Keri N Althoff1, Cameron N Stewart1, Elizabeth Humes1, Jinbing Zhang1, Lucas Gerace1, Cynthia M Boyd1,2, Cherise Wong3, Amy C Justice4, Kelly A Gebo1,2, Jennifer E Thorne1,2, Anna A Rubtsova5, Michael A Horberg6, Michael J Silverberg7, Sean X Leng2, Peter F Rebeiro8, Richard D Moore2, Kate Buchacz9, Parastu Kasaie1. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health. 2. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland. 3. Worldwide Medical and Safety, Pfizer Inc., New York, New York. 4. Yale Schools of Medicine and Public Health and the VA Connecticut Healthcare System, New Haven, Connecticut. 5. Department of Behavioral, Social, and Health Education Sciences, Emory University Rollins School of Public Health, Atlanta, Georgia. 6. Kaiser Permanente Mid-Atlantic Permanente Research Institute, Rockville, Maryland. 7. Division of Research, Kaiser Permanente Northern California, Oakland, California. 8. Department of Medicine, Divisions of Infectious Diseases & Epidemiology; Department of Biostatistics; Vanderbilt University School of Medicine, Nashville, Tennessee. 9. Division of HIV Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Abstract
OBJECTIVE: To project the future age distribution of people with HIV using antiretroviral therapy (ART) in the United States, under expected trends in HIV diagnosis and survival (baseline scenario) and achieving the ending the HIV epidemic (EHE) goals of a 75% reduction in HIV diagnoses from 2020 to 2025 and sustaining levels to 2030 (EHE75% scenario). DESIGN: An agent-based simulation model with mathematical functions estimated from North American AIDS Cohort Collaboration on Research and Design data and parameters from the US Centers for Disease Control and Prevention's annual HIV surveillance reports. METHODS: The PEARL (ProjEcting Age, MultimoRbidity, and PoLypharmacy in adults with HIV) model simulated individuals in 15 subgroups of sex-and-HIV acquisition risk and race/ethnicity. Simulation outcomes from the baseline scenario are compared with outcomes from the EHE75% scenario. RESULTS: Under the baseline scenario, PEARL projects a substantial increase in number of ART-users over time, reaching a population of 909 638 [95% uncertainty range (UR): 878 449-946 513] by 2030. The overall median age increased from 50 years in 2020 to 52 years in 2030, with 23% of ART-users age ≥65 years in 2030. Under the EHE75% scenario, the projected number of ART-users was 718 348 [703 044-737 817] (median age = 56 years) in 2030, with a 70% relative reduction in ART-users <30 years and a 4% relative reduction in ART-users age ≥65 years compared to baseline, and persistent heterogeneities in projected numbers by sex-and-HIV acquisition risk group and race/ethnicity. CONCLUSIONS: It is critical to prepare healthcare systems to meet the impending demand of the US population aging with HIV.
OBJECTIVE: To project the future age distribution of people with HIV using antiretroviral therapy (ART) in the United States, under expected trends in HIV diagnosis and survival (baseline scenario) and achieving the ending the HIV epidemic (EHE) goals of a 75% reduction in HIV diagnoses from 2020 to 2025 and sustaining levels to 2030 (EHE75% scenario). DESIGN: An agent-based simulation model with mathematical functions estimated from North American AIDS Cohort Collaboration on Research and Design data and parameters from the US Centers for Disease Control and Prevention's annual HIV surveillance reports. METHODS: The PEARL (ProjEcting Age, MultimoRbidity, and PoLypharmacy in adults with HIV) model simulated individuals in 15 subgroups of sex-and-HIV acquisition risk and race/ethnicity. Simulation outcomes from the baseline scenario are compared with outcomes from the EHE75% scenario. RESULTS: Under the baseline scenario, PEARL projects a substantial increase in number of ART-users over time, reaching a population of 909 638 [95% uncertainty range (UR): 878 449-946 513] by 2030. The overall median age increased from 50 years in 2020 to 52 years in 2030, with 23% of ART-users age ≥65 years in 2030. Under the EHE75% scenario, the projected number of ART-users was 718 348 [703 044-737 817] (median age = 56 years) in 2030, with a 70% relative reduction in ART-users <30 years and a 4% relative reduction in ART-users age ≥65 years compared to baseline, and persistent heterogeneities in projected numbers by sex-and-HIV acquisition risk group and race/ethnicity. CONCLUSIONS: It is critical to prepare healthcare systems to meet the impending demand of the US population aging with HIV.
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