Using Observational Data to Inform HIV Policy Change for Children and Youth

Abstract

Abstract:Observational data characterizing the pediatric and adolescent HIV epidemics in real-world settings are critical to informing clinical guidelines, governmental HIV programs, and donor prioritization. Global expertise in curating and analyzing these data has been expanding, with increasingly robust collaborations and the identification of gaps in existing surveillance capacity. In this commentary, we describe existing sources of observational data for children and youth living with HIV, focusing on larger regional and global research cohorts, and targeted surveillance studies and programs. Observational data are valuable resources to cross-validate other research and to monitor the impact of changing HIV program policies. Observational studies were among the first to highlight the growing population of children surviving perinatal HIV and transitioning to adolescence and young adulthood, and have raised serious concerns about high rates of treatment failure, loss to follow-up, and death among older perinatally infected youth. The use of observational data to inform modeling of the current global epidemic, predict future patterns of the youth cascade, and facilitate antiretroviral forecasting are critical priorities and key end products of observational HIV research. Greater investments into data infrastructure are needed at the local level to improve data quality and at the global level to faciliate reliable interpretation of the evolving patterns of the pediatric and youth epidemics. Although this includes harmonized data forms, use of unique patient identifiers to allow for data linkages across routine data sets and electronic medical record systems, and competent data managers and analysts are essential to make optimal use of the data collected.

Global HIV mortality trends among children on antiretroviral treatment corrected for under‐reported deaths: an updated analysis of the International epidemiology Databases to Evaluate AIDS collaboration

“…Accurate estimates of the number of children living with HIV (CHIV) are essential for programme planning and resource allocation [1,2]. Further, the number of deaths among CHIV and paediatric antiretroviral therapy (ART) coverage are important measures of programme effectiveness and progress towards targets such as the Joint United Nations Programme http://onlinelibrary.wiley.com/doi/10.1002/jia2.25780/full | https://doi.org/10.1002/jia2.25780 on HIV/AIDS (UNAIDS) 90-90-90 goal [3].…”

Using Climate-HIV to describe real-world clinical outcomes for people living with HIV taking dolutegravir-based regimens

“…Databases like the Climate-HIV database that collect data on treatment outcomes in patients with HIV-1 infection provide valuable information for addressing evidence gaps not likely to be assessed in randomised control trials. 37 , 39 Climate-HIV at the time of study design was the only single-point database with detailed patient-level data for individuals with HIV and was shared across four large separate NHS trusts with broad patient demographics. Climate-HIV was also the only database with single-point access as it was linked to the electronic patient record system so CD4 + cell count and viral load records were up-to-date.…”

“…Such evidence is important for evaluating the real-world implementation of new treatment guidelines or interventions. 39 , 40 Thus, the dissemination of HIV-1 treatment outcomes data from databases, including the real-world DBR clinical outcomes reported in this analysis, is critical for informing the real-world success of HIV-1 treatments.…”

Predictors of retention in the prospective HIV prevention OKAPI cohort in Kinshasa

“…Observational studies can show the real-world context outside the controlled protocols of clinical trials. They can help to properly design preventive interventions, and to improve their feasibility, uptake, acceptability and efficiency 17 – 20 . Longitudinal observational studies can also provide information concerning loss to follow-up (LTFU) and their predictors, which is relevant for the implementation of HIV preventive strategies, and to improve the quality of the data obtained 21 .…”