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J Acquir Immune Defic Syndr. 2017 Feb 1;74 Suppl 2:S88-S95. doi: 10.1097/QAI.0000000000001234.

Longitudinal HIV Care Trajectories in North Carolina.

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*Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC; †Communicable Disease Branch, Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC; ‡Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC; §Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC; and ‖Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH.



Long-term HIV care and treatment engagement is required for maximal clinical and prevention benefits, but longitudinal care patterns are poorly understood. We used the last 10 years' worth of HIV surveillance data from North Carolina to describe longitudinal HIV care trajectories from diagnosis.


We conducted a retrospective, population-based cohort study of all persons newly diagnosed with HIV in North Carolina between March 31, 2006 and March 31, 2015 (N = 16,207). We defined HIV care attendance in each 3-month and 6-month interval after diagnosis as the presence of viral load and/or CD4 records (care visit proxies) in the interval. We used group-based trajectory modeling to identify common care trajectories and baseline predictors thereof.


A predicted 26% of newly HIV-diagnosed persons showed consistently high care attendance over time; ∼16% exhibited steadily declining attendance; ∼26% showed consistently low attendance; ∼17% had initially weak attendance with an increase starting ∼1.5 year later; and ∼15% showed initially weak attendance with an increase starting ∼3 years later. Older age at diagnosis was protective against all suboptimal trajectories (with the "consistently high" pattern as referent), and being a man who has sex with men was protective against 3 of the 4 suboptimal patterns.


As measured by surveillance-based laboratory proxies, most newly HIV-diagnosed persons exhibited suboptimal care trajectories, but there was wide variation in the particular pathways followed. The insights provided by this analytical approach can help to inform the design of epidemic models and tailored interventions, with the ultimate goal of improving HIV care engagement and transmission prevention.

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