Objective

The objective of this study is to understand the spread of HIV among and between age and racial/ethnic groups of men who engage in male-to-male sexual contact (MSM) in the United States.

Design

An analysis of HIV-1 pol sequences for MSM collected through the US National HIV Surveillance System (NHSS) during 2001-2012.

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.

Results

Of 23 048 MSM with HIV sequences submitted to NHSS during 2000-2012, we identified potential transmission partners for 8880 (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 than young white MSM.

Conclusion

Black/African-American 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 age-disassortative relationships. Concerted efforts to increase access to preexposure prophylaxis, quality HIV care and effective treatment are needed to interrupt transmission chains among young, black/African-American MSM.

Objective

To identify correlates of incident HIV infection in rapidly growing HIV molecular clusters.

Design

Phylogenetic analysis of HIV public health surveillance data.

Methods

High-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period.

Results

Of the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster.

Conclusion

These findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

Background

In the United States (US), foreign-born persons are disproportionately affected by HIV and differ epidemiologically from US-born persons with diagnosed HIV infection. Understanding HIV transmission dynamics among foreign-born persons is important to guide HIV prevention efforts for these populations. We conducted molecular transmission network analysis to describe HIV transmission dynamics among foreign-born persons with diagnosed HIV.

Methods

Using HIV-1 polymerase nucleotide sequences reported to the US National HIV Surveillance System for persons with diagnosed HIV infection during 2001-2013, we constructed a genetic distance-based transmission network using HIV-TRACE and examined the birth region of potential transmission partners in this network.

Results

Of 77,686 people, 12,064 (16%) were foreign born. Overall, 28% of foreign-born persons linked to at least one other person in the transmission network. Of potential transmission partners, 62% were born in the United States, 31% were born in the same region as the foreign-born person, and 7% were born in another region of the world. Most transmission partners of male foreign-born persons (63%) were born in the United States, whereas most transmission partners of female foreign-borns (57%) were born in their same world region.

Discussion

These finding suggests that a majority of HIV infections among foreign-born persons in our network occurred after immigrating to the United States. Efforts to prevent HIV infection among foreign-born persons in the United States should include information of the transmission networks in which these individuals acquire or transmit HIV to develop more targeted HIV prevention interventions.

Background

Studying HIV transmission networks provides insight into the spread of HIV and opportunities for intervention. We identified transmission dynamics among risk groups and racial/ethnic groups in the United States.

Methods

For HIV-1 pol sequences reported to the US National HIV Surveillance System during 2001-2012, we calculated pairwise genetic distance, identified linked pairs of sequences (those with distance ≤1.5%), and examined transmission category and race/ethnicity of these potential transmission partners.

Results

Of 40,950 sequences, 12,910 (32%) were linked to ≥1 other sequence. Of men who have sex with men (MSM) who were linked to ≥1 sequence, 88% were linked to other MSM and only 4% were linked to heterosexual women. Of heterosexual women for whom we identified potential transmission partners, 29% were linked to MSM, 21% to heterosexual men, and 12% to persons who inject drugs. Older and black MSM were more likely to be linked to heterosexual women. Assortative mixing was present for all racial/ethnic groups; 81% of blacks/African Americans linked to other blacks.

Conclusions

This analysis is the first use of US surveillance data to infer an HIV transmission network. Our data suggest that HIV infections among heterosexual women predominantly originate from MSM, followed by heterosexual men. Although few MSM were linked to women, suggesting that a minority of MSM are involved in transmission with heterosexual women, these transmissions represent a substantial proportion of HIV acquisitions by heterosexual women. Interventions that reduce transmissions involving MSM are likely to also reduce HIV acquisition among other risk groups.

The majority of HIV infections in the United States can be traced back to a single introduction in late 1960s or early 1970s. However, it remains unclear whether subsequent introductions of HIV into the United States have given rise to onward transmission. Genetic transmission networks can aid in understanding HIV transmission. We constructed a genetic distance-based transmission network using HIV-1 pol sequences reported to the U.S. National HIV Surveillance System (n = 41,539) and all publicly available non-U.S. HIV-1 pol sequences (n = 86,215). Of the 13,145 U.S. persons clustered in the network, 457 (3.5%) were genetically linked to a potential transmission partner outside the United States. For internationally connected persons residing in but born outside the United States, 61% had a connection to their country of birth or to another country that shared a language with their country of birth. Bayesian molecular clock phylogenetic analyses indicate that introduced nonsubtype B infections have resulted in onward transmission within the United States.

Public health interviews (i.e., partner services), during which persons with diagnosed human immunodeficiency virus (HIV) infection name their sexual or needle-sharing partners (named partners), are used to identify HIV transmission networks to guide and prioritize HIV prevention activities. HIV sequence data, generated from provider-ordered drug resistance testing, can be used to understand characteristics of molecular clusters, a group of sequences for which each sequence is highly similar (linked) to all other sequences, and assess whether named partners are plausible HIV transmission partners. Although molecular data in higher HIV-morbidity states have been analyzed (1-3), few analyses exist for lower morbidity states (4), such as Wisconsin, which reported 4.6 HIV diagnoses per 100,000 persons aged ≥13 years in 2016 (5). The Wisconsin Division of Public Health (DPH) analyzed HIV sequence data generated from provider-ordered drug resistance testing and collected through routine HIV surveillance to identify molecular clusters and describe demographic and transmission risk characteristics among pairs of persons whose sequences were highly genetically similar (i.e., molecular linkages). In addition, overlap between partner linkages identified during public health interviews and molecular linkages was assessed. Overall, characteristics of molecular clusters in Wisconsin mirrored those from states with more HIV diagnoses, particularly in that most molecular linkages were observed among persons of the same race (78.2% of non-Hispanic blacks [blacks] linked to other blacks), the same transmission risk (90.2% of men who have sex with men [MSM] linked to other MSM), and the same age group (59.2% of persons aged 20-29 years linked to other persons aged 20-29 years). Among named partner linkages identified during interviews in which both persons also had a reported sequence, overlap of named partner and molecular linkages was moderate: 33.8% of named partners were plausible transmission partners according to available molecular data. Analysis of HIV sequence data is a useful tool for characterizing transmission patterns not immediately apparent using traditional public health interview data, even in a state with lower HIV morbidity. Prevention recommendations generated from national data (e.g., targeting preexposure prophylaxis for HIV-negative persons at high risk and implementing measures to maintain viral suppression among persons with HIV infection) also are relevant in a lower HIV-morbidity state.

Understanding genetic variation in human immunodeficiency virus (HIV) is clinically and immunologically important for patient treatment and vaccine development. We investigated the longitudinal intra-host genetic variation of HIV in over 3,000 individuals in the US National HIV Surveillance System with at least four reported HIV-1 polymerase (pol) sequences. In this population, we identified 149 putative instances of superinfection (i.e. an individual sequentially infected with genetically divergent, polyphyletic viruses). Unexpectedly, we discovered a group of 240 individuals with consecutively sampled viral strains that were >0.015 substitutions/site divergent, despite remaining monophyletic in the phylogeny. Viruses in some of these individuals had a maximum genetic divergence approaching that found between two random, unrelated HIV-1 subtype-B pol sequences within the US population. Individuals with these highly divergent viruses tended to be diagnosed nearly a decade earlier in the epidemic than people with superinfection or virus with less intra-host genetic variation, and they had distinct transmission risk factor profiles. To better understand this genetic variation in cases with extremely divergent, monophyletic viruses, we performed molecular clock phylogenetic analysis. Our findings suggest that, like Hepatitis C virus, extremely divergent HIV lineages can be maintained within an individual and reemerge over a period of years.

Background

Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States.

Methods

We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using 2 genetic distance thresholds (0.5% and 1.5%) and 2 periods for diagnoses (all years and 2013-2015, ie, recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies.

Results

A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5-13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years.

Conclusions

Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

Test-and-treat programs are central to the global control of HIV, but transmitted drug resistance threatens the effectiveness of these programs. HIV mutations conferring resistance to antiretroviral drugs reduce replicative fitness in vitro, but their effect on propagation in vivo is less understood. Here, we estimate transmission fitness of these mutations in antiretroviral-naïve populations in the U.S. National HIV Surveillance System by comparing their frequency of clustering in a genetic transmission network relative with wild-type viruses. The large dataset (66,221 persons), comprising 30,196 antiretroviral-naïve persons, permitted the evaluation of sixty-nine resistance mutations. Decreased transmission fitness was demonstrated for twenty-three mutations, including M184V. In contrast, many high prevalence mutations (e.g. K103N, Y181C, and L90M) had transmission fitness that was indistinguishable from or exceeded wild-type fitness, permitting the establishment of large, self-sustaining drug resistance reservoirs. We highlight implications of these findings on strategies to preserve global treatment effectiveness.

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.