Explore the vast range of titles available.

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.

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.

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.

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.

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.

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.

Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.1-like genomes and pre-existing immunity (seropositivity) in NYC neighborhoods. In the context of varying seroprevalence we described socio-economic profiles of neighborhoods and performed migration and lineage persistence analyses using a Bayesian phylogeographical framework. Seropositivity was greater in areas with high poverty and a larger proportion of Black and Hispanic or Latino residents. Seropositivity was positively correlated with the proportion of Iota-E484K and Iota genomes, and negatively correlated with the proportion of Alpha and B.1-like genomes. The proportion of persisting Alpha lineages declined over time in locations with high seroprevalence, whereas the proportion of persisting Iota-E484K lineages remained the same in high seroprevalence areas. During the second wave, the geographic variation of standing immunity, due to disproportionate disease burden during the first wave of SARS-CoV-2 in NYC, allowed for the immune evasive Iota-E484K variant, but not the more transmissible Alpha variant, to circulate in locations with high pre-existing immunity.

Objective Internally displaced persons (IDPs) can have limited access to HIV and hepatitis C Virus (HCV) treatment and prevention. IDPs comprise > 7% of Georgian population but prevalence and levels of HIV and HCV knowledge in this population remain unknown. We tested 100 IDPs in Georgia for HIV and HCV, many of whom had drug injecting experience, and interviewed them about their migration experience, sexual and drug injecting practices, and HIV/HCV transmission knowledge. Results The average age of participants was 37.5 years (range 18–63); 31% were women. Almost half (N = 48) of participants reported ever injecting drugs; 17% of those (N = 8) started injecting drugs within the last year. Anti-HCV and HIV prevalence was 11% and 0%, respectively. Fewer people without drug use experience compared to people who inject drugs correctly answered all questions on the HIV knowledge test (13% vs. 35%, p  = 0.015) or knew where to get tested for HIV (67% vs 98%, p  < 0.001). There was no difference in HCV knowledge between the two groups. HIV and HCV prevalence remains low among Georgian IDPs, but levels of HIV knowledge were much lower than levels of HCV knowledge.

The Russian invasion of Ukraine has displaced millions, potentially exposing them to traumatic events in the process. Potentially traumatic events (PTEs) have been linked to negative health outcomes, including depression, substance abuse and risky sexual behaviours. Men who have sex with men (MSM) are especially vulnerable to the effects of displacement, given widespread MSM stigma in Ukraine. A cross-sectional survey of MSM was conducted as part of a peer-driven intervention between August 2023 and January 2024 across eight cities in Ukraine via respondent-driven sampling. Lifetime PTE exposure responses were grouped into three binary variables: accidental/injury, victimisation and death threat. The relationship between displacement and exposure to PTEs was modelled using multivariate covariance generalized linear models with a logistic link, extending logistic regression to all three PTE responses. n=3617 (mean age 29.8, SD 8.1; 93% of the 3886 surveyed) were analysed. Controlling for sampling structure, participation in military operations, adverse experience of unstable housing in the last 2 years and age, internal displacement was significantly associated (p<0.001) with all three types of PTEs: adjusted ORs for accidental/injury, victimisation and death threat were 2.04, 1.57 and 2.05, respectively. As the war continues, our results highlight the need for trauma-informed care for internally displaced MSM in Ukraine, as many of them have been exposed to various types of PTEs. Those with adverse experiences of unstable housing conditions or participating in military operations particularly need to be considered.

New York City (NYC) was a major hotspot during the 2022 multi-country Mpox virus (MPXV) outbreak in the U.S. To investigate the genomic characteristics of MPXV in NYC, we sequenced 1138 specimens from 758 individuals using PrimalSeq and Illumina technology and performed phylogenomic analyses alongside 2967 global MPXV sequences. Nextclade lineage assignment revealed a NYC-specific B.1.12 lineage, with phylogenetic analysis showing unique clusters in NYC and North America. MPXV lineage B-specific mutations were predominantly driven by APOBEC3 activity (53/58 mutations). APOBEC3-associated mutations were significantly higher in 2022 outbreak sequences compared to those before 2022. Intra-host genome diversity was investigated in individuals with multiple specimens ( n  = 360). This analysis showed that 6.4% of these individuals had distinct genomic profiles, with 4.2% likely due to co-infections with distinct MPXV strains. This study identified unique MPXV genomic profiles in NYC, estimated concurrent infections with multiple MPXV strains and emphasized the need for enhanced surveillance and public health strategies to address co-infections, especially through collaboration with labs, clinics, and community groups. Using MPXV genomes specific to New York City, phylogenetic clusters were identified. Most mutations were driven by ABOBEC3. The prevalence of coinfections with distinct strains was ~4.2% and results may improve MPXV genomic epidemiology applications.