Does nonlocal women's attendance at antenatal clinics distort HIV prevalence surveillance estimates in pregnant women in Zimbabwe?

Staying, leaving and returning: Trends of prevention of mother-to-child transmission retention among newly diagnosed HIV-positive pregnant and postpartum women

Uptake of services and retention throughout the Prevention of Mother-to-Child Transmission continuum are necessary to achieve the goal of reducing Mother-to-Child Transmission of Human Immunodeficiency Virus (HIV). Adopting a retrospective cohort design, we tracked the uptake of services in a district hospital in Ghana from antenatal booking through to six weeks postnatal when early infant diagnosis was conducted. Of the 1252 pregnant women booked antenatally, 94.1% (n = 1178) received pre-test counselling, 96.3% (1134) opted for HIV testing and 3.8% (n = 43) women tested positive for HIV throughout the continuum. The retention rate at six weeks postpartum was 67.4%. Missed opportunities occurred throughout the programme and the highest disengagement, 58.9% (23/39) occurred antenatally. Instances of re-engagement were also recorded. Establishing measures to promote retention throughout the programme is critical to ensuring HIV-infected mothers maintain their health and their exposed newborns are HIV-free. This phase of the study provided a comprehensive view of retention in the absence of any baseline.

Combining national survey with facility-based HIV testing data to obtain more accurate estimate of HIV prevalence in districts in Uganda

Background

National or regional population-based HIV prevalence surveys have small sample sizes at district or sub-district levels; this leads to wide confidence intervals when estimating HIV prevalence at district level for programme monitoring and decision making. Health facility programme data, collected during service delivery is widely available, but since people self-select for HIV testing, HIV prevalence estimates based on it, is subject to selection bias. We present a statistical annealing technique, Hybrid Prevalence Estimation (HPE), that combines a small population-based survey sample with a facility-based sample to generate district level HIV prevalence estimates with associated confidence intervals.

Methods

We apply the HPE methodology to combine the 2011 Uganda AIDS indicator survey with the 2011 health facility HIV testing data to obtain HIV prevalence estimates for districts in Uganda. Multilevel logistic regression was used to obtain the propensity of testing for HIV in a health facility, and the propensity to test was used to combine the population survey and health facility HIV testing data to obtain the HPEs. We assessed comparability of the HPEs and survey-based estimates using Bland Altman analysis.

Results

The estimates ranged from 0.012 to 0.178 and had narrower confidence intervals compared to survey-based estimates. The average difference between HPEs and population survey estimates was 0.00 (95% CI: − 0.04, 0.04). The HPE standard errors were 28.9% (95% CI: 23.4–34.4) reduced, compared to survey-based standard errors. Overall reduction in HPE standard errors compared survey-based standard errors ranged from 5.4 to 95%.

Conclusions

Facility data can be combined with population survey data to obtain more accurate HIV prevalence estimates for geographical areas with small population survey sample sizes. We recommend use of the methodology by district level managers to obtain more accurate HIV prevalence estimates to guide decision making without incurring additional data collection costs.

Difference in HIV prevalence by testing venue: results from population level survey in Uganda

While countries now have national and regional measures of HIV prevalence, sub-regional (district) and sub-district level information is sparse. Growing demand to fill this gap with health facility testing data, in addition to other HIV testing data requires understanding the comparability of these various data sources. We analysed the 2011 Uganda AIDS indicator survey (UAIS) data to assess the proportion of people tested for HIV across Uganda and the venue of testing. We compared HIV prevalence between those tested in a health facility and those testing in a community setting and investigated factors associated with HIV positivity in each subgroup.

We computed HIV prevalence among those tested in a health facility and community setting and obtained HIV prevalence ratio and 95% confidence intervals using the Katz et al (1978) methodology. Factors associated with HIV positivity in each subgroup were assessed using multilevel logistic regression.

Of the 11, 685 individuals, 8,978 (77.1%) had ever tested for HIV in a health facility (female: 6,396, 84.0% versus male: 2,582, 64.2%). Fifty nine percent tested in a health facility in the 12 months preceding the survey (female: 5,507, 72.7% versus male: 1,413, 34.9%). HIV prevalence ratio was1.8 times among those tested in a health facility compared to those tested at community setting (10.9% [95% CI: 10.0-11.7] versus 6.2% [95% CI: 5.4-7.0]). Among heath facility testers, older age group, previously married and having no sexual partner was associated with significantly higher HIV prevalence.

Using facility testing data for program planning and implementation should take into consideration the elevated and varying HIV prevalence among individuals accessing HIV testing services at health facilities as well as differences in their social demographic characteristics.

Demographic change and HIV epidemic projections to 2050 for adolescents and young people aged 15-24

Background: Ending AIDS as a public health threat by 2030 is a significant challenge, as new HIV infections among adolescents and young people have not decreased fast enough to curb the epidemic. The combination of slow HIV response and increasing youth populations 15–24 could affect progress towards 2030 goals.

Objective: This analysis aimed to describe global and regional trends from 2010–2050 in the HIV epidemic among adolescents and young people by accounting for demographic projections and recent trends in HIV interventions.

Methods: 148 national HIV estimates files were used to project the HIV epidemic to 2050. Numbers of people living with HIV and new HIV infections were projected by sex and five-year age group. Along with demographic data, projections were based on three key assumptions: future trends in HIV incidence, antiretroviral treatment coverage, and coverage of antiretrovirals for prevention of mother-to-child transmission. Results represent nine geographic regions.

Results: While the number of adolescents and young people is projected to increase by 10% from 2010–2050, those living with HIV is projected to decrease by 61%. In Eastern and Southern Africa, which hosts the largest HIV epidemic, new HIV infections among adolescents and young people are projected to decline by 84% from 2010–2050. In West and Central Africa, which hosts the second-largest HIV epidemic, new infections are projected to decline by 35%.

Conclusions: While adolescents and young people living with HIV are living longer and ageing into adulthood, if current trends continue, the number of new HIV infections is not projected to decline fast enough to end AIDS as a health threat in this age group. Regional variations suggest that while progress in Eastern and Southern Africa could reduce the size of the epidemic by 2050, other regions exhibit slower rates of decline among adolescents and young people.