Background: We estimated the magnitude of the HIV epidemic among children and youth living with HIV (CYHIV) aged 0-25 years in Thailand, projecting forward from 2005 to 2025, and identified underreported input parameters that influence epidemic projections, in order to inform future public health and research priorities.
Methods: We developed a focused multi-state transition model incorporating perinatally-acquired HIV and non-perinatally-acquired HIV, stratified by population, including men who have sex with men (MSM), female sex workers (FSW), people who inject drugs (PWID), and the remainder of the population ("other"). We populated the model with published and programmatic data from the Thai national AIDS program when available. We projected the period from 2005-2025 and compared model results to programmatic data and projections from other models. In a scenario analysis, we projected the potential impact of pre-exposure prophylaxis (PrEP) for MSM from 2018-2025.
Results: The initial 2005 cohort was comprised of 66,900 CYHIV; 8% CYHIV were <5 years, 21% were 5-14 years, and 71% were 15-25 years of age. By 2020, 94% were projected to be >15 years and infections among MSM constituted 83% of all new HIV infections. The numbers of CYHIV decreased over time, projected to reach 30,760 by 2020 (-54%) and 22,640 by 2025 (-66%). The proportion of all CYHIV aged 0-25 who were diagnosed and on ART increased from 37 to 60% over the 2005-2025 period. Projections were sensitive to variations in assumptions about initial HIV prevalence and incidence among MSM, PWID, and "other" youth.
Conclusions: More data on incidence rates among sexual and gender minority youth and PWID are needed to characterize the role of specific exposures and key populations in the adolescent HIV epidemic. More accurate estimates will project shifts in population and inform more targeted interventions to prevent and care for Thai CYHIV.
Copyright: © 2022 Desmonde et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.