HIV-1 transmission dynamics among people who inject drugs on the US/Mexico border during the COVID-19 pandemic: a prosepective cohort study.

Background: We examined HIV prevalence and transmission dynamics among people who inject drugs in the U.S./Mexico border region during the COVID-19 pandemic. Methods: People who inject drugs aged ≥18 years from 3 groups were recruited: people who inject drugs who live in San Diego (SD) and engaged in cross-border drug use in Tijuana, Mexico (SD CBDUs), and people who inject drugs in SD and Tijuana (TJ) who did not engage in cross-border drug use (NCBDUs). We computed HIV prevalence at baseline and bivariate incidence-density rates (IR) at 18-month follow-up. Bayesian phylogenetic analysis was used to identify local transmission clusters, estimate their age, and effective reproductive number (Re) over time within the clusters. Findings: At baseline (n = 612), 26% of participants were female, 9% engaged in sex work, and HIV prevalence was 8% (4% SD CBDU, 4% SD NCBDU, 16% TJ NCBDU). Nine HIV seroconversions occurred over 18 months, IR: 1.357 per 100 person-years (95% CI: 0.470, 2.243); 7 in TJ NCBDU and 2 in SD CBDU. Out of 16 identified phylogenetic clusters, 9 (56%) had sequences from both the U.S. and Mexico (mixed-country). The age of three youngest mixed-country dyads (2018-2021) overlapped with the COVID-related US-Mexico border closure in 2020. One large mixed-country cluster (N = 15) continued to grow during the border closure (Re = 4.8, 95% Highest Posterior Density (HPD) 1.5-9.1) with 47% engaging in sex work. Interpretation: Amidst the COVID-19 pandemic and the border closure, cross-border HIV clusters grew. Efforts to end the HIV epidemic in the U.S. should take into account cross-border HIV-1 transmission from Tijuana. Mobile harm reduction services and coordination with municipal HIV programs to initiate anti-retroviral therapy and pre-exposure prophylaxisis are needed to reduce transmission. Funding: This research was supported by the James B. Pendleton Charitable Trust and the San Diego Center for AIDS Research.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models.

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

The Effect of Immunoglobulin G on the Humoral Immunity in Patients with Tuberculosis/HIV Coinfection.

Previously, an increase in clinical effectiveness of the antituberculosis treatment (ATT) and antiretroviral therapy (ART) in case of additional immunoglobulin G (IgG) administration in patients with multidrug-resistant tuberculosis (MDR-TB)/HIV coinfection was reported. The aim of this study was to investigate the impact of IgG administration in addition to the standard second-line ATT and ART on the humoral immunity status in patients with MDR-TB/HIV coinfection immune deficiency. The study involved 52 patients living with HIV with MDR-TB coinfection and CD4+ lymphocyte cell count below 50 cells/µCL. Patients in the control group and intervention group received the second-line ATT and ART; in addition, patients in the intervention group received IgG intravenously. The humoral immunity status was evaluated by measurement of IgA, IgE, IgG, and IgM in plasma. The standard ATT and ART resulted in a two-step change in humoral immunity: IgM, IgG, IgA, and IgE levels gradually increased to a maximal level at the 5-month mark and started to gradually decrease after the 8-month mark. Addition of IgG to the standard therapy resulted in a steeper decrease in the immunoglobulin level in serum, especially IgG, compared with standard therapy alone, allowing for an earlier initiation of ART in patients in the intervention group.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models.

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

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.

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2.

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just ~1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

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

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.

Network-level HIV risk norms are associated with individual-level HIV risk and harm reduction behaviors among people who inject drugs: a latent profile analysis.

The COVID-19 related U.S.-Mexico border-crossing restrictions disrupted social networks and HIV harm reduction services among people who inject drugs (PWID) in San Diego and Tijuana. We assessed associations of descriptive network norms on PWID's HIV vulnerability during this period. Between 10/2020 and 10/2021, 399 PWID completed a behavioral and egocentric questionnaire. We used Latent Profile Analysis to categorize PWID into network norm risk profiles based on proportions of their network (n = 924 drug use alters) who injected drugs and engaged in cross-border drug use (CBDU), among other vulnerabilities. We used logistic and linear regressions to assess network profile associations with individual-level index of HIV vulnerability and harm reduction behaviors. Fit indices specified a 4-latent profile solution of descriptive network risk norms: lower (n = 178), moderate with (n = 34) and without (n = 94) CBDU and obtainment, and higher (n = 93). Participants in higher risk profiles reported more HIV vulnerability behaviors and fewer harm reduction behaviors. PWID's gradient of HIV risk was associated with network norms, warranting intervention on high-vulnerability networks when services are limited.

Left behind on the path to 90-90-90: understanding and responding to HIV among displaced people.

INTRODUCTION: In 2021, the number of people affected by displacement worldwide reached the highest on record, with an estimated 30.5 million refugees and 4.6 million asylum seekers seeking safety across international borders and further 53.2 million people displaced within their countries of origin. Most forcibly displaced persons come from or relocate to lower- and middle-income countries (LMICs) and many of those countries have large HIV epidemics. In this commentary, we describe some of the challenges at the intersection of HIV and displacement vulnerabilities that cannot be easily addressed in resource-limited environments. DISCUSSION: HIV transmission and prevention and treatment efforts in the context of displacement are affected by myriad behavioural, social and structural factors across different stages of the displacement journey. For example, structural barriers faced by people experiencing displacement in relation to HIV prevention and care include funding constraints and legal framework deficiencies. Such barriers prevent all forced migrants, and particularly those whose sexual identities or practices are stigmatized against, access to prevention and care equal to local residents. Xenophobia, racism and other social factors, as well as individual risky behaviours facilitated by experiences of forced migration, also affect the progress towards 90-90-90 targets in displaced populations. Current evidence suggests increased HIV vulnerability in the period before displacement due to the effect of displacement drivers on medical supplies and infrastructure. During and after displacement, substantial barriers to HIV testing exist, though following resettlement in stable displacement context, HIV incidence and viral suppression are reported to be similar to those of local populations. CONCLUSIONS: Experiences of often-marginalized displaced populations are diverse and depend on the context of displacement, countries of origin and resettlement, and the nature of the crises that forced these populations to move. To address current gaps in responses to HIV in displacement contexts, research in LMIC, particularly in less stable resettlement settings, needs to be scaled up. Furthermore, displaced populations need to be specifically addressed in national AIDS strategies and HIV surveillance systems. Finally, innovative technologies, such as point-of-care viral load and CD4 testing, need to be developed and introduced in settings facing displacement.

Tracking SARS-COV-2 variants using Nanopore sequencing in Ukraine in 2021.

The use of real-time genomic epidemiology has enabled the tracking of the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), informing evidence-based public health decision making. Ukraine has experienced four waves of the Coronavirus Disease 2019 (COVID-19) between spring 2020 and spring 2022. However, insufficient capacity for local genetic sequencing limited the potential application of SARS-CoV-2 genomic surveillance for public health response in the country. Herein, we report local sequencing of 103 SARS-CoV-2 genomes from patient samples collected in Kyiv in July-December 2021 using Oxford Nanopore technology. Together with other published Ukrainian SARS-CoV-2 genomes, our data suggest that the third wave of the epidemic in Ukraine (June-December 2021) was dominated by the Delta Variant of Concern (VOC). Our phylogeographic analysis revealed that in summer 2021 Delta VOC was introduced into Ukraine from multiple locations worldwide, with most introductions coming from Central and Eastern European countries. The wide geographic range of Delta introductions coincides with increased volume of travel to Ukraine particularly from locations outside of Europe in summer 2021. This study highlights the need to urgently integrate affordable and easily scaled pathogen sequencing technologies in locations with less developed genomic infrastructure, in order to support local public health decision making.

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2.

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

Introduction and Establishment of SARS-CoV-2 Gamma Variant in New York City in Early 2021.

BACKGROUND: Monitoring the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is an important public health objective. We investigated how the Gamma variant was established in New York City (NYC) in early 2021 in the presence of travel restrictions that aimed to prevent viral spread from Brazil, the country where the variant was first identified. METHODS: We performed phylogeographic analysis on 15 967 Gamma sequences sampled between 10 March and 1 May 2021, to identify geographic sources of Gamma lineages introduced into NYC. We identified locally circulating Gamma transmission clusters and inferred the timing of their establishment in NYC. RESULTS: We identified 16 phylogenetically distinct Gamma clusters established in NYC (cluster sizes ranged 2-108 genomes); most of them were introduced from Florida and Illinois and only 1 directly from Brazil. By the time the first Gamma case was reported by genomic surveillance in NYC on 10 March, the majority (57%) of circulating Gamma lineages had already been established in the city for at least 2 weeks. CONCLUSIONS: Although travel from Brazil to the United States was restricted from May 2020 through the end of the study period, this restriction did not prevent Gamma from becoming established in NYC as most introductions occurred from domestic locations.

Detection of SARS-CoV-2 intra-host recombination during superinfection with Alpha and Epsilon variants in New York City.

Recombination is an evolutionary process by which many pathogens generate diversity and acquire novel functions. Although a common occurrence during coronavirus replication, detection of recombination is only feasible when genetically distinct viruses contemporaneously infect the same host. Here, we identify an instance of SARS-CoV-2 superinfection, whereby an individual was infected with two distinct viral variants: Alpha (B.1.1.7) and Epsilon (B.1.429). This superinfection was first noted when an Alpha genome sequence failed to exhibit the classic S gene target failure behavior used to track this variant. Full genome sequencing from four independent extracts reveals that Alpha variant alleles comprise around 75% of the genomes, whereas the Epsilon variant alleles comprise around 20% of the sample. Further investigation reveals the presence of numerous recombinant haplotypes spanning the genome, specifically in the spike, nucleocapsid, and ORF 8 coding regions. These findings support the potential for recombination to reshape SARS-CoV-2 genetic diversity.

Unified European support framework to sustain the HIV cascade of care for people living with HIV including in displaced populations of war-struck Ukraine.

Ukraine is one of the countries in Europe most affected by HIV. The escalation of open war on the European continent has affected HIV care in Ukraine in an unprecedented way. Treating physicians in Europe have little experience on how to handle HIV-specific care under these circumstances. A framework is urgently needed that both defines and sets out strategies to handle the specific challenges for emergency support for people living with HIV, both those staying in Ukraine and those becoming displaced. The optimal allocation of the few available medical resources, primarily antiretroviral therapy, is necessary to best prevent individual morbidity and achieve population transmission control. Professional HIV networks play a central role to create, optimise, and execute support strategies. Through a rapid literature review we identified the key strategies needed to create a support framework, adapted to Ukraine's HIV epidemiology. We produce a unified support framework aiming to reduce the inevitable impact on Ukraine's HIV care cascade now, and when rebuilding it after the war.

Tracking SARS-COV-2 Variants Using Nanopore Sequencing in Ukraine in Summer 2021.

Since spring 2020, Ukraine has experienced at least two COVID-19 waves and has just entered a third wave in autumn 2021. The use of real-time genomic epidemiology has enabled the tracking of SARS-CoV-2 circulation patterns worldwide, thus informing evidence-based public health decision making, including implementation of travel restrictions and vaccine rollout strategies. However, insufficient capacity for local genetic sequencing in Ukraine and other Lower and Middle-Income countries limit opportunities for similar analyses. Herein, we report local sequencing of 24 SARS-CoV-2 genomes from patient samples collected in Kyiv in July 2021 using Oxford Nanopore MinION technology. Together with other published Ukrainian SARS-COV-2 genomes sequenced mostly abroad, our data suggest that the second wave of the epidemic in Ukraine (February-April 2021) was dominated by the Alpha variant of concern (VOC), while the beginning of the third wave has been dominated by the Delta VOC. Furthermore, our phylogeographic analysis revealed that the Delta variant was introduced into Ukraine in summer 2021 from multiple locations worldwide, with most introductions coming from Central and Eastern European countries. This study highlights the need to urgently integrate affordable and easily-scaled pathogen sequencing technologies in locations with less developed genomic infrastructure, in order to support local public health decision making.

Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York.

Wide-scale SARS-CoV-2 genome sequencing is critical to tracking viral evolution during the ongoing pandemic. We develop the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detect an emerging lineage of SARS-CoV-2 in the New York region that shares mutations with previously reported variants. The most common sets of spike mutations in this lineage (now designated as B.1.526) are L5F, T95I, D253G, E484K or S477N, D614G, and A701V. This lineage was first sequenced in late November 2020. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage. In concert with other variants, like B.1.1.7, the rise of B.1.526 appears to have extended the duration of the second wave of COVID-19 cases in NYC in early 2021. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, supporting the public health relevance of this lineage.