The projected prevalence of comorbidities and multimorbidity in people with HIV in the United States through the year 2030

Importance Estimating the medical complexity of people aging with HIV can inform clinical programs and policy to meet future healthcare needs. Objective To project the prevalence of comorbidities and multimorbidity among people with HIV (PWH) using antiretroviral therapy (ART) in the US through 2030. Design Agent-based simulation model Setting HIV clinics in the United States in the recent past (2020) and near future (2030) Participants In 2020, 674,531 PWH were using ART; 9% were men and 4% women with history of injection drug use; 60% were men who have sex with men (MSM); 8% were heterosexual men and 19% heterosexual women; 44% were non-Hispanic Black/African American (Black); 32% were non-Hispanic White (White); and 23% were Hispanic. Exposure(s) Demographic and HIV acquisition risk subgroups Main Outcomes and Measures Projected prevalence of anxiety, depression, stage ≥3 chronic kidney disease (CKD), dyslipidemia, diabetes, hypertension, cancer, end-stage liver disease (ESLD), myocardial infarction (MI), and multimorbidity (≥2 mental or physical comorbidities, other than HIV). Results We projected 914,738 PWH using ART in the US in 2030. Multimorbidity increased from 58% in 2020 to 63% in 2030. The prevalence of depression and/or anxiety was high and increased from 60% in 2020 to 64% in 2030. Hypertension and dyslipidemia decreased, diabetes and CKD increased, MI increased steeply, but there was little change in cancer and ESLD. Among Black women with history of injection drug use (oldest demographic subgroup in 2030), CKD, anxiety, hypertension, and depression were most prevalent and 93% were multimorbid. Among Black MSM (youngest demographic subgroup in 2030), depression was highly prevalent, followed by hypertension and 48% were multimorbid. Comparatively, 67% of White MSM were multimorbid in 2030 (median age in 2030=59 years) and anxiety, depression, dyslipidemia, CKD, and hypertension were highly prevalent. Conclusion and relevance The distribution of multimorbidity will continue to differ by race/ethnicity, gender, and HIV acquisition risk subgroups, and be influenced by age and risk factor distributions that reflect the impact of social disparities of the health on women, people of color, and people who use drugs. HIV clinical care models and funding are urgently required to meet the healthcare needs of people with HIV in the next decade. Question How will the prevalence of multimorbidity change among people with HIV (PWH) using antiretroviral therapy in the US from 2020 to 2030? Findings In this agent-based simulation study using data from the NA-ACCORD and the CDC, multimorbidity (≥2 mental/physical comorbidities other than HIV) will increase from 58% in 2020 to 63% in 2030. The composition of comorbidities among multimorbid PWH vary by race/ethnicity, gender, and HIV acquisition risk group. Meaning HIV clinical programs and policy makers must act now to identify resources and care models to meet the increasingly complex medical needs of PWH over time, particularly mental healthcare needs. ### Competing Interest Statement KN Althoff serves on the scientific review board for TrioHealth Inc and as a consultant to the All of Us Research Program. MJ Gill has been an Hoc member on national HIV Advisory Boards of Merck, Gilead and ViiV. C Wong is currently employed by Regeneron Pharmaceuticals Inc and contributed to this article as a prior trainee of Johns Hopkins University. All other co-authors report no competing interests. ### Funding Statement This research was supported by R01 AG053100 (PI: KN Althoff) from the National Institute on Aging, National Institutes of Health (NIH). PK was supported through the National Institution of Allergy and Infectious Diseases, NIH (Career development award, K01AI138853). EPH was supported through the National Institute on Aging, NIH (R01AG069575) and the Jerome and Celia Reich Endowed Scholar Award. The NA-ACCORD is supported by National Institutes of Health grants U01AI069918, F31AI124794, F31DA037788, G12MD007583, K01AI093197, K01AI131895, K23EY013707, K24AI065298, K24AI118591, K24DA000432, KL2TR000421, N01CP01004, N02CP055504, N02CP91027, P30AI027757, P30AI027763, P30AI027767, P30AI036219, P30AI050409, P30AI050410, P30AI094189, P30AI110527, P30MH62246, R01AA016893, R01DA011602, R01DA012568, R01AG053100, R24AI067039, R34DA045592, U01AA013566, U01AA020790, U01AI038855, U01AI038858, U01AI068634, U01AI068636, U01AI069432, U01AI069434, U01DA036297, U01DA036935, U10EY008057, U10EY008052, U10EY008067, U01HL146192, U01HL146193, U01HL146194, U01HL146201, U01HL146202, U01HL146203, U01HL146204, U01HL146205, U01HL146208, U01HL146240, U01HL146241, U01HL146242, U01HL146245, U01HL146333, U24AA020794, U54GM133807, UL1RR024131, UL1TR000004, UL1TR000083, UL1TR002378, Z01CP010214 and Z01CP010176; contracts CDC-200-2006-18797 and CDC-200-2015-63931 from the Centers for Disease Control and Prevention, USA; contract 90047713 from the Agency for Healthcare Research and Quality, USA; contract 90051652 from the Health Resources and Services Administration, USA; the Grady Health System; grants CBR-86906, CBR-94036, HCP-97105 and TGF-96118 from the Canadian Institutes of Health Research, Canada; Ontario Ministry of Health and Long Term Care, and the Government of Alberta, Canada. Additional support was provided by the National Institute Of Allergy And Infectious Diseases (NIAID), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Human Genome Research Institute (NHGRI), National Institute for Mental Health (NIMH) and National Institute on Drug Abuse (NIDA), National Institute On Aging (NIA), National Institute Of Dental & Craniofacial Research (NIDCR), National Institute Of Neurological Disorders And Stroke (NINDS), National Institute Of Nursing Research (NINR), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), and National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). These data were collected by cancer registries participating in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, or the US Center for Disease Control and Prevention, or Regeneron Pharmaceuticals Inc. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Johns Hopkins Bloomberg School of Public Health Institutional Review Board determined the PEARL study meets criteria permissible under the 2018 Common Rule as of August 31, 2021. This committee has allowed our study to proceed without ongoing continuing review through August 17, 2024. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All mathematical functions and input parameters used in the PEARL agent-based computer simulation model are available at [www.PEARLHIVmodel.org][1]. [1]: https://www.PEARLHIVmodel.org