The epidemiology of HIV infection among young people aged 15–24 years in southern Africa
Gouws, Eleanora; Stanecki, Karen Ab; Lyerla, Roba; Ghys, Peter Da
aEvidence, Monitoring and Policy Department, Switzerland
bStrategic Country Intelligence, UNAIDS, Geneva, Switzerland.
Correspondence to Eleanor Gouws, UNAIDS, 20 Avenue Appia, 1211 Geneva 27, Switzerland. Tel: +41 22 791 4237; e-mail: firstname.lastname@example.org
Objectives: To investigate epidemiological patterns and trends of HIV infection and sexual behaviour among young people aged 15–24 years in the nine countries in southern Africa most affected by the HIV epidemic.
Methods: Data on HIV prevalence among young people in the general population were obtained from national population-based surveys conducted between 2000 and 2007, whereas data on sexual behaviour were obtained from repeat surveys between 1994 and 2007. Linear or exponential regression was used to analyse HIV prevalence trends among young women attending antenatal clinics in recent years.
Results: Patterns of HIV infection among young people are similar across the countries included in this analysis. The prevalence of HIV increases after the age of 15 years, more rapidly among women than among men, reaching a peak among women in their twenties and men in their thirties. Between 2000 and 2007 the prevalence of HIV among antenatal clinic attendees was constant in Mozambique and South Africa and declining in Lesotho, Namibia, Swaziland, Zambia, Botswana, Malawi and Zimbabwe, but only reached statistical significance (P < 0.05) in the last three. Changes towards safer sexual behaviour were observed over time among young men and women in the general population in this region.
Conclusion: Sexual behaviour changes among young people are encouraging and are associated with declines in HIV prevalence among young antenatal clinic attendees over time. More research is needed to understand the recent changes and the very high prevalence among young women in this region. Interventions aimed at reducing risky behaviour need to be supported and expanded while incorporating new approaches to prevention.
At the end of 2007, The Joint United Nations Programme on HIV/AIDS (UNAIDS) estimated that southern Africa accounted for 35% of all people infected with HIV globally, as well as for approximately one third of all new infections and AIDS deaths . In 2007, the estimated national adult HIV prevalence was more than 10% in nine countries: Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia and Zimbabwe, all in southern Africa. It is further estimated that more than 40% of all HIV-infected children under the age of 15 years and more than 50% of all HIV-infected women (15 years and older) globally live in southern Africa . In this region, as in sub-Saharan Africa as a whole, women account for more than 60% of all HIV infections. Young people are at especially high risk of HIV infection in southern Africa, and survey data have shown that HIV prevalence increases rapidly after the age of 15 years to a peak among women in their twenties and men in their thirties [2–10].
In this paper we review the epidemiological data of HIV infection among young people in the nine most affected countries in the world in order to assess current patterns and recent trends in HIV infection at a national level, and to make comparisons with recent changes in sexual behaviour among young people.
Epidemiological data for the nine countries listed above were reviewed and secondary analyses were done to assess patterns and trends in the HIV epidemic. Seven countries had conducted national population-based surveys between 2001 and 2007 in which HIV testing had been included. Demographic and Health surveys (DHS) were performed in Lesotho in 2004 , Malawi in 2004 , Swaziland in 2006/2007 , Zambia in 2001/2002  and 2007  and Zimbabwe in 2005/2006 , an AIDS Impact Survey was performed in Botswana in 2004 , and two large national household surveys were carried out by the Human Sciences Research Council (HSRC) in South Africa in 2002  and 2005 . National surveys on HIV and sexual health among young adults were conducted in Zimbabwe in 2001/2002  and in South Africa in 2003 . HIV testing has not been done nationally in Mozambique and Namibia.
HIV prevalence was compared between men and women in different age groups using data from the national population-based surveys, focusing on young people aged 15–24 years. Female to male prevalence ratios were calculated for young people. For three countries with repeat national surveys in recent years (South Africa, Zambia and Zimbabwe), a chi-squared test was used to test for trends over time in the HIV prevalence among young men and women.
HIV prevalence data collected by Ministries of Health or National AIDS Councils from young pregnant women (aged 15–24 years) attending antenatal clinics in all nine countries [13–22] were used to assess changes in prevalence over time. The analysis of time trends used only those sites that were consistently included in surveillance between 1998–2000 and 2006–2007. Site-specific data were not available for South Africa, and national estimates from antenatal clinic surveillance reports were used in the analysis. Linear or exponential regression analysis (depending on the time trends) was performed to assess changes in prevalence over time.
Behavioural data collected in repeat national population-based surveys between 1994 and 2007 were analysed to assess changes in behaviour over time. Only data reported in DHS (available at http://www.measuredhs.com/), multiple indicator cluster surveys (MICS; available at http://www.unicef.org) or the two national surveys conducted by the HRSC in South Africa [9,10] were used in this analysis to ensure consistency in the methodology. Repeat surveys including relevant behavioural indicators have been conducted in Malawi, Mozambique, Namibia, South Africa, Zimbabwe and Zambia.
Three indicators, as recommended for monitoring and reporting of the Declaration of Commitment made at the 2001 General Assembly Special Session on HIV/AIDS , were considered in the analysis: the proportion of young people aged 15–19 years who have had sexual intercourse by the age of 15 years; the percentage of young men and women (aged 15–24 years) who have had sexual intercourse with more than one partner in the past 12 months; the percentage of those young men and women (aged 15–24 years) who had more than one partner in the past 12 months and reported using a condom during the last sex act.
For countries with more than one survey, time trends in the indicators were assessed, the percentage change per year was calculated and statistical tests were used to assess the significance of the change over time. When two surveys had been conducted, a chi-square test of association was used, and when more than two surveys had been conducted in the past 10–12 years, a chi-square test for trend was used.
HIV prevalence among young people in the most affected countries in southern Africa
Recent national population-based surveys in which HIV testing was included show rapid increases in HIV prevalence reaching very high levels among women between the ages of 15 and 24 years (Table 1). Among 20–24-year-old women HIV prevalence was greater than 20% in Botswana, Lesotho and South Africa between 2004 and 2005, and 38% in Swaziland in 2006.
The prevalence of HIV among women was generally higher than among men of the same age, with a median female: male prevalence ratio of 3.3 [interquartile range (IQR) 2.2–4.7] among 15–19 year olds, and 2.9 (IQR 2.4–3.3) among 20–24 year olds (Table 1); among all young people aged 15–24 years it was 3.3 (IQR 2.6–3.8). Comparison of the age-specific prevalence among women and men (Fig. 1) shows that the patterns of infection are similar in all countries in southern Africa, with female prevalence rising rapidly from close to zero at the age of 15 years to a peak in their late-twenties, whereas prevalence among men rises more slowly, reaching a peak in their mid–late-thirties. The prevalence of HIV in most countries in the region reaches very high levels. In Swaziland in 2006, for example, the peak prevalence was 49% among women aged 25–29 years and 45% among men aged 35–39 years. In most countries, prevalence peaks at a younger age and at a higher level among women than men, except in Malawi, where prevalence in 2004 peaked at 20.4% among 30–34-year-old men, whereas it peaked at 18.1% among women in the same age group.
HIV prevalence was generally higher among young people (aged 15–24 years) living in urban areas than in rural areas, as shown in Lesotho in 2004  (prevalence in urban areas 15.2% and in rural areas 10.5%), Malawi in 2004  (urban 7.2%, rural 5.8%), Swaziland in 2006/2007  (urban 17.9%, rural 13.3%), Zambia in 2001/2002  (urban 10.6%, rural 5.8%), and Zimbabwe in 2005/2006  (urban 8.0%, rural 7.6%). In South Africa in 2005, HIV prevalence among all young people aged 15–24 years was 6.9% in urban formal areas, 17.8% in urban informal areas, 11.1% in rural formal, and 16.7% in rural informal areas . The median urban: rural ratio for HIV prevalence among young people was 1.35.
Comparing the prevalence in Zambia in 2001/2002 with that in 2007 (Fig. 1) shows how the HIV epidemic has matured over time: the peak prevalence has shifted to older ages, and infection levels among young women have declined. The peak prevalence among adult women was slightly lower in 2007 than in 2001/2002, and peaked at a slightly higher level and at an older age among men in 2007. The female-to-male prevalence ratio for young people aged 15–24 years in Zambia fell from 3.7 in 2001/2002 to 1.58 in 2007 (Table 1). The decline in prevalence among young women in Zambia corresponds to significant behaviour change and Table 2 shows a significant decline in the percentage of young men and women who started having sex before age 15 years, a reduction in the number of sexual partners, and an increase in condom use.
Prevalence trends from repeat cross sectional studies
More than one national population-based survey has been conducted in recent years in three countries in the region: South Africa in 2002  and 2005 , Zambia in 2001/2002  and 2007 , and Zimbabwe in 2001/2002 (youth survey)  and 2005/2006 (DHS) . The same methods were used in the repeat surveys in each of the three countries allowing a comparison of prevalence estimates at different time points. The surveys in South Africa were conducted by the HSRC, whereas the surveys in Zambia were conducted by Macro DHS. The national youth survey in Zimbabwe in 2001/2002 employed methods that were similar to those used in the 1999 and 2005/2006 DHS surveys, with similar age distributions for both male and female respondents . The prevalence estimates for young men and women in each of the three countries are shown in Fig. 2. In Zambia, the prevalence fell between 2002 and 2007 among women aged 15–24 years (although not statistically significantly) but not among men. In South Africa the prevalence fell among men between 2003 and 2005, but increased significantly among young women aged 15–24 years (P < 0.01). In Zimbabwe the prevalence fell between 2002 and 2006 and was statistically significant among women aged 15–24 years (P < 0.001), but not among men aged 15–24 years.
Time trends in HIV prevalence among young women attending antenatal clinics
In order to assess recent time trends in HIV prevalence, we analysed data collected and published in national surveillance reports, between 2000 and 2007 on HIV prevalence among women (aged 15–24 years) attending antenatal clinics in the nine countries. Sites that were consistently included in national surveillance over time were included in the analysis. In Zambia, national trend data were available for 15–19 and 15–39-year-old women, but not for 15–24-year-old women. Only the trends among 15–19-year-old women were included in this analysis.
Very high prevalence levels have been reported for young pregnant women in all nine countries (Fig. 3). In all countries, except Mozambique and South Africa, regression analysis of recent HIV prevalence data among young women between 1998/2000 and 2005/2007 show declining trends, although these declines were statistically significant (P < 0.05) only in Botswana, Zimbabwe and Malawi. HIV prevalence in Mozambique showed an increase over time between 2000 and 2004, although data for 2004 and 2007 indicate that this trend might be changing.
The prevalence of HIV among young women aged 15–24 years in South Africa appears to have been stable since approximately 2000. To investigate this further, we analysed prevalence trends separately for women aged 15–19 years and 20–24 years between 1995 and 2007 (Fig. 4). Fitted logistic curves show that HIV prevalence has stabilized in both age groups, although at a much higher level among 20–24-year-old women. Only since 2005 have data shown a slight decline in prevalence among young women, although this is not statistically significant.
Behavioural data among young people aged 15–24 years were collected from repeat population-based surveys conducted between 1994 and 2007. Repeat survey data for the three indicators of interest were not available in Botswana, Lesotho and Swaziland. For all countries, except South Africa, data were obtained from DHS (available at http://www.measuredhs.com/). Although data in South Africa were available from the two HSRC surveys conducted in 2002  and 2005  as well as from the sexual behaviour survey conducted among young people by the Reproductive Health and HIV Research Unit in 2003 , only data from the two HSRC surveys were included in the statistical analysis to ensure that the data collection methods were consistent. MICS surveys (available at www.unicef.org) provided additional information on the age of sexual debut. The results are summarized in Table 2 and Fig. 5 and show encouraging changes towards safer sexual behaviour among young people in this region. Significantly fewer men reported having had sex by the age of 15 years in all countries except in Mozambique, whereas significant changes in this indicator for women were found in Malawi and Zambia (Table 2a). Significantly smaller percentages of men and women indicated having had sex with more than one partner over time in most countries with relevant data, except in Malawi and Namibia where the change among women was not statistically significant, and in South Africa where more men reported having had multiple sex partners in the second survey in 2005 compared with the first survey in 2002. Generally in this region, the percentage of young women included in national surveys who indicated having had multiple sex partners in the past 12 months was below 5% in all countries except in South Africa, where 8.8% of women in 2002 and 6% of women in 2005 reported multiple partners (Table 2b). Although condom use increased over time among young men and women in most countries, it was statistically significant only among young women in Namibia and Zambia (Table 2c). Denominators for this latter indicator were generally small, especially for women, because of the small percentage of women who had multiple partners. Of those young people who had more than one partner in the past 12 months, condom use during the last sexual encounter was reported to be higher than 50% among young men in Lesotho, Namibia, Swaziland, Zimbabwe, and among young women in Namibia and Swaziland. Overall in this region, behaviour among young people has become safer over time.
Data collected over time from routine surveillance systems at a national level as well as from recent national population-based surveys in the nine countries in southern Africa show very high HIV prevalence among young women between the ages of 15 and 24 years. The prevalence increases rapidly with age in young women: whereas prevalence is low among 10–14-year-old girls [4,8,10], it rises dramatically from the age of 15 years, reaching 38% among women aged 20–24 years and 49% among women aged 25–29 years in the general population in Swaziland in 2006. HIV prevalence among young women in the general population in southern Africa (as observed in national population-based surveys) ranged from 3.7% among 15–19 year olds and 13.2% among 20–24 year olds in Malawi in 2004 to 10.2% and 38.2%, respectively, in Swaziland in 2006/2007.
Although patterns of HIV infection are similar in all nine countries included in this analysis, it shows that infection rates among young women increase much faster than among men, and the peak prevalence occurs at younger ages among women than men (Fig. 1). For all nine countries, the age-specific prevalence curves are shifted to older age groups in men compared with women, by approximately 5 years. The ratio of the prevalence of HIV infection among women relative to men shows that young women (aged 15–24 years) are approximately 3.3 times (IQR 2.6–3.8) more likely to be infected with HIV than young men in this region. Data collected from national population-based surveys on sexual behaviour, however, indicate that the percentage of young women reported to have had multiple sex partners in the past 12 months is generally low (Table 2). The higher prevalences among young women compared with young men are likely to be related to young women having older male sexual partners, and to young women being biologically more susceptible to HIV infection . Recent studies from South Africa suggest that the rapid increase and high prevalence levels among young women in this region could be associated with per partnership probabilities of HIV transmission from men to women that are higher than those reported elsewhere [26,27].
Prevalence data collected over time among young women attending antenatal clinics show declining trends in most of the countries in this region, although it was statistically significant only in Botswana (between 2001 and 2006), Malawi (between 1999 and 2007) and Zimbabwe (between 2000 and 2006). South Africa and Mozambique were the only two countries in this region in which the fitted trend line between 2000 and 2007 did not show a decline, although data from the last two antenatal clinic surveys in both countries suggest that the prevalence might be starting to fall. Repeat national population-based surveys in Zimbabwe (in 2001/2002 and 2006) and Zambia (in 2001/2002 and 2007) show trends among young women that are consistent with those observed among antenatal clinic attendees: in Zimbabwe prevalence among young women (aged 15–24 years) in the general population fell from17.4% in 2001/2002 to 10.9% in 2007 (P < 0.001), whereas in Zambia it fell from 11.2% in 2001/2002 to 9.5% in 2007 (P = 0.118). In contrast to the stable prevalence trend observed among antenatal clinic attendees in South Africa, however, repeat population-based surveys showed an increase in prevalence among 15–24-year-old women from 12% in 2002 to 16.7% in 2005 (P < 0.01). The difference in trends between antenatal clinic attendees and household survey participants could be ascribed to the different time periods of data collection; the antenatal clinic data were from 2000 to 2007, whereas the household surveys were from 2002 and 2005. In addition, there has been some concern over the high levels of non-response in the household surveys in South Africa and the HIV testing methodologies that differed between the two surveys: saliva tests were used in the first survey , whereas venous blood was used in the second survey .
National population-based surveys and antenatal clinic surveillance both have strengths and weaknesses [28–30]. Although population-based surveys provide better coverage of the general population, sentinel surveillance provides important information on prevalence trends over time . A major limitation of antenatal clinic surveillance is that young pregnant women in the age group 15–24 years only represent those who are sexually active and who receive antenatal care in public health facilities. Further biases could be associated with limited geographical coverage of antenatal clinic surveillance. Biases in national population-based surveys, on the other hand, are mainly associated with the level of non-response in the survey (absence from the household or refusal to participate) and the exclusion of populations not living in households such as young people living in hostels or in military camps. The two data sources provide important and complementary information on patterns and trends in the HIV epidemic at a national level.
Comparing adult HIV prevalence from national surveys and antenatal clinic surveillance in all countries in sub-Saharan Africa that have conducted national surveys shows that antenatal clinics generally overestimate prevalence in the national population . In five countries in southern and east Africa antenatal clinic-based estimates among young women (aged 15–24 years) were higher than survey estimates for younger women in the antenatal clinic catchment areas, but lower than the estimates for older women, suggesting that women covered by antenatal clinic surveillance are not representative of all women . Data for the nine countries included in this paper also show that prevalence is generally higher among young pregnant women than among young women in the general population. For example, the prevalence among young women aged 15–24 years in the general population in Botswana in 2004 was 18.2%, whereas it was approximately 30% among pregnant women of the same age. In South Africa in 2005 the corresponding figures were 16.7% and 24.4%, respectively, and in Swaziland in 2006, the corresponding figures for women aged 15–24 years were 22.6% and 35%, respectively.
Although sentinel surveillance provides the best source of data on prevalence trends in countries, knowledge of the extent to which prevalence trends among national antenatal clinic attendees represent trends in the general population is limited. Reports from selected communities in Zambia [31,32] and Zimbabwe  suggest that trends among young women attending antenatal clinics underestimate declines in HIV in the general population. In Zambia, this difference is partly explained by educational attainment and delays in the age of first pregnancy among young women over time . Furthermore, as quality of surveillance can also change over time, analysis and interpretation of changes in antenatal clinic-based prevalence trends need to be done carefully.
Data on changes in sexual behaviour over time were available from population-based surveys for six of the nine countries, but not for Botswana, Lesotho and Swaziland. In most of the countries showing declines in HIV prevalence among young women attending antenatal clinics, changes towards safer sexual behaviour over time were also observed among men and women participating in national household surveys. In Malawi between 1999 and 2007, the prevalence of HIV among women attending antenatal clinics declined, whereas the proportion of young women and men who reported having had sex by the age of 15 years declined significantly, the proportion of men who reported having had multiple partners declined, and the number who reported using condoms increased, although the change in the latter indicator was not statistically significant. In Zambia between 2001 and 2007, the prevalence of HIV among young women fell, but not significantly, in antenatal clinic data and repeat population-based surveys conducted in 2001 and 2007. Over the period 1996 to 2007, significant changes were observed in all three behavioural indicators for young men as well as young women in Zambia. The declines in HIV prevalence and associated changes in sexual behaviour are consistent with changes found in selected Zambian communities [32,34,35]. In Zimbabwe, the decline in prevalence among young women over time, observed in both antenatal clinic surveys (2000–2006) as well as from the two population-based surveys (2001/2002 to 2006), is associated with a reduction in sexual experience before the age of 15 years and a significant reduction in the percentage of young women and men who reported having had multiple sex partners between 1999 and 2005. The association between declining prevalence and behaviour change in Zimbabwe has been studied in detail and is also reported elsewhere [33,36,37]. Although the decline in prevalence between 2002 and 2006 among young antenatal clinic attendees in Namibia was not statistically significant, there were significant changes in some of the behavioural indicators; a significantly smaller percentage of young men between 2000 and 2006 reported having had sex by age 15 years, a significantly smaller percentage of men reported having had multiple sex partners, and there was a significant increase in condom use among young women.
Changes in the prevalence of HIV among young women attending antenatal clinics in South Africa were not statistically significant, despite significant changes in some of the behavioural indicators. Between the 2002 and 2005 household surveys in South Africa, there was a significant reduction in the proportion of young women reported having had multiple partners. The opposite was observed for young men, however, among whom there was an increase in the percentage reported having had multiple partners. In contrast, the two national surveys in South Africa showed an increase in prevalence among young women between 2002 and 2005 and a decline in prevalence among young men. Mozambique is the only other country in which the prevalence trend between 2000 and 2007 did not show a decline, while there was a significant increase over time (1997 to 2003) in the percentage of young men, but not in the percentage of young women, who reported having had sex by the age of 15 years.
Estimating the incidence of HIV infection is essential for understanding the dynamics of HIV transmission as well as for targeting and evaluating the impact of prevention programmes . However, while incidence provides a more immediate indicator of impact than prevalence, it is more difficult to measure than prevalence. Direct measures of HIV incidence can be obtained from following cohorts of people over time. Because of the logistical and ethical difficulties of following people until they seroconvert, however, very few cohort studies have been conducted to determine incidence in this region. Where available, these studies are normally only conducted in small areas or communities (such as the Hlabisa community in South Africa  and Manicaland in Zimbabwe ), and have not been conducted at a national level. There are, however, several other ways of determining incidence. For example, incidence can be determined from laboratory-based techniques that aim to differentiate recent from established HIV infection, using a serological testing algorithm for recent HIV seroconversion (STARHS)  or using the BED capture enzyme immunoassay [42,43]. Although these methods can add important value to prevalence-based surveillance systems, further research is still being carried out to generalize and validate these methods in different populations . Incidence can also be estimated indirectly using mathematical models to analyse age and time trends in prevalence data [45,46] or to compare the prevalence in a population at two times, allowing for changes caused by new infections and mortality . Such models have been used to estimate incidence in Malawi , South Africa  and Zimbabwe .
An alternative approach to estimating trends in incidence over time is to use a surrogate measure, such as the prevalence among young people aged 15–24 years . As the onset of sexual activity in this age group is expected to be recent, the prevalence in this age group should reflect recent infections. Although the method is not ideal it has been shown that HIV prevalence among young pregnant women (aged 15–24 years) attending antenatal clinics can provide a reasonable indication of the incidence in the population under stable conditions, but needs to be interpreted with caution if there are changes in age patterns or sexual debut . Using trends in HIV prevalence among young antenatal clinic attendees (aged 15–24 years) as a proxy measure for trends in incidence, it would seem likely that the incidence of HIV is declining in most countries in this region.
The changes towards safer sexual behaviour among young men and women in this region are encouraging and are associated with declines in HIV prevalence among antenatal clinic attendees over time in the six countries where such data are available. In all countries with declines in prevalence among young women, significant changes in one or more of the behavioural indicators were observed among young men and women. Caution is needed, however, when interpreting trends from the different data sources, and the tendency to underreport high-risk behaviour may increase over time in countries with severe HIV epidemics . Further analysis of both prevalence and behavioural data are therefore required to provide a better understanding of the changing patterns and the reasons for the changes in behaviour. Regular surveys are needed to monitor trends in HIV prevalence and sexual behaviour among young people, while more research is also needed on the validity of behavioural indicators (e.g. investigating social desirability bias), as well as on the impact of sexual networks, including intergenerational sex and concurrent partnerships.
Despite the declines in HIV prevalence among young people in recent years, data from both antenatal clinic surveillance and national population-based surveys still show that the prevalence among young women is unacceptably high. Current programmes aimed at delaying sexual onset, reducing the number of sexual partners and increasing condom use should be supported and expanded, whereas new approaches such as male circumcision, targeting places that act as nodes for sexual networks [51,52] and perhaps using antiretroviral therapy to reduce HIV transmission  should be combined with existing prevention efforts. Further studies are needed to obtain a better understanding of the reasons for the high prevalence among young women as a matter of urgency, and we need to find ways to finally protect young women from becoming infected with HIV.
The authors thank Macro International and UNICEF for providing the behavioural data from DHS and MICS surveys that were used in this analysis, and Dr Brian Williams for valuable comments on the manuscript. An earlier version of this paper was presented at a technical meeting on young women in HIV hyper-endemic countries of southern Africa, organized by UNAIDS and the RHRU, from 18 to 19 June 2008 in Johannesburg, South Africa. Publication of this article was funded by UNAIDS.
Conflicts of interest: None.
1. UNAIDS. 2008 Report on the global AIDS epidemic
. Geneva: UNAIDS; 2008. Available at: www.unaids.org
. Accessed: October 2008.
2. Ministry of Health and Social Welfare (MOHSW) Lesotho, Bureau of Statistics (BOS) Lesotho, and ORC Macro. Lesotho demographic and health survey 2004
. Calverton, Maryland: MOH, BOS and ORC Macro; 2005.
3. National Statistical Office (NSO) Malawi and ORC Macro. Malawi demographic and health survey 2004
. Calverton, Maryland: NSO and ORC Macro; 2005.
4. Central Statistical Office Swaziland and Macro International Inc. Swaziland demographic health survey 2006–07
. Mbabane, Swaziland: Central Statistical Office and Macro International Inc.; 2008.
5. Central Statistical Office Zambia, Central Board of Health Zambia, and ORC Macro. Zambia demographic and health survey 2001–2002.
Calverton, Maryland, USA: Central Statistical Office, Central Board of Health and ORC Macro; 2003.
6. Central Statistical Office Zambia, Ministry of Health Zambia, and Measure DHS. Zambia demographic and health survey 2007
. Preliminary report. Lusaka, Zambia: Central Statistical Office Zambia, Ministry of Health Zambia, and Macro International Inc., 2008.
7. Central Statistical Office (CSO) Zimbabwe and Macro International Inc. Zimbabwe demographic and health survey 2005–06
. Calverton, Maryland: CSO and Macro International Inc.; 2007.
8. NACA. Botswana AIDS impact survey II
. Botswana: NACA, CSO, UNDP, ACHAP, UNICEF; 2004.
9. Shisana O, Simbayi L. Nelson Mandela/HSRC study of HIV/AIDS: South African national HIV prevalence, behavioural risks and mass media
. Household survey 2002. Executive Summary. Pretoria: HSRC; 2003.
10. Shisana O, Rehle T, Simbayi LC, Parker W, Zuma K, Bhana A, et al
. South African national HIV prevalence, HIV incidence, behaviour and communication survey, 2005. Cape Town: HSRC Press; 2005.
11. Ministry of Health and Child Welfare Zimbabwe, Zimbabwe National Family Planning Council, National AIDS Council Zimbabwe, and US Centers for Disease Control and Prevention. The Zimbabwe young adult survey 2001–2002
. Harare, Zimbabwe: Ministry of Health and Child Welfare and US Centers for Disease Control and Prevention; 2004.
12. Pettifor AE, Rees HV, Steffenson A, Hlongwa-Madikizela L, MacPhail C, Vermaak K, et al
. HIV and sexual behaviour among young South Africans: a national survey of 15–24 year olds. Johannesburg: Reproductive Health Research Unit; 2004.
13. Botswana Department of HIV/AIDS Prevention and Care. 2006 Botswana second generation HIV/AIDS surveillance
. Technical report. Botswana: Ministry of Health; 2006.
14. Ministry of Health and Social Welfare. Sentinel HIV/syphilis survey 2007.
Maseru, Lesotho: Ministry of Health and Social Welfare; 2008.
15. National AIDS Commission. HIV and syphilis sero-survey and national HIV prevalence and AIDS estimates
. Report for 2007. Lilongwe, Malawi: Ministry of Health; 2008.
16. National AIDS Council. Universal declaration of commitment on HIV/AIDS: progress report for United Nations General Assembly special session on HIV/AIDS, 2003–2005
. Mozambique: National AIDS Council, Mozambique; 2006.
17. Ministry of Health. Update of the HIV Epidemiological Surveillance Data - 2007 Round
. Maputo, Mozambique: National Directorate of Health, National STD/HIV-AIDS Control Programme, Ministry of Health; 2008.
18. Ministry of Health and Social Services. Report of the 2006 national HIV sentinel survey.
Windhoek, Republic of Namibia: Ministry of Health and Social Services; 2007.
19. Odido H, Tsela S. HIV estimations and projections for Swaziland. Mbabane, Swaziland: National Emergency Response Council on HIV and AIDS; 2007.
20. Department of Health. The national HIV and syphilis prevalence survey, South Africa, 2007
. Pretoria, South Africa: Department of Health; 2008.
21. Ministry of Health. Zambia antenatal clinic sentinel surveillance report 1994–2006
. Lusaka, Zambia: Ministry of Health, Zambia; 2008.
22. Ministry of Health and Child Welfare. 2006 ANC report.
Harare, Zimbabwe: AIDS and TB Unit, Ministry of Health and Child Welfare; 2007.
23. UNAIDS. 2007 United Nations General Assembly special session on HIV/AIDS. Monitoring the declaration of commitment on HIV/AIDS: guidelines on construction of core indicators
. Geneva: UNAIDS; 2007.
24. Shisana O, Rehle T, Simbayi CC, Parker W, Zuma K, Bhana A, et al
. South African national HIV prevalence, HIV incidence, behavioural and communication survey, 2005. Cape Town: HSRC Press; 2005.
25. Williams BG, Gouws E, Colvin M, Sitas F, Ramjee G, Karim SSA. Patterns of infection: using age prevalence data to understand the epidemic of HIV in South Africa. South Afr J Sci 2000; 96:305–312.
26. Pettifor AE, Hudgens MG, Levandowski BA, Rees HV, Cohen MS. Highly efficient HIV transmission to young women in South Africa. AIDS 2007; 21:861–865.
27. Pettifor A, Macphail C, Rees H, Cohen M. HIV and sexual behavior among young people: the South African paradox. Sex Transm Dis 2008; 35:843–844.
28. Gouws E, Mishra V, Fowler TB. Comparison of adult HIV prevalence from national population-based surveys and antenatal clinic surveillance in countries with generalised epidemics: implications for calibrating surveillance data. Sex Transm Infect 2008; 84(Suppl. 1):i17–i23.
29. Montana LS, Mishra V, Hong R. Comparison of HIV prevalence estimates from antenatal care surveillance and population-based surveys in sub-Saharan Africa. Sex Transm Infect 2008; 84(Suppl. 1):i78–i84.
30. Mishra V, Barrere B, Hong R, Khan S. Evaluation of bias in HIV seroprevalence estimates from national household surveys. Sex Transm Infect 2008; 84(Suppl. 1):i63–i70.
31. Michelo C, Sandoy I, Fylkesnes K. Antenatal clinic HIV data found to underestimate actual prevalence declines: evidence from Zambia. Trop Med Int Health 2008; 13:171–179.
32. Michelo C, Sandoy IF, Dzekedzeke K, Siziya S, Fylkesnes K. Steep HIV prevalence declines among young people in selected Zambian communities: population-based observations (1995–2003). BMC Public Health 2006; 6:279, doi:10.1186/1471-2458-6-279.
33. Gregson S, Garnett GP, Nyamukapa CA, Hallett TB, Lewis JJ, Mason PR, et al
. HIV decline associated with behavior change in eastern Zimbabwe. Science 2006; 311:664–666.
34. Sandoy IF, Michelo C, Siziya S, Fylkesnes K. Associations between sexual behaviour change in young people and decline in HIV prevalence in Zambia. BMC Public Health 2007; 7:60, doi:10.1186/1471-2458-7-60.
35. Michelo C, Sandoy IF, Fylkesnes K. Marked HIV prevalence declines in higher educated young people: evidence from population-based surveys (1995–2003) in Zambia. AIDS 2006; 20:1031–1038.
36. Mahomva A, Greby S, Dube S, Mugurungi O, Hargrove J, Rosen D, et al
. HIV prevalence and trends from data in Zimbabwe, 1997–2004. Sex Transm Infect 2006; 82(Suppl. 1):i42–i47.
37. UNAIDS. Evidence for HIV decline in Zimbabwe: a comprehensive review of the epidemiological data
. Geneva: Joint United Nations Programme on HIV/AIDS; 2005.
38. Gouws E. HIV incidence rates in South Africa. In: Abdool Karim SS, Abdool Karim Q, editors. HIV/AIDS in South Africa. New York: Cambridge University Press; 2005.
39. Barnighausen T, Tanser F, Gqwede Z, Mbizana C, Herbst K, Newell ML. High HIV incidence in a community with high HIV prevalence in rural South Africa: findings from a prospective population-based study. AIDS 2008; 22:139–144.
40. Lopman B, Nyamukapa C, Mushati P, Mupambireyi Z, Mason P, Garnett GP, et al
. HIV incidence in 3 years of follow-up of a Zimbabwe cohort – 1998–2000 to 2001-03: contributions of proximate and underlying determinants to transmission. Int J Epidemiol 2008; 37:88–105.
41. Janssens RS, Satten GA, Stramer SL, Rawal BD, O'Brien TR, Weiblen BJ, et al
. New testing strategy to detect early HIV-1 infection for use in incidence estimates and for clinical and prevention purposes. JAMA 1998; 280:42–48.
42. McDougal JS, Pilcher CD, Parekh BS, Gershy-Damet G, Branson BM, Marsh K, et al
. Surveillance for HIV-1 incidence using tests for recent infection in resource-constrained countries. AIDS 2005; 19(Suppl. 2):S25–S30.
43. Hargrove JW, Humphrey JH, Mutasa K, Parekh BS, McDougal JS, Ntozini R, et al
. Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay. AIDS 2008; 22:511–518.
45. Gregson S, Machekano R, Donnelly CA, Mbizvo MT, Anderson RM, Katzenstein DA. Estimating HIV incidence from age-specific prevalence data: comparison with concurrent cohort estimates in a study of male factory workers, Harare, Zimbabwe. AIDS 1998; 12:2049–2058.
46. Williams B, Gouws E, Wilkinson D, Karim SA. Estimating HIV incidence rates from age prevalence data in epidemic situations. Stat Med 2001; 20:2003–2016.
47. Hallett T, Zaba B, Todd J, Lopman B, Mwita W, Biraro S, et al
. Estimating incidence from prevalence in generalised HIV epidemics: methods and validation. PLoS Med 2008; 5:e80.
48. White RG, Vynnycky E, Glynn JR, Crampin AC, Jahn A, Mwaungulu F, et al
. HIV epidemic trend and antiretroviral treatment need in Karonga District, Malawi. Epidemiol Infect 2007; 135:922–932.
49. Ghys PD, Kufa E, George MV. Measuring trends in prevalence and incidence of HIV infection in countries with generalised epidemics. Sex Transm Infect 2006; 82(Suppl. 1):i52–i56.
50. Zaba B, Boerma T, White R. Monitoring the AIDS epidemic using HIV prevalence data among young women attending antenatal clinics: prospects and problems. AIDS 2000; 14:1633–1645.
51. Weir SS, Pailman C, Mahlalela X, Coetzee N, Meidany F, Boerma JT. From people to places: focusing AIDS prevention efforts where it matters most. AIDS 2003; 17:895–903.
52. Sandoy IF, Siziya S, Fylkesnes K. Lost opportunities in HIV prevention: programmes miss places where exposures are highest. BMC Public Health 2008; 8:31, doi:10.1186/1471-2458-8-31.
53. Montaner JS, Hogg R, Wood E, Kerr T, Tyndall M, Levy AR, et al
. The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic. Lancet 2006; 368:531–536.
epidemiology; HIV; southern Africa; young people
© 2008 Lippincott Williams & Wilkins, Inc.
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Highlight selected keywords in the article text.
Data is temporarily unavailable. Please try again soon.
Readers Of this Article Also Read