HIV This Week

Bärnighausen T, Tanser F, Newell ML. Lack of a Decline in HIV Incidence in a Rural Community with High HIV Prevalence in South Africa, 2003-2007. AIDS Res Hum Retroviruses. 2009 Apr;25(4):405-9.

To understand the dynamics of the HIV epidemic and to plan HIV treatment and prevention programs, it is critical to know how HIV incidence in a population evolves over time. Bärnighausen and colleagues used data from a large population-based longitudinal HIV surveillance in a rural community in South Africa to test whether HIV incidence in this population has changed in the period from 2003 through 2007. They observed 563 seroconversions in 8095 individuals over 16,256 person-years at risk, yielding an overall HIV incidence of 3.4 per 100 person-years (95% confidence interval 3.1-3.7). The authors included time-dependent period dummy variables (in half-yearly increments) in age-stratified Cox regressions in order to test for trends in HIV incidence. They first did regression analyses separately for women and men. In both regressions, the coefficients of all period dummy variables were individually insignificant (all p >/= 0.338) and jointly insignificant (p = 0.764 and p = 0.111, respectively). They then did regression analysis using the pooled data on women and men, controlling for sex and interactions between sex and age. Again, the coefficients of the eight period dummy variables were individually insignificant (all p >/= 0.387) and jointly insignificant (p = 0.701). They show for the first time that high levels of HIV incidence have been maintained without any sign of decline over the past 5 years in both women and men in a rural South African community with high HIV prevalence. It is unlikely that the HIV epidemic in rural South Africa can be reversed without new or intensified efforts to prevent HIV infection.

Editors’ note: Changes in HIV prevalence figures are difficult to interpret as they reflect both the incidence of new infections and mortality in people living with HIV. What we really need to know is the trend in HIV incidence as this reflects the effectiveness of prevention programming and predicts eventual treatment demand. The findings from this prospective, longitudinal study are highly disturbing: with a constant, unrelenting incidence of 3.4 per 100 person-years, 15 out of every 100 people who were HIV-negative at the start of the study in 2003 had seroconverted by its end 5 years later. The prevention programmes that have been operating clearly do not reach enough people with effective prevention messages, skills building, and support for changed sexual behaviour norms. Safe male circumcision services, positive prevention programmes, and community mobilisation to address the structural factors underlying risk in this rural KwaZulu-Natal community are additional approaches that deserve immediate attention.

HIV programs in generalized epidemics have traditionally relied on antenatal clinic sentinel surveillance data to guide prevention and to model epidemic trends. Antenatal clinic data, however, come from a subset of the population, and their representativeness of the population has been debated. Musinguzi and colleagues compared data from a national population-based Uganda HIV Sero-Behavioral Survey with those from antenatal clinic sentinel surveillance. Using geographic information system, Uganda HIV Sero-Behavioral Survey clusters within a 30 km radius of the antenatal clinic sites were mapped. Estimates of HIV prevalence from antenatal clinic surveillance were compared with those from Uganda HIV Sero-Behavioral Survey. They found that the antenatal clinic-based HIV prevalence, 6.0% [confidence interval (CI) 5.5% to 6.5%], was similar to that from Uganda HIV Sero-Behavioral Survey, 5.9% (CI 5.4% to 6.4%). The antenatal clinic-based estimate correlated with that of Uganda HIV Sero-Behavioral Survey catchment area women who were pregnant and those who had given birth in the 2 years preceding the survey. Antenatal clinic data overestimated prevalence in the 15-year to 19-year age group, were similar to Uganda HIV Sero-Behavioral Survey for ages 20-29 years, and underestimated prevalence in older respondents. Antenatal clinic data underestimated HIV prevalence among women (6.0% vs. 7.4%; CI 6.6% to 8.2%) and urban women (7.6% vs. 12.7%) but was similar for rural women (5.3% vs. 4.9%). Antenatal clinic -based surveillance remains an important tool for monitoring HIV programs. Antenatal clinic and Uganda HIV Sero-Behavioral Survey data were similar overall and for 15-year to 29-year olds, women who were pregnant, and women who had a birth in the 2 years before the survey. Antenatal clinic estimates were lower in those >/=30 years and in urban areas. Periodic serosurveys to adjust antenatal clinic -based estimates are needed.

Editors’ note: In a mature epidemic such as Uganda’s, antenatal surveillance is likely to underestimate HIV prevalence in older women because older women can be at significant risk of acquiring HIV after the reproductive age and women with HIV who are of reproductive age tend to have lower fertility. Antenatal surveillance does generally reflect the general population prevalence among 15 to 29 year olds and in the age group 15 to 19 years it can be used as a general proxy measure of HIV incidence. Thus, antenatal clinic surveillance, supplemented by periodic population-based sero-behavioural surveys to provide an adjusted picture of national HIV epidemics, remains a valid surveillance tool.

To reconstruct the past HIV incidence and prevalence in Thailand from 1980 to 2008 and predict the country’s AIDS incidence from 2009 to 2011, nonparametric backcalculation was adopted utilizing 100 quarterly observed new AIDS counts excluding paediatric cases. The accuracy of data was enhanced through a series of data adjustments using the weight method to account for several surveillance reporting issues. The mixture of time-dependent distributions allowed the effects of age at seroconversion and antiretroviral therapy to be incorporated simultaneously. Sensitivity analyses were conducted to assess model variations that were subject to major uncertainties. Future AIDS incidence was projected for various predetermined HIV incidence patterns. HIV incidence in Thailand reached its peak in 1992 with approximately 115 000 cases. A steep decline thereafter discontinued in 1997 and was followed by another strike of 42 000 cases in 1999. The second surge, which happened concurrently with the major economic crisis, brought on 60 000 new infections. As of December 2008, more than 1 million individuals had been infected and around 430 000 adults were living with HIV corresponding to a prevalence rate of 1.2%. The incidence rate had become less than 0.1% since 2002. The backcalculated estimates were dominated by postulated median AIDS progression time and adjustments to surveillance data. The authors’ analysis indicated that, thus far, the 1990s was the most severe era of HIV epidemic in Thailand with two HIV incidence peaks. A drop in new infections led to a decrease in recent AIDS incidence, and this tendency is likely to remain unchanged until 2011, if not further.

Editors’ note: Backcalculation reconstructs a past pattern of HIV incidence based on AIDS surveillance data and a plausible incubation period from HIV infection to AIDS diagnosis. The relatively short incubation period of 7 years used in this work may have lowered the estimates of backcalculated total infections. Although it makes logical sense that the large cuts of one-third to one-half in government HIV prevention budgets during the financial crisis of 1998 to 2000 could have led to an intriguing second peak in HIV incidence in Thailand, further study is needed to confirm this.

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