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Behind the Cascade: Analyzing Spatial Patterns along the HIV Care Continuum
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    Successful HIV treatment as prevention requires individuals to be tested, aware of their status, linked to and retained in care, and virally suppressed. Spatial analysis may be useful for monitoring HIV care by identifying geographic areas with poor outcomes.


    Retrospective cohort of 1,704 people newly diagnosed with HIV identified from Philadelphia’s Enhanced HIV/AIDS Reporting System in 2008–2009, with follow-up to 2011. Outcomes of interest were not linked to care, not linked to care within 90 days, not retained in care, and not virally suppressed. Spatial patterns were analyzed using K-functions to identify ‘hot spots’ for targeted intervention. Geographic components were included in regression analyses along with demographic factors to determine their impact on each outcome.


    Overall, 1,404 persons (82%) linked to care; 75% (1,059/1,404) linked within 90 days; 37% (526/1,059) were retained in care; and 72% (379/526) achieved viral suppression. 59 census tracts were in ‘hot spots’, with no overlap between outcomes. Persons residing in geographic areas identified by the local K-function analyses were more likely to not link to care (AOR 1.76 [95% CI 1.30–2.40]), not link to care within 90 days (1.49, 1.12–1.99), not be retained in care (1.84, 1.39–2.43), and not be virally suppressed (3.23, 1.87–5.59) than persons not residing in the identified areas.


    This study is the first to identify spatial patterns as a strong independent predictor of linkage to care, retention in care, and viral suppression. Spatial analyses are a valuable tool for characterizing the HIV epidemic and treatment cascade.

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    (PS13-130202/PS/NCHHSTP CDC HHS/United States
    5P30AI087714/AI/NIAID NIH HHS/United States
    K23 MH097647/MH/NIMH NIH HHS/United States
    K23-MH097647/MH/NIMH NIH HHS/United States
    P30 AI045008/AI/NIAID NIH HHS/United States
    P30-AI-45008/AI/NIAID NIH HHS/United States
    U62/003959/PHS HHS/United States
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