Projecting the age-distribution of men who have sex with men receiving HIV treatment in the United States

Forecasting the effect of HIV-targeted interventions on the age distribution of people with HIV in Kenya

OBJECTIVES

To provide accurate forecasts of the age distribution of people with HIV (PWH) in Kenya from 2025 to 2040.

DESIGN

Development of a compartmental model of HIV in Kenya, calibrated to historical estimates of HIV epidemiology.

METHODS

We forecasted changes in population size and age distribution of new HIV infections and PWH under the status quo and under scale-up of HIV services.

RESULTS

Without scale-up, new HIV infections were forecasted to fall from 34 000 (28 000-41 000) in 2,025 to 29 000 (15 000-57 000) in 2,040; the percentage of new infections occurring among persons over 30 increased from 33% (20-50%) to 40% (24-62%). The median age of PWH increased from 39 years (38-40) in 2025 to 43 years (39-46) in 2040, and the percentage of PWH over age 50 increased from 26% (23-29%) to 34% (26-43%). Under the full intervention scenario, new infections were forecasted to fall to 6,000 (3,000-12 000) in 2,040. The percentage of new infections occurring in people over age 30 increased to 52% (34-71%) in 2,040, and there was an additional shift in the age structure of PWH [forecasted median age of 46 (43-48) and 40% (33-47%) over age 50].

CONCLUSION

PWH in Kenya are forecasted to age over the next 15 years; improvements to the HIV care continuum are expected to contribute to the growing proportion of older PWH.

The forecasted prevalence of comorbidities and multimorbidity in people with HIV in the United States through the year 2030: A modeling study

BACKGROUND

Estimating the medical complexity of people aging with HIV can inform clinical programs and policy to meet future healthcare needs. The objective of our study was to forecast the prevalence of comorbidities and multimorbidity among people with HIV (PWH) using antiretroviral therapy (ART) in the United States (US) through 2030.

METHODS AND FINDINGS

Using the PEARL model-an agent-based simulation of PWH who have initiated ART in the US-the 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) were forecasted through 2030. Simulations were informed by the US CDC HIV surveillance data of new HIV diagnosis and the longitudinal North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) data on risk of comorbidities from 2009 to 2017. The simulated population represented 15 subgroups of PWH including Hispanic, non-Hispanic White (White), and non-Hispanic Black/African American (Black/AA) men who have sex with men (MSM), men and women with history of injection drug use and heterosexual men and women. Simulations were replicated for 200 runs and forecasted outcomes are presented as median values (95% uncertainty ranges are presented in the Supporting information). In 2020, PEARL forecasted a median population of 670,000 individuals receiving ART in the US, of whom 9% men and 4% women with history of injection drug use, 60% MSM, 8% heterosexual men, and 19% heterosexual women. Additionally, 44% were Black/AA, 32% White, and 23% Hispanic. Along with a gradual rise in population size of PWH receiving ART-reaching 908,000 individuals by 2030-PEARL forecasted a surge in prevalence of most comorbidities to 2030. Depression and/or anxiety was high and increased from 60% in 2020 to 64% in 2030. Hypertension decreased while dyslipidemia, diabetes, CKD, and MI increased. There was little change in prevalence of cancer and ESLD. The forecasted multimorbidity among PWH receiving ART increased from 63% in 2020 to 70% in 2030. There was heterogeneity in trends across subgroups. Among Black women with history of injection drug use in 2030 (oldest demographic subgroup with median age of 66 year), dyslipidemia, CKD, hypertension, diabetes, anxiety, and depression were most prevalent, with 92% experiencing multimorbidity. Among Black MSM in 2030 (youngest demographic subgroup with median age of 42 year), depression and CKD were highly prevalent, with 57% experiencing multimorbidity. These results are limited by the assumption that trends in new HIV diagnoses, mortality, and comorbidity risk observed in 2009 to 2017 will persist through 2030; influences occurring outside this period are not accounted for in the forecasts.

CONCLUSIONS

The PEARL forecasts suggest a continued rise in comorbidity and multimorbidity prevalence to 2030, marked by heterogeneities across race/ethnicity, gender, and HIV acquisition risk subgroups. HIV clinicians must stay current on the ever-changing comorbidities-specific guidelines to provide guideline-recommended care. HIV clinical directors should ensure linkages to subspecialty care within the clinic or by referral. HIV policy decision-makers must allocate resources and support extended clinical capacity to meet the healthcare needs of people aging with HIV.

Impact of subgroup-specific heterogeneities and dynamic changes in mortality rates on forecasted population size, deaths, and age distribution of persons receiving antiretroviral treatment in the United States: a computer simulation study

PURPOSE

Model-based forecasts of population size, deaths, and age distribution of people with HIV (PWH) are helpful for public health and clinical services planning but are influenced by subgroup-specific heterogeneities and changes in mortality rates.

METHODS

Using an agent-based simulation of PWH in the United States, we examined the impact of distinct approaches to parametrizing mortality rates on forecasted epidemiology of PWH on antiretroviral treatment (ART). We first estimated mortality rates among (1) all PWH, (2) sex-specific, (3) sex-and-race/ethnicity-specific, and (4) sex-race/ethnicity-and-HIV-acquisition-risk-specific subgroups. We then assessed each scenario by (1) allowing unrestricted reductions in age-specific mortality rates over time and (2) restricting the mortality rates among PWH to subgroup-specific mortality thresholds from the general population.

RESULTS

Among the eight scenarios examined, those lacking subgroup-specific heterogeneities and those allowing unrestricted reductions in future mortality rates forecasted the lowest number of deaths among all PWH and 9 of the 15 subgroups through 2030. The forecasted overall number and age distribution of people with a history of injection drug use were sensitive to inclusion of subgroup-specific mortality rates.

CONCLUSIONS

Our results underscore the potential risk of underestimating future deaths by models lacking subgroup-specific heterogeneities in mortality rates, and those allowing unrestricted reductions in future mortality rates.

Microbiota-derived short-chain fatty acids and modulation of host-derived peptides formation: Focused on host defense peptides

The byproducts of bacterial fermentation known as short-chain fatty acids (SCFAs) are chemically comprised of a carboxylic acid component and a short hydrocarbon chain. Recent investigations have demonstrated that SCFAs can affect intestinal immunity by inducing endogenous host defense peptides (HDPs) and their beneficial effects on barrier integrity, gut health, energy supply, and inflammation. HDPs, which include defensins, cathelicidins, and C-type lectins, perform a significant function in innate immunity in gastrointestinal mucosal membranes. SCFAs have been demonstrated to stimulate HDP synthesis by intestinal epithelial cells via interactions with G protein-coupled receptor 43 (GPR43), activation of the Jun N-terminal kinase (JNK) and Mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) pathways, and the cell growth pathways. Furthermore, SCFA butyrate has been demonstrated to enhance the number of HDPs released from macrophages. SCFAs promote monocyte-to-macrophage development and stimulate HDP synthesis in macrophages by inhibiting histone deacetylase (HDAC). Understanding the etiology of many common disorders might be facilitated by studies into the function of microbial metabolites, such as SCFAs, in the molecular regulatory processes of immune responses (e.g., HDP production). This review will focus on the current knowledge of the role and mechanism of microbiota-derived SCFAs in influencing the synthesis of host-derived peptides, particularly HDPs.

A Growing Number of Men Who Have Sex With Men Aging With HIV (20212031): A Comparison of Two Microsimulation Models

BACKGROUND

Men who have sex with men (MSM) on antiretroviral therapy (ART) are at risk for multimorbidity as life expectancy increases. Simulation models can project population sizes and age distributions to assist with health policy planning.

METHODS

We populated the CEPAC-US model with CDC data to project the HIV epidemic among MSM in the United States. The PEARL model was predominantly informed by NA-ACCORD data (20092017). We compared projected population sizes and age distributions of MSM receiving ART (20212031) and investigated how parameters and assumptions affected results.

RESULTS

We projected an aging and increasing population of MSM on ART: CEPAC-US, mean age 48.6 (SD 13.7) years in 2021 versus 53.9 (SD 15.0) years in 2031; PEARL, 46.7 (SD 13.2) years versus 49.2 (SD 14.6) years. We projected 548 800 MSM on ART (147 020 65 years) in 2031 (CEPAC-US) and 599 410 (113 400 65 years) (PEARL). Compared with PEARL, CEPAC-US projected a smaller population of MSM on ART by 2031 and a slower increase in population size, driven by higher estimates of disengagement in care and mortality.

CONCLUSIONS

Findings from two structurally distinct microsimulation models suggest that the MSM population receiving ART in the United States will increase and age over the next decade. Subgroup-specific data regarding engagement in care and mortality can improve projections and inform health care policy planning.

Projection of age of individuals living with HIV and time since ART initiation in 2030: estimates for France

Introduction

Thanks to antiretroviral treatment (ART), people living with HIV (PLHIV) are living longer and ageing. However, ageing involves increased risks of co‐morbidities, which also depend on when PLHIV individuals started ART. To tackle the HIV age‐related upcoming challenges, knowledge of the current and future age structure of the HIV population is needed. Here, we forecast the demographic profile of the adult population living with diagnosed HIV (aPLdHIV) in France until 2030, accounting for the impact of the ART initiation period on mortality.

Methods

We used national data from the French Hospital Database on HIV (ANRS CO4‐FHDH) and a sample of the National Health Data System to, first, characterize the aPLdHIV in 2018 and estimate their mortality rates according to age, sex and ART initiation period. Second, we used national HIV surveillance data to define three scenarios for the numbers of newly diagnosed HIV cases over 2019–2030: 30% decrease in HIV cases (S1), status quo situation (S2) and epidemic elimination (S3). We then combined these data using a matrix model, to project the age structure of aPLdHIV and time since ART initiation.

Results

In 2018, there was an estimated 161,125 aPLdHIV (33% women), of which 55% were aged 50 or older (50+), 22% aged 60+ and 8% aged 70+. In 2030, the aPLdHIV would grow to 195,246 for S1, 207,972 for S2 and 167,221 for S3. Whatever the scenario, in 2030, the estimated median time since ART initiation would increase and age distribution would shift towards older ages: with 65–72% aPLdHIV aged 50+, 42–48% 60+ and 17–19% 70+. This corresponds to ∼83,400 aPLdHIV (28% women) aged 60+, among which ∼69% started ART more than 20 years ago (i.e. before 2010) and ∼39% ≥30 years ago (i.e. before 2000), and to ∼33,100 aPLdHIV (27% women) aged 70+, among which ∼72% started ART ≥20 years ago and ∼43% ≥30 years ago.

Conclusions

By 2030, in France, close to 20% of the aPLdHIV will be aged 70+, of which >40% would have started ART more than 30 years ago. These estimates are essential to adapt co‐morbidities screening and anticipate resource provision in the aged care sector.