Phylodynamics and migration data help describe HIV transmission dynamics in internally displaced people who inject drugs in Ukraine

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 novel 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 (IDPWID). 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 show 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.

Hepatitis C Virus in people with experience of injection drug use following their displacement to Southern Ukraine before 2020

“…In both of the identified recent HCV clusters, although transmissions happened after displacement, all cluster members originated from the same home regions (Donetsk and Crimea for clusters 4 and 7, respectively), which supports previous observations of the importance of social networks from the same home community amongst forcibly displaced people [ 29 ]. Our phylogeographic analysis of HIV sequences obtained from the same study population showed that upon relocation, the host population is likely to transmit HIV infections to IDPWID [ 17 ]. Unfortunately, similar analysis of HCV sequences, or further clustering analysis between migrant, home, and host communities, was not possible due to a lack of available genetic sequence data from autochthonous populations, despite Ukraine having one of the highest HCV burdens in the world [ 5 , 20 ].…”

“…Our results suggest that HCV seroprevalence in IDPWID residing in Odesa in 2020 (67.7%) is higher than the prevalence reported in 2015 in both autochthonous PWID (47.5%) and in PWID residing in Donetsk (55.2%) [ 10 ]. This may reflect our recruitment strategy, given the enhanced coupon distribution for HIV-positive participants who were not in ART treatment at the time of enrolment [ 17 ]. Of those previously reporting a positive anti-HCV test result, 22% had also received treatment in the past (treatment regimen not reported), compared to only 9.4% receiving treatment in a 2013 study, which may be due to a recent increase in targeted HCV treatment efforts for the PWID community in the area [ 32 , 33 ].…”

“…At the same time whole blood samples were collected from all participants using the phlebotomy technique, and serum was isolated at the Odesa Regional Virology Laboratory and stored at ─80 °C. Further information on the study design and participant characteristics is described elsewhere [ 17 ].…”

“…Although MinION based HCV sequencing methods have been described previously [ 21 ], we aimed to develop an alternative protocol that meets the need for generation of near real-time sequencing data in field settings, without compromising sample integrity or losing sensitivity. Thus, all sequencing work was carried out in a simulated field environment using a “lab-in-a-suitcase” approach [ 15 , 17 ]. Further details including bioinformatic workflow, beyond the description in this section, are presented in the Supplementary Materials .…”