programme’s (UNDP) Human Development Index (HDI). Life expectancy figures provide one third of the weighting for the calculation of the HDI, the others being educational attainment, which is measured by literacy and enrolment rates and standard of living, which is measured by real gross domestic product (GDP) per capita. We must note that figures on life expectancy are modelled rather than observed.
Table 2: Life expectancy and place in the Human Development Index
| |
1996 Report (1993 data) |
1997 Report (1994 data) |
1999 Report (1997 data) |
2001 Report (1999 data) |
| Life expect. |
HDI (rank) |
Life expect. |
HDI (rank) |
Life expect. |
HDI (rank) |
Life expect. |
HDI (rank) |
| Angola |
46.8 |
0.283 (165) |
47.2 |
0.335 (157) |
46.5 |
0.398 (160) |
45.0 |
0.422 (146) |
| Botswana |
65.2 |
0.741 (71) |
52.3 |
0.673 (97) |
47.4 |
0.609 (122) |
41.9 |
0.577 (114) |
| D R Congo |
51.2 |
0.517 (125) |
51.3 |
0.500 (130) |
50.8 |
0.479 (141) |
51.0 |
0.429 (142) |
| Lesotho |
60.8 |
0.464 (130) |
57.9 |
0.457 (137) |
56.0 |
0.582 (127) |
47.9 |
0.541 (120) |
| Malawi |
45.5 |
0.321 (157) |
41.1 |
0.320 (161) |
39.3 |
0.399 (159) |
40.3 |
0.397 (151) |
| Mauritius |
70.4 |
0.825 (54) |
70.7 |
0.831 (61) |
71.4 |
0.764 (59) |
71.1 |
0.765 (63) |
| Mozambique |
46.4 |
0.261 (167) |
46.0 |
0.281 (166) |
45.2 |
0.341 (169) |
39.8 |
0.323 (157) |
| Namibia |
59.1 |
0.573 (116) |
55.9 |
0.570 (118) |
52.4 |
0.638 (115) |
44.9 |
0.601 (111) |
| Seychelles |
71.0 |
0.792 (60) |
70.1 |
0.848 (51) |
71.0 |
0.755 (66) |
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| South Africa |
63.2 |
0.649 (100) |
63.7 |
0.716 (90) |
54.7 |
0.695 (101) |
53.9 |
0.701 (94) |
| Swaziland |
57.8 |
0.586 (110) |
58.3 |
0.582 (114) |
60.2 |
0.644 (113) |
47.0 |
0.583 (113) |
| Tanzania |
52.1 |
0.364 (144) |
50.3 |
0.357 (149) |
47.9 |
0.421 (156) |
51.1 |
0.436 (140) |
| Zambia |
48.6 |
0.411 (136) |
42.6 |
0.369 (143) |
40.1 |
0.431 (151) |
42.9 |
0.554 (117) |
| Zimbabwe |
53.4 |
0.534 (124) |
49.0 |
0.513 (129) |
44.1 |
0.560 (130) |
42.9 |
0.544 (117) |
The situation will get worse as people living with HIV develop AIDS and the number of people dying increases. The U.S. Bureau of the Census has calculated what life expectancy will be by 2010. They suggest that in Botswana it will fall to 37.8 years; in South Africa to 42.4 years; and, in Zimbabwe to 38.8 years [US Bureau of the Census, 1998].
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Key point:
the number of AIDS cases and deaths with consequent social economic and political impacts are certain to rise. Of central importance is providing care for the millions of affected and infected children. To date there has been little evidence that this is being planned for.
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Footnotes:
- The SADC countries are: Angola, Botswana, Democratic Republic of Congo, Lesotho, Malawi, Mauritius, Mozambique, Namibia, South Africa, Seychelles, Swaziland, Tanzania, Zambia and Zimbabwe.
- No estimates are produced by UNAIDS for the Seychelles.
- Adults are considered to be all those between the ages of 15 and 49 years.
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