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Updated: May 30, 2026

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells
Published on: March 3, 2017
Use of Medicaid data to explore community characteristics associated with HIV prevalence among beneficiaries with
James Walkup1, Ayse Akincigil, Donald R Hoover
1Institute for Health, Health Care Policy, and Aging Research, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA. walkup@rci.rutgers.edu
Objectives:
People with severe mental illness (SMI) may be at increased risk for several adverse health conditions, including HIV/AIDS. This disproportionate disease burden has been studied primarily at the individual rather than community level, in part due to the rarity of data sources linking individual information on medical and mental health characteristics with community-level data. We demonstrated the potential of Medicaid data to address this gap.
Methods:
We analyzed data on Medicaid beneficiaries with schizophrenia from eight states that account for 66% of cumulative AIDS cases nationally.
Results:
Across 44 metropolitan statistical areas (MSAs), the treated prevalence of HIV among adult Medicaid beneficiaries diagnosed with schizophrenia was 1.56% (standard deviation = 1.31%). To explore possible causes of variation, we linked claims files with a range of MSA social and contextual variables including local AIDS prevalence rates, area-based economic measures, crime rates, substance abuse treatment resources, and estimates of injection drug users (IDUs) and HIV infection among IDUs, which strongly predicted community infection rates among people with schizophrenia.
Conclusions:
Effective strategies for HIV prevention among people with SMI may include targeting prevention efforts to areas where risk is greatest; examining social network links between IDU and SMI groups; and implementing harm reduction, drug treatment, and other interventions to reduce HIV spread among IDUs. Our findings also suggest the need for research on HIV among people with SMI that examines geographical variation and demonstrates the potential use of health-care claims data to provide epidemiologic insights into small-area variations and trends in physical health among those with SMI.
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