Skip Navigation LinksHome > August 24, 2013 - Volume 27 - Issue 13 > Disparities in community viral load among HIV-infected perso...
AIDS:
doi: 10.1097/QAD.0b013e328360f619
Epidemiology and Social

Disparities in community viral load among HIV-infected persons in New York city

Laraque, Fabiennea,b; Mavronicolas, Heather A.b; Robertson, McKaylee M.b; Gortakowski, Heidi W.c; Terzian, Arpi S.d,e

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Abstract

Objective:

HIV infection is a major problem in New York City (NYC), with more than 100 000 living HIV-infected persons. Novel public health approaches are needed to control the epidemic. The NYC Department of Health and Mental Hygiene (DOHMH) analysed community viral load (CVL) for a baseline to monitor the population-level impact of HIV control interventions.

Design:

A cross-sectional study using routinely collected surveillance data.

Methods:

All HIV-infected persons reported to the NYC HIV Registry who were at least 13 years of age, with at least one viral load test result in 2008, and alive at the end of 31 December 2008 were included. CVL was defined as the mean of individual viral load means reported between January and December 2008. Detectable viral load was defined as an individual mean of more than 400 copies/ml. Differences in CVL and proportion undetectable were computed by socio-demographic characteristics and summary measures were mapped.

Results:

New York City CVL was 21 318 copies/ml overall (N = 62 550) and 44 749 copies/ml (N = 28 366) among persons with detectable mean viral loads. CVL varied by demographic and clinical characteristics, with statistically significant differences (P < 0.001) in all groups except race/ethnicity (P = 0.16). Men, persons aged 20–49 years, MSM, persons with AIDS, those with a CD4+ cell count of 200 cells/μl or less and persons diagnosed after 2006 had higher mean viral load. Overall, 54.7% of HIV-infected persons had a suppressed mean viral load, with individual and neighbourhood variations (P < 0.0001).

Conclusion:

This analysis showed strong disparities in reported CVL by individual characteristics and neighbourhoods. CVL patterns can be utilized to target interventions and track their impact.

© 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins

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