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.

Integrated Genomic and Social Network Analyses of Severe Acute Respiratory Syndrome Coronavirus 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.

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.

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.

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.

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.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

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 development of testing methods, and allowed 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 the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

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.

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.

Global prevalence and phylogeny of hepatitis B virus (HBV) drug and vaccine resistance mutations

Vaccination and anti-viral therapy with nucleos(t)ide analogues (NAs) are key approaches to reducing the morbidity, mortality and transmission of hepatitis B virus (HBV) infection. However, the efficacy of these interventions may be reduced by the emergence of drug resistance-associated mutations (RAMs) and/or vaccine escape mutations (VEMs). We have assimilated data on the global prevalence and distribution of HBV RAMs/VEMs from publicly available data and explored the evolution of these mutations. We analysed sequences downloaded from the HBV Database and calculated prevalence of 41 RAMs and 38 VEMs catalogued from published studies. We generated maximum likelihood phylogenetic trees and used treeBreaker to investigate the distribution and estimated the age of selected mutations across tree branches. RAM M204I/V had the highest prevalence, occurring in 3.8% (109/2838) of all HBV sequences in our data set, and a significantly higher rate in genotype C at 5.4% (60/1102, p = 0.0007). VEMs had an overall prevalence of 1.3% (37/2837) and had the highest prevalence in genotype C and in Asia at 2.2% (24/1102; p = 0.002) and 1.6% (34/2109; p = 0.009), respectively. Phylogenetic analysis suggested that RAM/VEMs can arise independently of treatment/vaccine exposure. In conclusion, HBV RAMs/VEMs have been found globally and across genotypes, with the highest prevalence observed in genotype C. Screening for genotype and for resistance-associated mutations may help to improve stratified patient treatment. As NAs and HBV vaccines are increasingly being deployed for HBV prevention and treatment, monitoring for resistance and advocating for better treatment regimens for HBV remains essential.

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. Variants first detected in the United Kingdom, South Africa, and Brazil have spread to multiple countries. We developed the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detected 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 when it represented <1% of sequenced coronavirus genomes that were collected in New York City (NYC). By February 2021, genomes from this lineage accounted for ~32% of 3288 sequenced genomes from NYC specimens. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage in NYC, notably the sub-clade defined by the spike mutation E484K, which has outpaced the growth of other variants in NYC. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, indicating the public health importance of this lineage.

Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

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.

Challenges posed by COVID-19 to people who inject drugs and lessons from other outbreaks

INTRODUCTION

In light of the COVID-19 pandemic, considerable effort is going into identifying and protecting those at risk. Criminalization, stigmatization and the psychological, physical, behavioural and economic consequences of substance use make people who inject drugs (PWID) extremely vulnerable to many infectious diseases. While relationships between drug use and blood-borne and sexually transmitted infections are well studied, less attention has been paid to other infectious disease outbreaks among PWID.

DISCUSSION

COVID-19 is likely to disproportionally affect PWID due to a high prevalence of comorbidities that make the disease more severe, unsanitary and overcrowded living conditions, stigmatization, common incarceration, homelessness and difficulties in adhering to quarantine, social distancing or self-isolation mandates. The COVID-19 pandemic also jeopardizes essential for PWID services, such as needle exchange or substitution therapy programmes, which can be affected both in a short- and a long-term perspective. Importantly, there is substantial evidence of other infectious disease outbreaks in PWID that were associated with factors that enable COVID-19 transmission, such as poor hygiene, overcrowded living conditions and communal ways of using drugs.

CONCLUSIONS

The COVID-19 crisis might increase risks of homelessnes, overdoses and unsafe injecting and sexual practices for PWID. In order to address existing inequalities, consultations with PWID advocacy groups are vital when designing inclusive health response to the COVID-19 pandemic.

Transmission of hepatitis C virus in HIV-positive and PrEP-using MSM in England

We sought to characterize risk factors and patterns of HCV transmission amongst men who have sex with men (MSM). MSM with recently acquired HCV (AHCV) were prospectively recruited ('clinic cohort') between January and September 2017. Clinical data and risk behaviours were identified and blood obtained for HCV whole genome sequencing. Phylogenetic analyses were performed, using sequences from this cohort and two other AHCV cohorts, to identify transmission clusters. Sixteen (40.0%) men in the clinic cohort were HIV-negative MSM. HIV-negative MSM were younger than HIV-positive MSM; most (81.3%) had taken HIV PrEP in the preceding year. Eighteen men (45.0%) reported injection drug use; most (34, 85.0%) reported noninjection drug use in the last year. Most in both groups reported condomless anal sex, fisting and sex in a group environment. Few (7, 17.5%) men thought partners may have had HCV. There were 52 sequences in the HCV genotype 1a phylogeny, 18 from the clinic cohort and 34 from other AHCV cohorts; 47 (90.4%) clustered with ≥1 other sequence. There were 7 clusters of 2-27 sequences; 6 clusters contained HIV-negative and HIV-positive MSM and 1 cluster only HIV-positive MSM. Four of these clusters were part of larger clusters first described in 2007. PrEP-using MSM are at risk of HCV, sharing similar risk factors to HIV-positive MSM. Phylogenetics highlights that PrEP-using and HIV-positive MSM are involved in the same HCV transmission networks. Few men demonstrated HCV awareness and risk reduction strategies should be expanded.

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.

People with high HIV viral load within risk networks: who are these people and who refers them best?

Introduction:

Viral load is one of the most important determinants for HIV transmission. Identification of people with high viral load (PHVL) can be effective in limiting onward HIV transmission. In order to improve the identification of these individuals within risk networks, we determined a) the number of PHVL recruited through risk networks b) their socio-demographic, behavioural and clinical characteristics and c) the characteristics of individuals who referred these PHVL to the study.

Methodology:

From November 2013 to March 2016, in Odessa, Ukraine, Transmission Reduction Intervention Project (TRIP) was implemented to identify people recently infected with HIV within the risk networks of “seeds” and “venues” where they engaged in risk behaviour.

Results:

TRIP identified 53 PHVL, of whom 32 (60%) injected drugs; 42 (79%) were unaware of their HIV status; 25 (47%) had more than one sex partner, and only 14 (26%) were using condoms. There were 164 people who referred individuals into the study; 33 of them (20%) referred PHVL. In terms of referrers, those with lower than secondary level of education, not living with a sex partner, and reporting regular condom use were significantly more likely (p < 0.05) to refer PHVL. Most PHVL (38, 72%) and their referrers (27, 82%) were found through venues.

Conclusions:

In Odessa city, PHVL are at high risk of transmitting HIV as the majority inject drugs, do not know their HIV status, and have unprotected sex and/or multiple partners. Targeting these individuals for HIV prevention, harm reduction and initiation of antiretroviral treatment (ART) is urgent.

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.

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.

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.

An Innovative Study Design to Assess the Community Effect of Interventions to Mitigate HIV Epidemics Using Transmission-Chain Phylodynamics

Given globalization and other social phenomena, controlling the spread of infectious diseases has become an imperative public health priority. A plethora of interventions that in theory can mitigate the spread of pathogens have been proposed and applied. Evaluating the effectiveness of such interventions is costly and in many circumstances unrealistic. Most important, the community effect (i.e., the ability of the intervention to minimize the spread of the pathogen from people who received the intervention to other community members) can rarely be evaluated. Here we propose a study design that can build and evaluate evidence in support of the community effect of an intervention. The approach exploits molecular evolutionary dynamics of pathogens in order to track new infections as having arisen from either a control or an intervention group. It enables us to evaluate whether an intervention reduces the number and length of new transmission chains in comparison with a control condition, and thus lets us estimate the relative decrease in new infections in the community due to the intervention. We provide as an example one working scenario of a way the approach can be applied with a simulation study and associated power calculations.

Genomic and epidemiological monitoring of yellow fever virus transmission potential

The yellow fever virus (YFV) epidemic in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes species mosquitos highlights a need to monitor the risk of reestablishment of urban YFV transmission in the Americas. We use a suite of epidemiological, spatial, and genomic approaches to characterize YFV transmission. We show that the age and sex distribution of human cases is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally reveals an early phase of sylvatic YFV transmission and spatial expansion toward previously YFV-free areas, followed by a rise in viral spillover to humans in late 2016. Our results establish a framework for monitoring YFV transmission in real time that will contribute to a global strategy to eliminate future YFV epidemics.

Network Research Experiences in New York and Eastern Europe: Lessons for the Southern US in Understanding HIV Transmission Dynamics

PURPOSE

This paper presents an overview of different kinds of risk and social network methods and the kinds of research questions each can address.

RECENT FINDINGS

It also reviews what network research has discovered about how network characteristics are associated with HIV and other infections, risk behaviors, preventive behaviors, and care, and discusses some ways in which network-based public health interventions have been conducted. Based on this, risk and social network research and interventions seem both feasible and valuable for addressing the many public health and social problems raised by the widespread use of opioids in the US South.

Engagement in sex work does not increase HIV risk for women who inject drugs in Ukraine

Background

We studied the association between sex in exchange for money, drugs or goods and HIV for women who inject drugs (WWID) in Ukraine, as previous data on this association from the post-USSR region are contradictory.

Methods

Data come from the Integrated Bio-Behavioral Survey of Ukrainian people who inject drugs collected in 2011 using respondent-driven sampling. Participants were interviewed and tested with rapid HIV tests.

Results

The sample included 2465 WWID (24% HIV positive); 214 (8.7%) of which reported having had exchange sex during the last 90 days. Crude analysis showed no association between exchange sex and HIV (OR = 0.644; 95% CI 0.385–1.077). No confounders were found to alter this result in a multivariable analysis. Further modeling showed that exchange sex modifies association between HIV and alcohol use: no association between HIV and daily alcohol use was found for those women who exchanged sex (OR = 1.699, 95% CI 0.737–3.956); while not engaging in sex work and daily using alcohol reduced odds to be HIV infected (OR = 0.586, 95% CI 0.389–0.885).

Conclusions

Exchange sex may have less impact on the HIV status of WWID who are exposed to injecting risks. The finding that daily alcohol use appears protective against HIV among WWID who do not exchange sex requires more research.

Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health

The number of public health applications for molecular epidemiology and social network analysis has increased rapidly since the improvement in computational capacities and the development of new sequencing techniques. Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways. The latter are of great epidemiological importance as they let us describe how a virus spreads in a community, make predictions for the further epidemic developments, and plan preventive interventions. Social network methods are used to understand how infections spread through communities and what the risk factors for this are, as well as in improved contact tracing and message-dissemination interventions. Research is needed on how to combine molecular and social network data as both include essential, but not fully sufficient information on infection transmission pathways. The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members. Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data. Secondly, network data refer to the current state and interactions within the social network, while molecular data refer to the time points when transmissions happened, which might have happened years before the sampling date. As of today, there have been attempts to combine and compare the data obtained from the two sources. Even though there is no consensus on whether and how social and genetic data complement each other, this research might significantly improve our understanding of how viruses spread through communities.

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We summarise and analyse the roles of molecular evolution studies in molecular epidemiology of infectious diseases.

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We review how social network and molecular sequence data have been integrated in the past.

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We show how integrating social network and molecular evolution approaches may change the study of infectious diseases.

Socially-integrated transdisciplinary HIV prevention

Current ideas about HIV prevention include a mixture of primarily biomedical interventions, socio-mechanical interventions such as sterile syringe and condom distribution, and behavioral interventions. This article presents a framework for socially-integrated transdisciplinary HIV prevention that may improve current prevention efforts. It first describes one socially-integrated transdisciplinary intervention project, the Transmission Reduction Intervention Project. We focus on how social aspects of the intervention integrate its component parts across disciplines and processes at different levels of analysis. We then present socially-integrated perspectives about how to improve combination antiretroviral treatment (cART) processes at the population level in order to solve the problems of the treatment cascade and make "treatment as prevention" more effective. Finally, we discuss some remaining problems and issues in such a social transdisciplinary intervention in the hope that other researchers and public health agents will develop additional socially-integrated interventions for HIV and other diseases.

A new approach to prevent HIV transmission: Project Protect intervention for recently infected individuals

Past research suggests that as many as 50% of onward human immunodeficiency virus (HIV) transmissions occur during acute and recent HIV infection. It is clearly important to develop interventions which focus on this highly infectious stage of HIV infection to prevent further transmission in the risk networks of acutely and recently infected individuals. Project Protect tries to find recently and acutely infected individuals and prevents HIV transmission in their risk networks. Participants are recruited by community health outreach workers at community-based HIV testing sites and drug users' community venues, by coupon referrals and through referrals from AIDS clinics. When a network with acute/recent infection is identified, network members are interviewed about their risky behaviors, network information is collected, and blood is drawn for HIV testing. Participants are also educated and given prevention materials (condoms, syringes, educational materials); HIV-infected participants are referred to AIDS clinics and are assisted with access to care. Community alerts about elevated risk of HIV transmission are distributed within the risk networks of recently infected. Overall, 342 people were recruited to the project and screened for acute/recent HIV infection. Only six index cases of recent infection (2.3% of all people screened) were found through primary screening at voluntary counseling and testing (VCT) sites, but six cases of recent infection were found through contact tracing of these recently infected participants (7% of network members who came to the interview). Combining screening at VCT sites and contact tracing the number of recently infected people we located as compared to VCT screening alone. No adverse events were encountered. These first results provide evidence for the theory behind the intervention, i.e., in the risk networks of recently infected people there are other people with recent HIV infection and they can be successfully located without increasing stigma for project participants.