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

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

By: Annette H. Sohn, Ali Judd, Lynne Mofenson, Marisa Vicari, Degu Jerene, Valeriane Leroy, Linda-Gail Bekker, Mary-Ann Davies
Publication: Journal of Acquired Immune Deficiency Syndromes2018; Vol. 78, Suppl. 1: S22-S26. DOI: 10.1097/QAI.0000000000001745.

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.