Nearly Half Of US Adults Living With HIV Received Federal Disability Benefits In 2009

Joint modeling HIV and HPV using a new hybrid agent-based network and compartmental simulation technique

Persons living with human immunodeficiency virus (HIV) have a disproportionately higher burden of human papillomavirus infection (HPV)-related cancers. Causal factors include both behavioral and biological. While pharmaceutical and care support interventions help address biological risk of coinfection, as social conditions are common drivers of behaviors, structural interventions are key part of behavioral interventions. Our objective is to develop a joint HIV-HPV model to evaluate the contribution of each factor, to subsequently inform intervention analyses. While compartmental modeling is sufficient for faster spreading HPV, network modeling is suitable for slower spreading HIV. However, using network modeling for jointly modeling HIV and HPV can generate computational complexities given their vastly varying disease epidemiology and disease burden across sub-population groups. We applied a recently developed mixed agent-based compartmental (MAC) simulation technique, which simulates persons with at least one slower spreading disease and their immediate contacts as agents in a network, and all other persons including those with faster spreading diseases in a compartmental model, with an evolving contact network algorithm maintaining the dynamics between the two models. We simulated HIV and HPV in the U.S. among heterosexual female, heterosexual male, and men who have sex with men (men only and men and women) (MSM), sub-populations that mix but have varying HIV burden, and cervical cancer among women. We conducted numerical analyses to evaluate the contribution of behavioral and biological factors to risk of cervical cancer among women with HIV. The model outputs for HIV, HPV, and cervical cancer compared well with surveillance estimates. Model estimates for relative prevalence of HPV (1.67 times) and relative incidence of cervical cancer (3.6 times), among women with HIV compared to women without, were also similar to that reported in observational studies in the literature. The fraction attributed to biological factors ranged from 22-38% for increased HPV prevalence and 80% for increased cervical cancer incidence, the remaining attributed to behavioral. The attribution of both behavioral and biological factors to increased HPV prevalence and cervical cancer incidence suggest the need for behavioral, structural, and pharmaceutical interventions. Validity of model results related to both individual and joint disease metrics serves as proof-of-concept of the MAC simulation technique. Understanding the contribution of behavioral and biological factors of risk helps inform interventions. Future work can expand the model to simulate sexual and care behaviors as functions of social conditions to jointly evaluate behavioral, structural, and pharmaceutical interventions for HIV and cervical cancer prevention.

A new mixed agent-based network and compartmental simulation framework for joint modeling of related infectious diseases- application to sexually transmitted infections

Background

A model that jointly simulates infectious diseases with common modes of transmission can serve as a decision-analytic tool to identify optimal intervention combinations for overall disease prevention. In the United States, sexually transmitted infections (STIs) are a huge economic burden, with a large fraction of the burden attributed to HIV. Data also show interactions between HIV and other sexually transmitted infections (STIs), such as higher risk of acquisition and progression of co-infections among persons with HIV compared to persons without. However, given the wide range in prevalence and incidence burdens of STIs, current compartmental or agent-based network simulation methods alone are insufficient or computationally burdensome for joint disease modeling. Further, causal factors for higher risk of coinfection could be both behavioral (i.e., compounding effects of individual behaviors, network structures, and care behaviors) and biological (i.e., presence of one disease can biologically increase the risk of another). However, the data on the fraction attributed to each are limited.

Methods

We present a new mixed agent-based compartmental (MAC) framework for jointly modeling STIs. It uses a combination of a new agent-based evolving network modeling (ABENM) technique for lower-prevalence diseases and compartmental modeling for higher-prevalence diseases. As a demonstration, we applied MAC to simulate lower-prevalence HIV in the United States and a higher-prevalence hypothetical Disease 2, using a range of transmission and progression rates to generate burdens replicative of the wide range of STIs. We simulated sexual transmissions among heterosexual males, heterosexual females, and men who have sex with men (men only and men and women). Setting the biological risk of co-infection to zero, we conducted numerical analyses to evaluate the influence of behavioral factors alone on disease dynamics.

Results

The contribution of behavioral factors to risk of coinfection was sensitive to disease burden, care access, and population heterogeneity and mixing. The contribution of behavioral factors was generally lower than observed risk of coinfections for the range of hypothetical prevalence studied here, suggesting potential role of biological factors, that should be investigated further specific to an STI.

Conclusions

The purpose of this study is to present a new simulation technique for jointly modeling infectious diseases that have common modes of transmission but varying epidemiological features. The numerical analysis serves as proof-of-concept for the application to STIs. Interactions between diseases are influenced by behavioral factors, are sensitive to care access and population features, and are likely exacerbated by biological factors. Social and economic conditions are among key drivers of behaviors that increase STI transmission, and thus, structural interventions are a key part of behavioral interventions. Joint modeling of diseases helps comprehensively simulate behavioral and biological factors of disease interactions to evaluate the true impact of common structural interventions on overall disease prevention. The new simulation framework is especially suited to simulate behavior as a function of social determinants, and further, to identify optimal combinations of common structural and disease-specific interventions.

Successful Functional Aging in Middle-Aged and Older Adults with HIV

People living with HIV (PLWH) experience greater everyday functioning impairment. We examined frequency and correlates of successful functional aging (SFA) in PLWH. Using gold-standard questionnaires, SFA was defined in 174 HIV+ and 71 HIV- adults as absence of significant everyday cognitive symptoms and declines in instrumental activities of daily living. More HIV- (45%) than HIV+ (18%) adults met SFA criteria (p < 0.01). Depression, cognitive functioning, socioeconomic status, and HIV status were independent correlates of SFA (p values < 0.05). Motor ability, learning, and verbal fluency were associated with SFA. SFA was associated with health-related quality of life (HRQoL). PLWH are three times less likely to achieve SFA than HIV- adults, a phenotype that translates to HRQoL. While SFA is multifactorial, driven by clinico-demographic factors, HIV may pose additional risk to achieving SFA. Further work should examine other mechanisms whereby HIV hinders SFA (e.g., biomarkers, stress, mental health) and ultimately inform interventions to facilitate SFA.

Food Insecurity Is Associated with Cognitive Deficits Among HIV-Positive, But Not HIV-Negative, Individuals in a United States Sample

People living with HIV/AIDS (PLWHA) in the United States (US) have disproportionately high rates of food insecurity (FI). In the general population, FI has been associated with cognitive impairment among older adults and may exacerbate HIV-associated neurocognitive disorders. The current study assessed the effects of FI and HIV infection on the neuropsychological performance of 61 HIV-positive and 36 HIV-negative adults in the US. While the main effects were minimal, the interactive effects revealed that FI was related to deficits in speed of information processing, learning, memory, motor function, and overall cognitive impairment for the HIV-positive group, but not the HIV-negative group. The interactive effects remained after controlling for relevant sociodemographic characteristics. Although bidirectional associations cannot be ruled out in a cross-sectional study, the results suggest that FI may contribute to cognitive impairment among HIV-positive adults in the US. Given the high rates of socioeconomic disadvantage among PLWHA in the US, addressing FI as part of routine clinical care may be warranted.

Transitioning From Medicaid Disability Coverage to Long-Term Medicare Coverage: The Case of People Living With HIV/AIDS in California

Medicaid can serve as a bridge to Medicare coverage for the long-term disabled with sufficient covered work experience. We perform multinomial logistic regression on 2007-2010 Medicare and Medicaid claims data to examine transitions to Medicare for people living with HIV/AIDS (PLWHA) in California who had Medicaid coverage in 2007. We find only 16% had obtained Medicare coverage by 2010. African-Americans, women, individuals with schizophrenia diagnoses, alcohol or substance abuse disorders, and any physical comorbidity were significantly less likely than others to obtain Medicare (p < 0.001). This study contributes new information on the impact of eligibility requirements for Medicare long-term disability insurance for PLWHA. About one-third of PLWHA under age 65 are covered by Medicaid. Many PLWHA get stuck in Medicaid because their disability prevents them from obtaining the additional employment experience needed to qualify for Medicare.

HIV Testing among Outpatients with Medicaid and Commercial Insurance

Objective

To assess HIV testing and factors associated with receipt of testing among persons with Medicaid and commercial insurance during 2012.

Methods

Outpatient and laboratory claims were analyzed from two databases: all Medicaid claims from six states and all claims from Medicaid health plans from four other states and a large national convenience sample of patients with commercial insurance in the United States. We excluded those aged <13 years and >64 years, enrolled <9 of the 12 months, pregnant females, and previously diagnosed with HIV. We identified patients with new HIV diagnoses that followed (did not precede) the HIV test, using HIV ICD-9 codes. HIV testing percentages were assessed by patient demographics and other tests or diagnoses that occurred during the same visit.

Results

During 2012, 89,242 of 2,069,536 patients (4.3%) with Medicaid had at least one HIV test, and 850 (1.0%) of those tested received a new HIV diagnosis. Among 27,206,804 patients with commercial insurance, 757,646 (2.8%) had at least one HIV test, and 5,884 (0.8%) of those tested received a new HIV diagnosis. During visits that included an HIV test, 80.2% of Medicaid and 83.0% of commercial insurance claims also included a test or diagnosis for a sexually transmitted infection (STI), and/or Hepatitis B or C virus at the same visit.

Conclusions

HIV testing primarily took place concurrently with screening or diagnoses for STIs or Hepatitis B or C. We found little evidence to suggest routine screening for HIV infection was widespread.