Sorting by Race/Ethnicity Across HIV Genetic Transmission Networks in Three Major Metropolitan Areas in the United States.

An important component underlying the disparity in HIV risk between race/ethnic groups is the preferential transmission between individuals in the same group. We sought to quantify transmission between different race/ethnicity groups and measure racial assortativity in HIV transmission networks in major metropolitan areas in the United States. We reconstructed HIV molecular transmission networks from viral sequences collected as part of HIV surveillance in New York City, Los Angeles County, and Cook County, Illinois. We calculated assortativity (the tendency for individuals to link to others with similar characteristics) across the network for three candidate characteristics: transmission risk, age at diagnosis, and race/ethnicity. We then compared assortativity between race/ethnicity groups. Finally, for each race/ethnicity pair, we performed network permutations to test whether the number of links observed differed from that expected if individuals were sorting at random. Transmission networks in all three jurisdictions were more assortative by race/ethnicity than by transmission risk or age at diagnosis. Despite the different race/ethnicity proportions in each metropolitan area and lower proportions of clustering among African Americans than other race/ethnicities, African Americans were the group most likely to have transmission partners of the same race/ethnicity. This high level of assortativity should be considered in the design of HIV intervention and prevention strategies.

Estimating the probability of diagnosis within 1 year of HIV acquisition.

BACKGROUND: Early diagnosis of HIV is important for the prevention of ongoing transmission and development of HIV-related illness. The purpose of this study is to develop an outcome indicator to monitor the progress in early HIV diagnosis. METHODS: Persons diagnosed with HIV in New York City and their first CD4 test results were used to estimate the distribution of HIV diagnosis delay, based on a CD4 count depletion model. The distribution was then used to estimate the probability of diagnosis within 1 year of HIV acquisition, which is the number of cases diagnosed in a given calendar year for which diagnosis occurred within 1 year of acquisition divided by the number of incident cases in that calendar year. RESULTS: In 2012-2016, the estimated annual probability of diagnosis within 1 year of HIV acquisition in New York City was 43.0% [95% confidence interval (CI): 37.9-48.2%), 42.5% (95% CI: 36.8--48.3%), 42.8% (95% CI: 36.3--49.2%), 42.9% (95% CI: 35.4--50.3%), and 42.2% (95% CI: 33.1--51.2%), respectively. CONCLUSION: National and local health jurisdictions should consider using this new outcome indicator, the probability of diagnosis within 1 year of HIV acquisition, to monitor their progress in early HIV diagnosis.

Growth of HIV-1 Molecular Transmission Clusters in New York City.

Background: HIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments. Methods: We investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year. Results: Individual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions. Conclusions: Prevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.

Undiagnosed HIV and HCV Infection in a New York City Emergency Department, 2015.

OBJECTIVES: To measure undiagnosed HIV and HCV in a New York City emergency department (ED). METHODS: We conducted a blinded cross-sectional serosurvey with remnant serum from specimens originally drawn for clinical indications in the ED. Serum was deduplicated and matched to (1) the hospital's electronic medical record and (2) the New York City HIV and HCV surveillance registries for evidence of previous diagnosis before being deidentified and tested for HIV and HCV. RESULTS: The overall prevalence of HIV was 5.0% (250/4990; 95% confidence interval [CI] = 4.4%, 5.7%); the prevalence of undiagnosed HIV was 0.2% (12/4990; 95% CI = 0.1%, 0.4%); and the proportion of undiagnosed HIV was 4.8% (12/250; 95% CI = 2.5%, 8.2%). The overall prevalence of HCV (HCV RNA ≥ 15 international units per milliliter) was 3.9% (196/4989; 95% CI = 2.8%, 5.1%); the prevalence of undiagnosed HCV was 0.8% (38/4989; 95% CI = 0.3%, 1.3%); and the proportion of undiagnosed HCV was 19.2% (38/196; 95% CI = 11.4%, 27.0%). CONCLUSIONS: Undiagnosed HCV was more prevalent than undiagnosed HIV in this population, suggesting that aggressive testing initiatives similar to those directed toward HIV should be mounted to improve HCV diagnosis.

Social and Genetic Networks of HIV-1 Transmission in New York City.

BACKGROUND: Sexually transmitted infections spread across contact networks. Partner elicitation and notification are commonly used public health tools to identify, notify, and offer testing to persons linked in these contact networks. For HIV-1, a rapidly evolving pathogen with low per-contact transmission rates, viral genetic sequences are an additional source of data that can be used to infer or refine transmission networks. METHODS AND FINDINGS: The New York City Department of Health and Mental Hygiene interviews individuals newly diagnosed with HIV and elicits names of sexual and injection drug using partners. By law, the Department of Health also receives HIV sequences when these individuals enter healthcare and their physicians order resistance testing. Our study used both HIV sequence and partner naming data from 1342 HIV-infected persons in New York City between 2006 and 2012 to infer and compare sexual/drug-use named partner and genetic transmission networks. Using these networks, we determined a range of genetic distance thresholds suitable for identifying potential transmission partners. In 48% of cases, named partners were infected with genetically closely related viruses, compatible with but not necessarily representing or implying, direct transmission. Partner pairs linked through the genetic similarity of their HIV sequences were also linked by naming in 53% of cases. Persons who reported high-risk heterosexual contact were more likely to name at least one partner with a genetically similar virus than those reporting their risk as injection drug use or men who have sex with men. CONCLUSIONS: We analyzed an unprecedentedly large and detailed partner tracing and HIV sequence dataset and determined an empirically justified range of genetic distance thresholds for identifying potential transmission partners. We conclude that genetic linkage provides more reliable evidence for identifying potential transmission partners than partner naming, highlighting the importance and complementarity of both epidemiological and molecular genetic surveillance for characterizing regional HIV-1 epidemics.

Estimated HIV Incidence in the United States, 2003-2010.

OBJECTIVE: To estimate HIV incidence in the United States using a newly developed method. METHODS: The analysis period (2002-2011) was broken down into 3-year periods with overlaps, and HIV incidence was estimated based on the relationship between number of new diagnoses and HIV incidence in each of these 3-year periods, by assuming that all HIV infections would eventually be diagnosed and within each 3-year period HIV incidence and case finding were stable. RESULTS: The estimated HIV incidence in the United States decreased from 52,721 (range: 47,449-57,993) in 2003 to 39,651 (range: 35,686-43,617) in 2010, among males from 38,164 (range: 35,051-42,840) to 33,035 (range: 29,088-35,553), and among females from 13,557 (range: 12,133-14,830) to 6616 (range: 5825 to 7120). CONCLUSIONS: Using a simple and novel method based on the number of new HIV diagnoses, we were able to estimate HIV incidence and report a declining trend in HIV incidence in the United States since 2003.

Transmitted antiretroviral drug resistance in New York State, 2006-2008: results from a new surveillance system.

BACKGROUND: HIV transmitted drug resistance (TDR) is a public health concern because it has the potential to compromise antiretroviral therapy (ART) at the population level. In New York State, high prevalence of TDR in a local cohort and a multiclass resistant case cluster led to the development and implementation of a statewide resistance surveillance system. METHODOLOGY: We conducted a cross-sectional analysis of the 13,109 cases of HIV infection that were newly diagnosed and reported in New York State between 2006 and 2008, including 4,155 with HIV genotypes drawn within 3 months of initial diagnosis and electronically reported to the new resistance surveillance system. We assessed compliance with DHHS recommendations for genotypic resistance testing and estimated TDR among new HIV diagnoses. PRINCIPAL FINDINGS: Of 13,109 new HIV diagnoses, 9,785 (75%) had laboratory evidence of utilization of HIV-related medical care, and 4,155 (43%) had a genotype performed within 3 months of initial diagnosis. Of these, 11.2% (95% confidence interval [CI], 10.2%-12.1%) had any evidence of TDR. The proportion with mutations associated with any antiretroviral agent in the NNRTI, NRTI or PI class was 6.3% (5.5%-7.0%), 4.3% (3.6%-4.9%) and 2.9% (2.4%-3.4%), respectively. Multiclass resistance was observed in <1%. TDR did not increase significantly over time (p for trend = 0.204). Men who have sex with men were not more likely to have TDR than persons with heterosexual risk factor (OR 1.0 (0.77-1.30)). TDR to EFV+TDF+FTC and LPV/r+TDF+FTC regimens was 7.1% (6.3%-7.9%) and 1.4% (1.0%-1.8%), respectively. CONCLUSIONS/SIGNIFICANCE: TDR appears to be evenly distributed and stable among new HIV diagnoses in New York State; multiclass TDR is rare. Less than half of new diagnoses initiating care received a genotype per DHHS guidelines.

Comparison of Multispot EIA with Western blot for confirmatory serodiagnosis of HIV.

BACKGROUND: Recent improvements in the sensitivity of immunoassays (IA) used for HIV screening, coupled with increasing recognition of the importance of rapid point-of-care testing, have led to proposals to adjust the algorithm for serodiagnosis of HIV so that screening and confirmation can be performed using a dual or triple IA sequence that does not require Western blotting for confirmation. One IA that has been proposed as a second or confirmatory test is the Bio-Rad Multispot(®) Rapid HIV-1/HIV-2 Test. This test would have the added advantage of differentiating between HIV-1 and HIV-2 antibodies. OBJECTIVE: To compare the sensitivity and type-specificity of an algorithm combining a 3rd generation enzyme immunoassay (EIA) followed by a confirmatory Multispot with the conventional algorithm that combines a 3rd generation EIA (Bio-Rad GS HIV-1/HIV-2 Plus O EIA) followed by confirmatory Western blot (Bio-Rad GS HIV-1 WB). METHODS: 8760 serum specimens submitted for HIV testing to the New York City Public Health Laboratory between May 22, 2007, and April 30, 2010, tested repeatedly positive on 3rd generation HIV-1-2+O EIA screening and received parallel confirmatory testing by WB and Multispot (MS). RESULTS: 8678/8760 (99.1%) specimens tested WB-positive; 82 (0.9%) tested WB-negative or indeterminate (IND). 8690/8760 specimens (99.2%) tested MS-positive, of which 14 (17.1%) had been classified as negative or IND by WB. Among the HIV-1 WB-positive specimens, MS classified 26 (0.29%) as HIV-2. Among the HIV-1 WB negative and IND, MS detected 12 HIV-2. CONCLUSION: MS detected an additional 14 HIV-1 infections among WB negative or IND specimens, differentiated 26 HIV-1 WB positives as HIV-2, and detected 12 additional HIV-2 infections among WB negative/IND. A dual 3rd generation EIA algorithm incorporating MS had equivalent HIV-1 sensitivity to the 3rd generation EIA-WB algorithm and had the added advantage of detecting 12 HIV-2 specimens that were not HIV-1 WB cross-reactors. In this series an algorithm using EIA followed by MS would have resulted in the expedited referral of 38 specimens for HIV-2 testing and 40 specimens for nucleic acid confirmation. Further testing using a combined gold standard of nucleic acid detection and WB is needed to calculate specificity and validate the substitution of MS for WB in the diagnostic algorithm used by a large public health laboratory.

HIV type 2 in New York City, 2000-2008.

BACKGROUND: Antibody cross-reactivity complicates differential diagnosis of human immunodeficiency virus (HIV) type 2 (HIV-2) using standard serologic screening and confirmatory tests for HIV. HIV type 1 (HIV-1) viral load testing does not detect HIV-2. Although HIV-2 is, in general, less pathogenic than HIV-1, it can lead to immunosuppression and clinical AIDS, and there are important differences in the selection of antiretroviral therapy for HIV-2-related immunosuppression that make it imperative to differentiate between the 2 viruses. The New York City Department of Health (New York, NY) seeks to facilitate accurate diagnosis and surveillance of HIV-2 infection in the city. METHODS: We used routine HIV-1-2+O screening and a comprehensive algorithm to differentiate between HIV-1 and HIV-2 infection, universal HIV-related laboratory test reporting, population-based surveillance of HIV infection, and active communication with clinicians. RESULTS: Between 1 June 2000 and 31 December 2008, 62 persons received a diagnosis of confirmed or probable HIV-2 infection. The majority (60 [96.8%] of 62 individuals) were foreign-born (96.7% were born in Africa) and of black race/ethnicity (93.5%). At the time of initial diagnosis, 17.7% of patients with HIV-2 infection had AIDS. Forty (64.5%) of the patients received an initial diagnosis of HIV-1 infection. Among these patients, the median lag between initial diagnosis of HIV-1 infection and identification of HIV-2 as the infecting organism was 487.5 days. CONCLUSION: HIV-2 should be ruled out in persons presenting for HIV testing who originate in or travel to West Africa and other areas in which HIV-2 is endemic, particularly those who have negative or indeterminate results on HIV-1 Western blot testing or have atypical banding patterns and/or present with clinical signs of HIV infection or unexplained immunosuppression.