The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios ...geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partners and female sex workers FSW) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections.
Since at least the late 1990s, HIV has been viewed as a major threat to efforts by countries to reduce under-5 mortality. Previous work has documented increased under-5 mortality due to HIV from 1990 ...to 1999 in Africa. The current analysis presents estimates and trends in under-5 mortality due to HIV in low- and middle-income countries by region up to 2009.
The analyses are based on the national models of HIV and AIDS produced by country teams in coordination with UNAIDS and its partners for the years 1990-2009. These models produce a time series of estimates of HIV-related mortality as well as overall mortality in children aged <5 years.
These analyses indicate that, in 2009, HIV accounted for roughly 2.1% (1.2-3.0%) of under-5 deaths in low- and middle-income countries and 3.6% (2.0-5.0%) in sub-Saharan Africa. The percentage of under-5 deaths due to HIV has been falling in the last decade--for example, from 2.6% (1.6-3.5%) in 2000 to 2.1% (1.2-3.0%) in 2009 in low- and middle-income countries and from 5.4% (3.3-7.3%) in 2000 to 3.6% (2.0-5.0%) in 2009 in sub-Saharan Africa. This fall in the percentage of under-5 deaths due to HIV has been driven by a combination of factors including scale-up of prevention of mother-to-child transmission programmes and treatment for pregnant women and children, as well as a decrease in the prevalence of HIV among pregnant women.
The Spectrum projection package uses estimates of national HIV incidence, demographic data and other assumptions to describe the consequences of the HIV epidemic in low and middle-income countries. ...The default parameters used in Spectrum are updated every 2 years as new evidence becomes available to inform the model. This paper reviews the default parameters that define the course of HIV progression among adults and children in Spectrum.
For adults, data available from published and grey literature and data from the ART-LINC International epidemiologic Database to Evaluate AIDS (IeDEA) collaboration were combined to estimate survival among those who started antiretroviral therapy (ART). For children, a review of published material on survival on ART and survival on ART and cotrimoxazole was used to derive survival probabilities. Historical data on the distribution of CD4 cell counts and CD4 cell percentages by age among children who were not treated (before treatment was available) were used to progress children from seroconversion to different CD4 cell levels.
Based on the updated evidence estimated survival among adults aged over 15 years in the first year on ART was 86%, while in subsequent years survival was estimated at 90%. Survival among children during the first year on ART was estimated to be 85% and for subsequent years 93%.
The revised default parameters based on additional data will make Spectrum estimates more accurate than previous rounds of estimates.
This article examines whether increased years of schooling exercised a consistent impact on delayed childbearing in sub-Saharan Africa. Data were drawn from Demographic and Health Surveys conducted ...in eight countries over the period 1987-1999. Multiple logistic regressions were used to assess trends and determinants in the probability of first birth during adolescence. Girls’ education from about the secondary level onwards was found to be the only consistently significant covariate. No effect of community aggregate education was discernible, after controlling for urbanity and other individual-level variables. The results reinforce previous findings that improving girls’ education is a key instrument for raising ages at first birth, but suggest that increases in schooling at lower levels alone bear only somewhat on the prospects for fertility decline among adolescents.
The Spectrum computer package is used to generate national AIDS mortality estimates in settings where vital registration systems are lacking. Similarly, InterVA-4 (the latest version of the InterVA ...programme) is used to estimate cause-of-mortality data in countries where cause-specific mortality data are not available.
This study aims to compare trends in adult AIDS-related mortality estimated by Spectrum with trends from the InterVA-4 programme applied to data from a Health and Demographic Surveillance System (HDSS) in Nairobi, Kenya.
A Spectrum model was generated for the city of Nairobi based on HIV prevalence data for Nairobi and national antiretroviral therapy coverage, underlying mortality, and migration assumptions. We then used data, generated through verbal autopsies, on 1,799 deaths that occurred in the HDSS area from 2003 to 2010 among adults aged 15-59. These data were then entered into InterVA-4 to estimate causes of death using probabilistic modelling. Estimates of AIDS-related mortality rates and all-cause mortality rates from Spectrum and InterVA-4 were compared and presented as annualised trends.
Spectrum estimated that HIV prevalence in Nairobi was 7%, while the HDSS site measured 12% in 2010. Despite this difference, Spectrum estimated higher levels of AIDS-related mortality. Between 2003 and 2010, the proportion of AIDS-related mortality in Nairobi decreased from 63 to 40% according to Spectrum and from 25 to 16% according to InterVA. The net AIDS-related mortality in Spectrum was closer to the combined mortality rates when AIDS and tuberculosis (TB) deaths were included for InterVA-4.
Overall trends in AIDS-related deaths from both methods were similar, although the values were closer when TB deaths were included in InterVA. InterVA-4 might not accurately differentiate between TB and AIDS deaths.
Governments are increasingly recognizing the need to focus limited HIV resources on specific geographic areas and specific populations to have a greater impact. Nigeria, with the second largest HIV ...epidemic in the world, is an important example of where more localized programming has the potential to improve the efficiency of the HIV response.
Using Spectrum software we modelled the Nigerian HIV epidemic using two methods: First, we created national HIV estimates using trends in urban and rural areas. Second, we created national HIV estimates using trends from each of the 37 states in Nigeria and aggregated these results. In both instances we used HIV surveillance data from antenatal clinics and household surveys and aggregated the trends to determine the national epidemic.
The state models showed divergent trends in the 37 states. Comparing the national results calculated from the two methods resulted in different conclusions. In the aggregated state files, adult HIV incidence in Nigeria was stable between 2005 and 2013 (change of -6%), whereas the urban and rural file suggested incidence was decreasing over the same time (change of -50%). This difference was also reflected in the HIV prevalence trends, although the two methods showed similar trends in AIDS-related mortality. The two models had similar adult HIV prevalence in 2013: 3.0% (2.0-4.5%) in the aggregated state files versus 3.2% (3.0-3.5%) in the urban/rural file.
The state-level estimates provide insight into the variations of the HIV epidemic in each state and provide useful information for programme managers. However, the reliability of the results is highly dependent on the amount and quality of data available from each sub-national area.
Retention of patients on antiretroviral therapy (ART) over time is a proxy for quality of care and an outcome indicator to monitor ART programs. Using existing databases (Antiretroviral in Lower ...Income Countries of the International Databases to Evaluate AIDS and Médecins Sans Frontières), we evaluated three sampling approaches to simplify the generation of outcome indicators.
We used individual patient data from 27 ART sites and included 27,201 ART-naive adults (≥15 years) who initiated ART in 2005. For each site, we generated two outcome indicators at 12 months, retention on ART and proportion of patients lost to follow-up (LFU), first using all patient data and then within a smaller group of patients selected using three sampling methods (random, systematic and consecutive sampling). For each method and each site, 500 samples were generated, and the average result was compared with the unsampled value. The 95% sampling distribution (SD) was expressed as the 2.5(th) and 97.5(th) percentile values from the 500 samples. Overall, retention on ART was 76.5% (range 58.9-88.6) and the proportion of patients LFU, 13.5% (range 0.8-31.9). Estimates of retention from sampling (n = 5696) were 76.5% (SD 75.4-77.7) for random, 76.5% (75.3-77.5) for systematic and 76.0% (74.1-78.2) for the consecutive method. Estimates for the proportion of patients LFU were 13.5% (12.6-14.5), 13.5% (12.6-14.3) and 14.0% (12.5-15.5), respectively. With consecutive sampling, 50% of sites had SD within ±5% of the unsampled site value.
Our results suggest that random, systematic or consecutive sampling methods are feasible for monitoring ART indicators at national level. However, sampling may not produce precise estimates in some sites.
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