Objective

Unintentional drug poisoning and overdose deaths in New York City (NYC) increased 175% between 2010 and 2017, partly due to the transition from noninjectable opioids to heroin injection. This transition has led to concern of a resurgent HIV epidemic among persons who inject drugs (PWID) in NYC. Thus, we sought to characterize HIV transmission dynamics in PWID.

Design

Genetic network analysis of HIV-1 public health surveillance data.

Methods

We analyzed HIV diagnoses reported to public health surveillance to determine the trajectory of the HIV epidemic among PWID in NYC, from 1985 through 2019. Genetic distance-based clustering was performed using HIV-TRACE to reconstruct transmission patterns among PWID.

Results

The majority of the genetic links to PWID diagnosed in the 1980s and 1990s are to other PWID. However, since 2011, there has been a continued decline in new diagnoses among PWID, and genetic links between PWID have become increasingly rare, although links to noninjecting MSM and other people reporting sexual transmission risk have become increasingly common. However, we also find evidence suggestive of a resurgence of genetic links among PWID in 2018-2019. PWID who reported male-male sexual contact were not preferentially genetically linked to PWID over the surveillance period, emphasizing their distinct risk profile from other PWID.

Conclusion

These trends suggest a transition from parenteral to sexual transmission among PWID in NYC, suggesting that harm reduction, syringe exchange programs, and legalization of over-the-counter syringe sales in pharmacies have mitigated HIV risk by facilitating well tolerated injection among new PWID.

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.

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.

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.