Ten Years of Screening and Testing for Acute HIV Infection in North Carolina.

OBJECTIVE: To describe demographic and behavioral characteristics of persons with acute HIV infection (AHI) over time. METHODS: We conducted a retrospective assessment of AHI identified through the Screening and Tracing Active Transmission (STAT) program from 2003 to 2012 in North Carolina (NC). AHI was identified using pooled nucleic acid amplification for antibody negative samples and individual HIV-1 RNA for antibody indeterminate samples. The STAT program provides rapid notification and evaluation. We compared STAT-collected demographic and risk characteristics with all persons requesting tests and all non-AHI diagnoses from the NC State Laboratory of Public Health. RESULTS: The STAT Program identified 236 AHI cases representing 3.4% (95% confidence interval: 3.0% to 3.9%) of all HIV diagnoses. AHI cases were similar to those diagnosed during established HIV. On pretest risk-assessments, AHI cases were predominately black (69.1%), male (80.1%), young (46.8% < 25 years), and men who have sex with men (MSM) (51.7%). Per postdiagnosis interviews, the median age decreased from 35 (interquartile range 25-42) to 27 (interquartile range 22-37) years, and the proportion <25 years increased from 23.8% to 45.2% (trend P = 0.04) between 2003 and 2012. AHI men were more likely to report MSM risk post-diagnosis than on pretest risk-assessments (64%-82.9%; P < 0.0001). Post-diagnosis report of MSM risk in men with AHI increased from 71.4% to 96.2%. CONCLUSIONS: In NC, 3.4% of individuals diagnosed with HIV infection have AHI. AHI screening provides a real-time source of incidence trends, improves the diagnostic yield of HIV testing, and offers an opportunity to limit onward transmission.

Investigating a sexual network of black men who have sex with men: implications for transmission and prevention of HIV infection in the United States.

BACKGROUND: HIV infections increased 48% among young Black men who have sex with men (MSM) in the United States between 2006 and 2009. Incomplete understanding of this trend undermines prevention strategy development. We investigated a sexual network to characterize the risk environment in which young Black MSM acquire HIV. METHODS: Persons reported to the state after diagnosis of HIV or syphilis were included, along with sexual partners. We used network mapping alongside descriptive and bivariate statistics to characterize network connections. Generalized linear models assessed predictors of having untraceable sex partners. RESULTS: The network included 398 individuals and 419 sexual relationships. Three-quarters were Black (n = 299); 92% were MSM. Median age at first network appearance was 26 years and decreased over time (P < 0.001). HIV prevalence was at least 29% (n = 117); serostatus was unknown for 47% of the network, either because they were untraceable (n = 150) or refused HIV testing (n = 39). One in 5 network members diagnosed with HIV had a subsequent incident sexually transmitted infection. In multivariable models, one-time encounters increased the risk of having an untraceable partner (risk ratio = 4.51, 95% CI: 2.27 to 8.97), whereas being acutely HIV infected at diagnosis reduced it (risk ratio = 0.27, 95% CI: 0.08 to 0.89). CONCLUSIONS: HIV prevalence in this sexual network of young Black MSM rivals that of sub-Saharan Africa, reflecting dramatically increased risk of acquiring HIV from the moment one entered the network. Prevention efforts for this population must consider the effect of sexual networks on HIV risk and find ways of leveraging network structure to reduce transmission.

Estimating populations of men who have sex with men in the southern United States.

Population estimates of men who have sex with men (MSM) by state and race/ethnicity are lacking, hampering effective HIV epidemic monitoring and targeting of outreach and prevention efforts. We created three models to estimate the proportion and number of adult males who are MSM in 17 southern states. Model A used state-specific census data stratified by rural/suburban/urban area and national estimates of the percentage MSM in corresponding areas. Model B used a national estimate of the percentage MSM and state-specific household census data. Model C partitioned the statewide estimates by race/ethnicity. Statewide Models A and B estimates of the percentages MSM were strongly correlated (r = 0.74; r-squared = 0.55; p < 0.001) and had similar means (5.82% and 5.88%, respectively) and medians (5.5% and 5.2%, respectively). The estimated percentage MSM in the South was 6.0% (range 3.6-13.2%; median, 5.4%). The combined estimated number of MSM was 2.4 million, including 1,656,500 (69%) whites, 339,400 (14%) blacks, 368,800 (15%) Hispanics, 34,600 (1.4%) Asian/Pacific Islanders, 7,700 (0.3%) American Indians/Alaska Natives, and 11,000 (0.5%) others. The estimates showed considerable variability in state-specific racial/ethnic percentages MSM. MSM population estimates enable better assessment of community vulnerability, HIV/AIDS surveillance, and allocation of resources. Data availability and computational ease of our models suggest other states could similarly estimate their MSM populations.