Using Molecular HIV Surveillance Data to Understand Transmission Between Subpopulations in the United States

Am, Oster; Jo, Wertheim; Al, Hernández; Mc, Ocfemia; Saduvala, Neeraja; Hi, Hall

doi:10.1097/qai.0000000000000809

Cited by 138 publications

(151 citation statements)

References 23 publications

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“…[28][29][30][31] Transmission clusters can provide insight into shifts in social and structural dynamics influencing transmission over time and the role of social distance and other structural influences on transmission, independent of participant-reported history. 32 There is great potential for using these data to help identify segments of the population at highest risk for incident HIV infection, which can inform the mechanisms, upper limits of reach, and targeting for network-based HIV testing and care interventions, PrEP, and other social and behavioral intervention.…”

Section: Identifying Transmission Clustersmentioning

confidence: 99%

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Rose¹,

Lamers²,

Dollar³

et al. 2017

AIDS Research and Human Retroviruses

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We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

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Section: Identifying Transmission Clustersmentioning

confidence: 99%

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Rose¹,

Lamers²,

Dollar³

et al. 2017

AIDS Research and Human Retroviruses

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“…A similar pattern for sexual partnership between ethnic groups was reported in Britain [8]. Although we found a relatively higher assortativity among black MSM in general and a non negligible mixing between black ethnic groups from different origins (African, Caribbean and other), HIV transmission seems less assortative 285 among black MSM in the UK than it is in the USA [26].…”

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confidence: 41%

Mixing patterns of HIV transmission among men who have sex with men in the United Kingdom

Ratmann

Delpech

et al. 2018

Preprint

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Background: Near 60% of new HIV infections in the United Kingdom are estimated to occur in men who have sex with men (MSM). Patterns of mixing between different risk groups of MSM have been suggested to spread the HIV epidemics through age-disassortative partnerships and to contribute to ethnic disparities in infection rates. Understanding these mixing patterns in transmission can help to determine which groups are at a greater risk and guide prevention.Methods: We analyzed combined epidemiologic data and viral sequences from MSM diagnosed with HIV as of mid-2015 at the national level. We applied a phylodynamic source attribution model to infer patterns of transmission between groups of patients by age, ethnicity and region.Results: From pair probabilities of transmission between 19 847 MSM patients, we found that potential transmitters of HIV subtype B were on average 5 months older than recipients. We also found a moderate overall assortativity of transmission by ethnic group and a stronger assortativity by region.Conclusions: Our findings suggest that there is only a modest net flow of transmissions from older to young MSM in subtype B epidemics and that young MSM, both for Black or White groups, are more likely to be infected by one another than expected in a sexual network with random mixing.

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“…We found that, as has been documented for HIV transmission overall in the United States [21], HIV transmission among MSM was highly assortative by race/ethnicity. Racial/ethnicassortative mixing was especially evident for black/African American MSM.…”

Section: Discussionmentioning

confidence: 63%

“…We used a local version of HIV-TRACE (hivtrace.org), following the protocol outlined by Wertheim et al [18,21] for transmission network construction. Each sequence was aligned to an HIV reference sequence (HXB2, positions 2253 to 2869).…”

Section: Transmission Network Analysismentioning

confidence: 99%

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Molecular analysis allows inference into HIV transmission among young men who have sex with men in the United States

2017

Aids

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Objective-To understand the spread of HIV among and between age and racial/ethnic groups of men who engage in male-to-male sexual contact (men who have sex with men, MSM) in the United States. Methods-Pairwise genetic distance was calculated to determine potential transmission partners (those with very closely related nucleotide sequences, i.e., distance ≤1.5%). We described race/ ethnicity and age of potential transmission partners of MSM. Design-AnalysisResults-Of 23,048 MSM with HIV sequences submitted to NHSS during 2000-2012, we identified potential transmission partners for 8,880 (39%). Most potential transmission partners were of the same race/ethnicity (78% for blacks/African Americans, 64% for whites, and 49% for Hispanics/Latinos). This assortative mixing was even more pronounced in the youngest age groups. Significantly fewer young black/African American and Hispanic/Latino MSM had older potential transmission partners compared with young white MSM. Conclusion-Black/AfricanAmerican MSM, who are more profoundly affected by HIV, were more likely to have potential HIV transmission partners who were of the same race/ethnicity and similar in age, suggesting that disparities in HIV infections are in large part not due to agedisassortative relationships. Concerted efforts to increase access to pre-exposure prophylaxis, quality HIV care, and effective treatment are needed to interrupt transmission chains among young, black/African American MSM.

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Using Molecular HIV Surveillance Data to Understand Transmission Between Subpopulations in the United States

Cited by 138 publications

References 23 publications

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Mixing patterns of HIV transmission among men who have sex with men in the United Kingdom

Molecular analysis allows inference into HIV transmission among young men who have sex with men in the United States

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