Reducing HIV infection in people who inject drugs is impossible without targeting recently-infected subjects

Will the Russian war in Ukraine unleash larger epidemics of HIV, TB and associated conditions and diseases in Ukraine?

The Russian war in Ukraine poses many risks for the spread of HIV, TB and associated conditions, including possible increases in the numbers of people who inject drugs or engage in sex work in the years ahead. Ukrainian civil society and volunteer efforts have been able to maintain and at times expand services for HIV Key Populations. The extent of mutual-aid and volunteer efforts as well as the continued strength and vitality of harm reduction organizations such as the Alliance for Public Health and the rest of civil society will be crucial resources for postwar efforts to assist Key Populations and prevent the spread of HIV, TB and other diseases. The postwar period will pose great economic and political difficulties for Ukrainians, including large populations of people physically and/or psychically damaged and in pain who might become people who inject drugs. Local and international support for public health and for harm reduction will be needed to prevent potentially large-scale increases in infectious disease and related mortality.

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

BACKGROUND

Due to practical challenges associated with genetic sequencing in low-resource environments, the burden of hepatitis C virus (HCV) in forcibly displaced people is understudied. We examined the use of field applicable HCV sequencing methods and phylogenetic analysis to determine HCV transmission dynamics in internally displaced people who inject drugs (IDPWID) in Ukraine.

METHODS

In this cross-sectional study, we used modified respondent-driven sampling to recruit IDPWID who were displaced to Odesa, Ukraine, before 2020. We generated partial and near full length genome (NFLG) HCV sequences using Oxford Nanopore Technology (ONT) MinION in a simulated field environment. Maximum likelihood and Bayesian methods were used to establish phylodynamic relationships.

RESULTS

Between June and September 2020, we collected epidemiological data and whole blood samples from 164 IDPWID (PNAS Nexus.2023;2(3):pgad008). Rapid testing (Wondfo® One Step HCV; Wondfo® One Step HIV1/2) identified an anti-HCV seroprevalence of 67.7%, and 31.1% of participants tested positive for both anti-HCV and HIV. We generated 57 partial or NFLG HCV sequences and identified eight transmission clusters, of which at least two originated within a year and a half post-displacement.

CONCLUSIONS

Locally generated genomic data and phylogenetic analysis in rapidly changing low-resource environments, such as those faced by forcibly displaced people, can help inform effective public health strategies. For example, evidence of HCV transmission clusters originating soon after displacement highlights the importance of implementing urgent preventive interventions in ongoing situations of forced displacement.

Epidemiology and Molecular Transmission Characteristics of HIV in the Capital City of Anhui Province in China

Hefei, Anhui province, is one of the cities in the Yangtze River Delta, where many people migrate to Jiangsu, Zhejiang and Shanghai. High migration also contributes to the HIV epidemic. This study explored the HIV prevalence in Hefei to provide a reference for other provinces and assist in the prevention and control of HIV in China. A total of 816 newly reported people with HIV in Hefei from 2017 to 2020 were recruited as subjects. HIV subtypes were identified by a phylogenetic tree. The most prevalent subtypes were CRF07_BC (41.4%), CRF01_AE (38.1%) and CRF55_01B (6.3%). Molecular networks were inferred using HIV-TRACE. The largest and most active transmission cluster was CRF55_01B in Hefei’s network. A Chinese national database (50,798 sequences) was also subjected to molecular network analysis to study the relationship between patients in Hefei and other provinces. CRF55_01B and CRF07_BC-N had higher clustered and interprovincial transmission rates in the national molecular network. People with HIV in Hefei mainly transmitted the disease within the province. Finally, we displayed the epidemic trend of HIV in Hefei in recent years with the dynamic change of effective reproductive number (Re). The weighted overall Re increased rapidly from 2012 to 2015, with a peak value of 3.20 (95% BCI, 2.18–3.85). After 2015, Re began to decline and remained stable at around 1.80. In addition, the Re of CRF55_01B was calculated to be between 2.0 and 4.0 in 2018 and 2019. More attention needs to be paid to the rapid spread of CRF55_01B and CRF07_BC-N strains among people with HIV and the high Re in Hefei. These data provide necessary support to guide the targeted prevention and control of HIV.

Locally adaptive Bayesian birth-death model successfully detects slow and rapid rate shifts

Birth-death processes have given biologists a model-based framework to answer questions about changes in the birth and death rates of lineages in a phylogenetic tree. Therefore birth-death models are central to macroevolutionary as well as phylodynamic analyses. Early approaches to studying temporal variation in birth and death rates using birth-death models faced difficulties due to the restrictive choices of birth and death rate curves through time. Sufficiently flexible time-varying birth-death models are still lacking. We use a piecewise-constant birth-death model, combined with both Gaussian Markov random field (GMRF) and horseshoe Markov random field (HSMRF) prior distributions, to approximate arbitrary changes in birth rate through time. We implement these models in the widely used statistical phylogenetic software platform RevBayes, allowing us to jointly estimate birth-death process parameters, phylogeny, and nuisance parameters in a Bayesian framework. We test both GMRF-based and HSMRF-based models on a variety of simulated diversification scenarios, and then apply them to both a macroevolutionary and an epidemiological dataset. We find that both models are capable of inferring variable birth rates and correctly rejecting variable models in favor of effectively constant models. In general the HSMRF-based model has higher precision than its GMRF counterpart, with little to no loss of accuracy. Applied to a macroevolutionary dataset of the Australian gecko family Pygopodidae (where birth rates are interpretable as speciation rates), the GMRF-based model detects a slow decrease whereas the HSMRF-based model detects a rapid speciation-rate decrease in the last 12 million years. Applied to an infectious disease phylodynamic dataset of sequences from HIV subtype A in Russia and Ukraine (where birth rates are interpretable as the rate of accumulation of new infections), our models detect a strongly elevated rate of infection in the 1990s.

Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention

Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.

Social network approaches to locating people recently infected with HIV in Odessa, Ukraine

Introduction

This paper examines the extent to which an intervention succeeded in locating people who had recently become infected with HIV in the context of the large‐scale Ukrainian epidemic. Locating and intervening with people who recently became infected with HIV (people with recent infection, or PwRI) can reduce forward HIV transmission and help PwRI remain healthy.

Methods

The Transmission Reduction Intervention Project (TRIP) recruited recently‐infected and longer‐term infected seeds in Odessa, Ukraine, in 2013 to 2016, and asked them to help recruit their extended risk network members. The proportions of network members who were PwRI were compared between TRIP arms (i.e. networks of recently‐infected seeds vs. networks of longer‐term infected seeds) and to the proportion of participants who were PwRI in an RDS‐based Integrated Biobehavioral Surveillance of people who inject drugs in 2013.

Results

The networks of PwRI seeds and those of longer‐term infected seeds had similar (2%) proportions who were themselves PwRI. This was higher than the 0.25% proportion in IBBS (OR = 7.80; p = 0.016). The odds ratio among the subset of participants who injected drugs was 11.17 (p = 0.003). Cost comparison analyses using simplified ingredients‐based methods found that TRIP spent no more than US $4513 per PwRI located whereas IBBS spent $11,924.

Conclusions

Further research is needed to confirm these results and improve TRIP further, but our findings suggest that interventions that trace the networks of people who test HIV‐positive are a cost‐effective way to locate PwRI and reduce HIV transmission and should therefore be implemented.

Tracing the Impact of Public Health Interventions on HIV-1 Transmission in Portugal Using Molecular Epidemiology

BACKGROUND

Estimation of temporal changes in human immunodeficiency virus (HIV) transmission patterns can help to elucidate the impact of preventive strategies and public health policies.

METHODS

Portuguese HIV-1 subtype B and G pol genetic sequences were appended to global reference data sets to identify country-specific transmission clades. Bayesian birth-death models were used to estimate subtype-specific effective reproductive numbers (Re). Discrete trait analysis (DTA) was used to quantify mixing among transmission groups.

RESULTS

We identified 5 subtype B Portuguese clades (26-79 sequences) and a large monophyletic subtype G Portuguese clade (236 sequences). We estimated that major shifts in HIV-1 transmission occurred around 1999 (95% Bayesian credible interval [BCI], 1998-2000) and 2000 (95% BCI, 1998-2001) for subtypes B and G, respectively. For subtype B, Re dropped from 1.91 (95% BCI, 1.73-2.09) to 0.62 (95% BCI,.52-.72). For subtype G, Re decreased from 1.49 (95% BCI, 1.39-1.59) to 0.72 (95% BCI, .63-.8). The DTA suggests that people who inject drugs (PWID) and heterosexuals were the source of most (>80%) virus lineage transitions for subtypes G and B, respectively.

CONCLUSIONS

The estimated declines in Re coincide with the introduction of highly active antiretroviral therapy and the scale-up of harm reduction for PWID. Inferred transmission events across transmission groups emphasize the importance of prevention efforts for bridging populations.

Near Full-length Genomic Sequencing and Molecular Analysis of HIV-Infected Individuals in a Network-based Intervention (TRIP) in Athens, Greece: Evidence that Transmissions Occur More Frequently from those with High HIV-RNA

Background:

TRIP (Transmission Reduction Intervention Project) was a network-based, contact tracing approach to locate and link to care, mostly people who inject drugs (PWID) with recent HIV infection.

Objective:

We investigated whether sequences from HIV-infected participants with high viral load cluster together more frequently than what is expected by chance.

Methods:

Paired end reads were generated for 104 samples using Illumina MiSeq next-generation se-quencing.

Results:

63 sequences belonged to previously identified local transmission networks of PWID (LTNs) of an HIV outbreak in Athens, Greece. For two HIV-RNA cut-offs (105 and 106 IU/mL), HIV transmissions were more likely between PWID with similar levels of HIV-RNA (p<0.001). 10 of the 14 sequences (71.4%) from PWID with HIV-RNA >106 IU/mL were clustered in 5 pairs. For 4 of these clusters (80%), there was in each one of them at least one sequence from a recently HIV-infected PWID.

Conclusion:

We showed that transmissions are more likely among PWID with high viremia.

Risk network approaches to locating undiagnosed HIV cases in Odessa, Ukraine

INTRODUCTION

Providing HIV healthcare and Treatment as Prevention both depend on diagnosing HIV cases, preferably soon after initial infection. We hypothesized that tracing risk networks recruits higher proportions of undiagnosed positives than outreach-based testing or respondent-driven sampling (RDS) in Odessa, Ukraine.

METHODS

The Transmission Reduction Intervention Project (TRIP) used risk network tracing to recruit sexual and injection networks of recently-infected and longer-term infected (LTs) seeds (2013 to 2016). Integrated Biobehavioural Surveillance (IBBS) (2013) used RDS to recruit people who inject drugs (PWID). Outreach Testing tested PWID for HIV at community outreach sites (2013 to 2016). Proportions of undiagnosed positives among those tested were compared TRIP versus IBBS; TRIP versus Outreach Testing and between TRIP arms. Costs were compared across the projects.

RESULTS

TRIP tested 1252 people (21% women) in seeds' risk networks; IBBS tested 400 (18% women); Outreach Testing 13,936 (31% women). TRIP networks included a higher proportion of undiagnosed positives (14.6%) than IBBS (5.0%) or Outreach Testing (2.4%); odds ratio (OR) 3.25 (95% CI 2.07, 5.12) versus IBBS and 7.03 (CI 5.95, 8.31) versus Outreach Testing respectively. Findings remained significant in analyses stratified by sex and when PWID in TRIP networks were compared with Outreach Testing and IBBS. Within TRIP, recently-infected participants' networks contained higher proportions of undiagnosed positives (16.3%) than LTs' networks (12.2%); OR 1.41 (CI 1.01, 1.95). TRIP located undiagnosed positives less expensively than did RDS or Outreach Testing.

CONCLUSIONS

TRIP's recruiting techniques, including prioritizing networks of the recently infected, find undiagnosed HIV-positive people efficiently. They should be integrated with standard practice to improve case-finding. Research should test these techniques in other socio-epidemiologic contexts.

CLINICAL TRIAL REGISTRY

Registered ClinicalTrials.gov: NCT01827228.

Experiences of Stigma and Support Reported by Participants in a Network Intervention to Reduce HIV Transmission in Athens, Greece; Odessa, Ukraine; and Chicago, Illinois

A growing body of evidence suggests that network-based interventions to reduce HIV transmission and/or improve HIV-related health outcomes have an important place in public health efforts to move towards 90-90-90 goals. However, the social processes involved in network-based recruitment may pose a risk to participants of increasing HIV-related stigma if network recruitment causes HIV status to be assumed, inferred, or disclosed. On the other hand, the social processes involved in network-based recruitment to HIV testing may also encourage HIV-related social support. Yet despite the relevance of these processes to both network-based interventions and to other more common interventions (e.g., partner services), there is a dearth of literature that directly examines them among participants of such interventions. Furthermore, both HIV-related stigma and social support may influence participants' willingness and ability to recruit their network members to the study. This paper examines (1) the extent to which stigma and support were experienced by participants in the Transmission Reduction Intervention Project (TRIP), a risk network-tracing intervention aimed at locating recently HIV-infected and/or undiagnosed HIV-infected people and linking them to care in Athens, Greece; Odessa, Ukraine; and Chicago, Illinois; and (2) whether stigma and support predicted participant engagement in the intervention. Overall, experiences of stigma were infrequent and experiences of support frequent, with significant variation between study sites. Experiences and perceptions of HIV-related stigma did not change significantly between baseline and six-month follow-up for the full TRIP sample, and significantly decreased during the course of the study at the Chicago site. Experiences of HIV-related support significantly increased among recently-HIV-infected participants at all sites, and among all participants at the Odessa site. Both stigma and support were found to predict participants' recruitment of network members to the study at the Athens site, and to predict participants' interviewer-rated enthusiasm for naming and recruiting their network members at both the Athens and Odessa sites. These findings suggest that network-based interventions like TRIP which aim to reduce HIV transmission likely do not increase stigma-related risks to participants, and may even encourage increased social support among network members. However, the present study is limited by its associational design and by some variation in implementation by study site. Future research should directly assess contextual differences to improve understanding of the implications of site-level variation in stigma and support for the implementation of network-based interventions, given the finding that these constructs predict participants' recruitment of network members and engagement in the intervention, and thereby could limit network-based interventions' abilities to reach those most in need of HIV testing and care.

Identifying, linking, and treating people who inject drugs and were recently infected with HIV in the context of a network-based intervention

Identifying and linking people to care soon after HIV infection could limit viral transmission and protect their health. This work aims at describing the continuum of care among recently HIV-infected people who inject drugs (PWID) and participated in an intervention in the context of an HIV outbreak in Athens, Greece. The Transmission Reduction Intervention Project (TRIP) conducted risk network-based contact tracing and screened people for recent HIV infection. A comprehensive approach with a case management component that aimed to remove barriers to accessing care was adopted. Follow-up data on antiretroviral treatment (ART) and HIV-RNA levels were obtained from HIV clinics. TRIP enrolled 45 recently HIV-infected PWID (80% male) with a median viral load at recruitment of 5.43 log₁₀ copies/mL. Of the recently infected persons in TRIP, 87% were linked to care; of these, 77% started ART; and of those on ART, 89% achieved viral load <200 copies/mL. TRIP and its public health allies managed to get most of the recently HIV-infected PWID who were identified by the program into care and many of them onto ART. This resulted in very low HIV-RNA levels. Treatment as prevention can work if individuals are aided in overcoming difficulties in entry to, or attrition from care.

The Changing Epidemiological Profile of HIV-1 Subtype B Epidemic in Ukraine

While HIV-1 subtype B has caused a large epidemic in the Western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV-1 subtype B viruses circulating in Ukraine, characterized the transmission group structure, and estimated key evolutionary and epidemiological parameters. We analyzed 120 HIV-1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002 and 2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and date the most recent common ancestors of identified clades. A phylodynamic birth-death model was used to estimate the effective reproductive number (R_e) of these clades. We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV-1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV-1 subtype A into Ukraine. R_e was estimated to be 1.42 [95% highest posterior density (HPD) 1.26-1.56] for Clade 1 and 1.69 (95% HPD 1.49-1.84) for Clade 2. Evidently, the subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV-1 subtype B.

Molecular epidemiology reveals the role of war in the spread of HIV in Ukraine

Ukraine has one of the largest HIV epidemics in Europe, historically driven by people who inject drugs (PWID). The epidemic showed signs of stabilization in 2012, but the recent war in eastern Ukraine may be reigniting virus spread. We investigated the movement of HIV-infected people within Ukraine before and during the conflict. We analyzed HIV-1 subtype-A pol nucleotide sequences sampled during 2012-2015 from 427 patients of 24 regional AIDS centers and used phylogeographic analysis to reconstruct virus movement among different locations in Ukraine. We then tested for correlations between reported PWID behaviors and reconstructed patterns of virus spread. Our analyses suggest that Donetsk and Lugansk, two cities not controlled by the Ukrainian government in eastern Ukraine, were significant exporters of the virus to the rest of the country. Additional analyses showed that viral dissemination within the country changed after 2013. Spearman correlation analysis showed that incoming virus flow was correlated with the number of HIV-infected internally displaced people. Additionally, there was a correlation between more intensive virus movement and locations with a higher proportion of PWID practicing risky sexual behaviors. Our findings suggest that effective prevention responses should involve internally displaced people and people who frequently travel to war-affected regions. Scale-up of harm reduction services for PWID will be an important factor in preventing new local HIV outbreaks in Ukraine.