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.
Abstract Internally displaced persons are often excluded from HIV molecular epidemiology surveillance due to structural, behavioral, and social barriers in access to treatment. We test a field-based molecular epidemiology framework to study HIV transmission dynamics in a hard-to-reach and highly stigmatized group, internally displaced people who inject drugs (IDPWIDs). We inform the framework by Nanopore generated HIV pol sequences and IDPWID migration history. In June–September 2020, we recruited 164 IDPWID in Odesa, Ukraine, and obtained 34 HIV sequences from HIV-infected participants. We aligned them to publicly available sequences (N = 359) from Odesa and IDPWID regions of origin and identified 7 phylogenetic clusters with at least 1 IDPWID. Using times to the most recent common ancestors of the identified clusters and times of IDPWID relocation to Odesa, we infer potential post-displacement transmission window when infections likely to happen to be between 10 and 21 months, not exceeding 4 years. Phylogeographic analysis of the sequence data shows that local people in Odesa disproportionally transmit HIV to the IDPWID community. Rapid transmissions post-displacement in the IDPWID community might be associated with slow progression along the HIV continuum of care: only 63% of IDPWID were aware of their status, 40% of those were in antiviral treatment, and 43% of those were virally suppressed. Such HIV molecular epidemiology investigations are feasible in transient and hard-to-reach communities and can help indicate best times for HIV preventive interventions. Our findings highlight the need to rapidly integrate Ukrainian IDPWID into prevention and treatment services following the dramatic escalation of the war in 2022.
AbstractIntroductionMolecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention.MethodsAll new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV‐TRACE tool: Seguro HIV‐TRACE. Socio‐demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions.ResultsA total of 3168 HIV sequences from unique individuals were included. One thousand and one‐hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio‐economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub‐clusters with high growth potential.ConclusionsHIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.
During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated the development of testing methods and allowed the timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific and organizational challenges. Here, we discuss the application of genomic and computational methods for efficient data-driven COVID-19 response, the advantages of the democratization of viral sequencing around the world and the challenges associated with viral genome data collection and processing.
