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BackgroundMonitoring the emergence and spread of SARS-CoV-2 variants is an important public health objective. Travel restrictions, aimed to prevent viral spread, have major economic consequences and unclear effectiveness despite considerable research. We investigated the introduction and establishment of the Gamma variant in New York City (NYC) in 2021.MethodsWe performed phylogeographic analysis on 15,967 Gamma sequences available on GISAID and sampled between March 10th through May 1st, 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.FindingsWe identified 16 phylogenetically-distinct Gamma clusters established in NYC (cluster sizes ranged 2-108 genomes). Most of the NYC clusters were introduced from Florida and Illinois; only one was introduced from outside the United States (US). By the time the first Gamma case was reported by genomic surveillance in NYC on March 10th, the majority (57%) of circulating Gamma lineages had already been established in the city for at least two weeks.InterpretationDespite the expansion of SARS-CoV-2 genomic surveillance in NYC, there was a substantial gap between Gamma variant introduction and establishment in January/February 2021, and its identification by genomic surveillance in March 2021. Although travel from Brazil to the US 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.

SummaryThe maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of SARS-CoV-2 lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of ‘local’ when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

OBJECTIVES: We examined whether molecular cluster membership was associated with public health identification of HIV transmission potential among named partners in Chicago. DESIGN: Historical cohort study METHODS: We matched and analyzed HIV surveillance and partner services data from HIV diagnoses (2012–2016) prior to implementation of cluster detection and response interventions. We constructed molecular clusters using HIV-TRACE at a pairwise genetic distance threshold of 0·5% and identified clusters exhibiting recent and rapid growth according to the CDC’s definition (3 new cases diagnosed in past year). Factors associated with identification of partners with HIV transmission potential were examined using multivariable Poisson regression. RESULTS: There were 5,208 newly diagnosed index clients over this time period. Average age of index clients in clusters was 28; 47% were Black, 29% Latinx/Hispanic, 6% female and 89% men who have sex with men (MSM). Of the 537 named partners, 191 (35·6%) were linked to index cases in a cluster and of those 16% were either new diagnoses or viremic. There was no statistically significant difference in the probability of identifying partners with HIV transmission potential among index clients in a rapidly growing cluster versus those not in a cluster (adjusted Relative Risk 1·82, (0·81–4·06)). CONCLUSION: Partner services that were initiated from index clients in a molecular cluster yielded similar new HIV case finding or identification of those with viremia as did interviews with index clients not in clusters. It remains unclear whether these findings are due to temporal disconnects between diagnoses and cluster identification, unobserved cluster members, or challenges with partner services implementation.

Objectives Due to limited hepatitis C virus (HCV) sequence availability from patients in Russia, the relationship between subtypes and baseline resistance-associated substitutions (RAS) to direct antiretroviral treatment outcome is not fully understood. Methods Deep sequencing of HCV NS3, NS5A, and NS5B sequences was performed on plasma HCV samples from 412 direct-acting antiviral (DAA)-naive patients from Russia. Phylogenetic analysis was performed to investigate sequence similarities between HCV strains from Russia, Asia, Europe, and North America. Pretreatment HCV RAS was assessed with a 15% cutoff. Results HCV genotype GT1b and GT3a sequences in Russia were related to strains in Europe and Asia. The prevalence of GT1a and GT2a was low in Russia. In GT1b, the prevalence of NS5A Y93H was lower in Russia (6%) compared with Asia (15%). The prevalence of NS5B L159F was similar between Russia and Europe (26–39%). GT3a RAS prevalence was similar between Russia and Asia, Europe, and North America. The 2k/1b recombinant strain in Russia was related to strains from Europe. A higher prevalence of the NS5A RAS L31M (10%) was observed in 2k/1b sequences compared to GT1b (1–6%). Conclusions The prevalence of RASs and the phylogenetic analysis showed similarities in HCV strains between Russia, Europe, and North America. This information may be useful for HCV regimens in Russia.

An important component underlying the disparity in HIV risk between race/ethnic groups is the preferential transmission between individuals in the same group. We sought to quantify transmission between different race/ethnicity groups and measure racial assortativity in HIV transmission networks in major metropolitan areas in the United States. We reconstructed HIV molecular transmission networks from viral sequences collected as part of HIV surveillance in New York City, Los Angeles County, and Cook County, Illinois. We calculated assortativity (the tendency for individuals to link to others with similar characteristics) across the network for three candidate characteristics: transmission risk, age at diagnosis, and race/ethnicity. We then compared assortativity between race/ethnicity groups. Finally, for each race/ethnicity pair, we performed network permutations to test whether the number of links observed differed from that expected if individuals were sorting at random. Transmission networks in all three jurisdictions were more assortative by race/ethnicity than by transmission risk or age at diagnosis. Despite the different race/ethnicity proportions in each metropolitan area and lower proportions of clustering among African Americans than other race/ethnicities, African Americans were the group most likely to have transmission partners of the same race/ethnicity. This high level of assortativity should be considered in the design of HIV intervention and prevention strategies.

Large datasets along with sampling bias represent a challenge for phylodynamic reconstructions, particularly when the study data are obtained from various heterogeneous sources and/or through convenience sampling. In this study, we evaluate the presence of unbalanced sampled distribution by collection date, location, and risk group of HIV-1 subtype C using a compre-hensive subsampling strategy, and assess their impact on the reconstruction of the viral spatial and risk group dynamics using phylogenetic comparative methods. Our study shows that the most suitable dataset for ancestral trait reconstruction can be obtained through subsampling by collection date, location, and risk group, particularly using multigene datasets. We also demonstrate that sampling bias is inflated when considerable information for a given trait is unavailable or of poor quality, as we observed for the risk group in the analysis of HIV-1 subtype C. In conclusion, we suggest that, even if traits are not well recorded, including them deliberately optimizes the representativeness of the original dataset rather than completely excluding them. Therefore, we advise the inclusion of as many traits as possible with the aid of subsampling approaches in order to optimize the dataset for phylodynamic analysis while reducing the computational burden. This will benefit research communities investigating the evolutionary and spatiotemporal patterns of infectious diseases.

Funder: Somerville College MTST Development Award and Catherine Hughes Fund, Funder: Catherine Hughes Fund, Funder: Global Challenges Research Fund and Wellcome Institutional Strategic Support Fund, Funder: Branco Weiss Fellowship – Society in Science; doi: http://dx.doi.org/10.13039/501100001710, 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.

Human herpes simplex virus 2 (HSV-2) is a ubiquitous, slowly evolving DNA virus. HSV-2 has two primary lineages, one found in West and Central Africa and the other found worldwide. Competing hypotheses have been proposed to explain how HSV-2 migrated out-of-Africa (i)HSV-2 followed human migration out-of-Africa 50-100 thousand years ago, or (ii)HSV-2 migrated via the trans-Atlantic slave trade 150-500 years ago. Limited geographic sampling and lack of molecular clock signal has precluded robust comparison. Here, we analyze newly sequenced HSV-2 genomes from Africa to resolve geography and timing of divergence events within HSV-2. Phylogeographic analysis consistently places the ancestor of worldwide dispersal in East Africa, though molecular clock is too slow to be detected using available data. Rates 4.2 × 10−8−5.6 × 10−8 substitutions/site/year, consistent with previous age estimates, suggest a worldwide dispersal 22-29 thousand years ago. Thus, HSV-2 likely migrated with humans from East Africa and dispersed after the Last Glacial Maximum.

Phylogenetic trees from real-world data often include short edges with very few substitutions per site, which can lead to partially resolved trees and poor accuracy. Theory indicates that the number of sites needed to accurately reconstruct a fully resolved tree grows at a rate proportional to the inverse square of the length of the shortest edge. However, when inferred trees are partially resolved due to short edges, “accuracy” should be defined as the rate of discovering false splits (clades on a rooted tree) relative to the actual number found. Thus, accuracy can be high even if short edges are common. Specifically, in a “near-perfect” parameter space in which trees are large, the tree length $\xi$ (the sum of all edge lengths) is small, and rate variation is minimal, the expected false positive rate is less than $\xi/3$; the exact value depends on tree shape and sequence length. This expected false positive rate is far below the false negative rate for small $\xi$ and often well below 5% even when some assumptions are relaxed. We show this result analytically for maximum parsimony and explore its extension to maximum likelihood using theory and simulations. For hypothesis testing, we show that measures of split “support” that rely on bootstrap resampling consistently imply weaker support than that implied by the false positive rates in near-perfect trees. The near-perfect parameter space closely fits several empirical studies of human virus diversification during outbreaks and epidemics, including Ebolavirus, Zika virus, and SARS-CoV-2, reflecting low substitution rates relative to high transmission/sampling rates in these viruses.[Ebolavirus; epidemic; HIV; homoplasy; mumps virus; perfect phylogeny; SARS-CoV-2; virus; West Nile virus; Yule–Harding model; Zika virus.]

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 is critical to preventing future zoonotic outbreaks before they become the next pandemic. The Huanan Seafood Wholesale Market in Wuhan, China, was identified as a likely source of cases in early reports, but later this conclusion became controversial. We show here that the earliest known COVID-19 cases from December 2019, including those without reported direct links, were geographically centered on this market. We report that live SARS-CoV-2-susceptible mammals were sold at the market in late 2019 and that within the market, SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals. Although there is insufficient evidence to define upstream events, and exact circumstances remain obscure, our analyses indicate that the emergence of SARS-CoV-2 occurred through the live wildlife trade in China and show that the Huanan market was the epicenter of the COVID-19 pandemic. ispartof: SCIENCE vol:377 issue:6609 pages:951-959 ispartof: location:United States status: published

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.

Backtracking a pandemic Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have had a history of abortive human infections before a variant established a productive enough infection to create a transmission chain with pandemic potential. Therefore, the Wuhan cluster of infections identified in late December of 2019 may not have represented the initiating event. Pekar et al. used genome data collected from the early cases of the COVID-19 pandemic combined with molecular clock inference and epidemiological simulation to estimate when the most successful variant gained a foothold in humans. This analysis pushes human-to-human transmission back to mid-October to mid-November of 2019 in Hubei Province, China, with a likely short interval before epidemic transmission was initiated. Science, this issue p. 412, SARS-CoV-2 human-to-human transmission likely initiated in mid-October to mid-November 2019 in Hubei, China., Understanding when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged is critical to evaluating our current approach to monitoring novel zoonotic pathogens and understanding the failure of early containment and mitigation efforts for COVID-19. We used a coalescent framework to combine retrospective molecular clock inference with forward epidemiological simulations to determine how long SARS-CoV-2 could have circulated before the time of the most recent common ancestor of all sequenced SARS-CoV-2 genomes. Our results define the period between mid-October and mid-November 2019 as the plausible interval when the first case of SARS-CoV-2 emerged in Hubei province, China. By characterizing the likely dynamics of the virus before it was discovered, we show that more than two-thirds of SARS-CoV-2like zoonotic events would be self-limited, dying out without igniting a pandemic. Our findings highlight the shortcomings of zoonosis surveillance approaches for detecting highly contagious pathogens with moderate mortality rates.

OBJECTIVE. Unintentional drug poisoning and overdose deaths in New York City (NYC) increased 175% between 2010 and 2017, partly due to the transition from non-injectable opioids to heroin injection. This transition has led to concern of a resurgent HIV epidemic among persons who inject drugs (PWID) in NYC. Thus, we sought to characterize HIV transmission dynamics in PWID. DESIGN. Genetic network analysis of HIV-1 public health surveillance data. METHODS. We analyzed HIV diagnoses reported to public health surveillance to determine the trajectory of the HIV epidemic among PWID in NYC, from 1985 through 2019. Genetic distance-based clustering was performed using HIV-TRACE to reconstruct transmission patterns among PWID. RESULTS. The majority of the genetic links to PWID diagnosed in the 1980s and 1990s are to other PWID. However, since 2011, there has been a continued decline in new diagnoses among PWID, and genetic links between PWID have become increasingly rare, while links to non-injecting men who have sex with men and other people reporting sexual transmission risk have become increasingly common. However, we also find evidence suggestive of a resurgence of genetic links among PWID in 2018–2019. PWID who reported male-male sexual contact were not preferentially genetically linked to PWID over the surveillance period, emphasizing their distinct risk profile from other PWID. CONCLUSIONS. These trends suggest a transition from parenteral to sexual transmission among PWID in NYC, suggesting that harm reduction, syringe exchange programs, and legalization of over-the-counter syringe sales in pharmacies have mitigated HIV risk by facilitating safe injection among future new injectors.

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.

Detection of viral transmission clusters using molecular epidemiology is critical to the response pillar of the Ending the HIV Epidemic initiative. Here, we studied whether inference with an incomplete dataset would influence the accuracy of the reconstructed molecular transmission network. We analyzed viral sequence data available from ~ 13,000 individuals with diagnosed HIV (2012–2019) from Houston Health Department surveillance data with 53% completeness (n = 6852 individuals with sequences). We extracted random subsamples and compared the resulting reconstructed networks versus the full-size network. Increasing simulated completeness was associated with an increase in the number of detected clusters. We also subsampled based on the network node influence in the transmission of the virus where we measured Expected Force (ExF) for each node in the network. We simulated the removal of nodes with the highest and then lowest ExF from the full dataset and discovered that 4.7% and 60% of priority clusters were detected respectively. These results highlight the non-uniform impact of capturing high influence nodes in identifying transmission clusters. Although increasing sequence reporting completeness is the way to fully detect HIV transmission patterns, reaching high completeness has remained challenging in the real world. Hence, we suggest taking a network science approach to enhance performance of molecular cluster detection, augmented by node influence information.

BACKGROUND In the United States, young men (aged 13-24 years) who have sex with men (MSM) bear a disproportionate burden of HIV. Transmission among MSM has been found to be disassortative by age. METHODS We analyzed HIV-1 pol sequences reported to the US National HIV Surveillance System from MSM with HIV diagnosed during 2009-2016. Using an HIV genetic transmission network, we identified persons with closely related viruses (ie, genetic distance ≤1.5%) and used multivariable logistic regression to examine changes from 2009-2012 to 2013-2016 in proportions of MSM linked to young MSM who were >5 years older or of the same race/ethnicity. RESULTS Among 9510 young MSM linked to another MSM with a closely related virus, 37% linked to an older MSM and 62% linked to an MSM of the same race/ethnicity. Comparing 2013-2016 with 2009-2012, we found increases in linkage of older MSM to young MSM, with the most substantial increases seen in Hispanic/Latinos aged 13-19 [adjusted prevalence ratio (APR) = 1.31, 95% confidence interval (CI) = 1.11 to 1.56] and blacks aged 13-19 (APR = 1.23, CI = 1.06 to 1.41) and 20-24 years (APR = 1.14, CI = 1.02 to 1.28). By contrast, change in linkage patterns among racial/ethnic groups was unremarkable. CONCLUSIONS We found evidence of increased age mixing among MSM with respect to HIV transmission over time, which coincides temporally with changes in partner-seeking behavior such as increased use of mobile applications. These findings indicate the importance of social factors on HIV sexual and transmission networks and suggest that prevention efforts need to effectively reach MSM of all ages.

Objective To identify correlates of incident HIV infection in rapidly growing HIV molecular clusters. Design Phylogenetic analysis of HIV public health surveillance data. Methods High-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period. Results Of the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster. Conclusion These findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

BACKGROUND: To develop a predictive model to prioritize persons with a transmissible HIV viral load for transmission-reduction interventions. METHODS: New York City (NYC) HIV molecular surveillance data from 2010–2013 were used to build a model to predict the probability that the partial pol gene of the virus of a person with a transmissible HIV viral load (>1,500 copies/mL) would be genetically similar to that of a person with a new HIV infection (diagnosis at stage 0 or 1 according to the revised Centers for Disease Control and Prevention classification system). Data from 2013–2016 were then used to validate the model and compare it with five other selection strategies that can be used to prioritize persons for transmission-reduction interventions. RESULTS: A total of 10,609 persons living with HIV (PLWH) were included in the development dataset, and 8,257 were included in the validation dataset. Among the six selection strategies, the predictive model had the highest area under the receiver operating characteristic curve (AUC) (0.86, 95% confidence interval [CI]: 0.84, 0.88), followed by the “Young men who have sex with men (MSM)” (0.79, 95% CI: 0.77, 0.82), “MSM with high viral loads” (0.74, 95% CI: 0.72, 0.76), “Random sample of MSM” (0.73, 95% CI: 0.71, 0.76), “Persons with high viral loads” (0.56, 95% CI: 0.54, 0.59), and “Random sample” (0.50, 95% CI: 0.48, 0.53) strategies. CONCLUSIONS: Jurisdictions should consider applying predictive modeling to prioritize persons with a transmissible viral load for transmission-reduction interventions and to evaluate its feasibility and effectiveness.

Recombination is an evolutionary process by which many pathogens generate diversity and acquire novel functions. Although a common occurrence during coronavirus replication, recombination can only be detected when two genetically distinct viruses contemporaneously infect the same host. Here, we identify an instance of SARS-CoV-2 superinfection, whereby an individual was simultaneously 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 revealed that Alpha variant alleles comprised between 70-80% of the genomes, whereas the Epsilon variant alleles comprised between 20-30% of the sample. Further investigation revealed 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.

Human herpes simplex virus 2 (HSV-2) is a globally ubiquitous, slow evolving DNA virus. HSV-2 genomic diversity can be divided into two main groups: an African lineage and worldwide lineage. Competing hypotheses have been put forth to explain the history of HSV-2. HSV-2 may have originated in Africa and then followed the first wave of human migration out of Africa between 50-100 kya. Alternatively, HSV-2 may have migrated out of Africa via the trans-Atlantic slave trade within the last 150-500 years. The lack of HSV-2 genomes from West and Central Africa, combined with a lack of molecular clock signal in HSV-2 has precluded robust testing of these competing hypotheses. Here, we expand the geographic sampling of HSV-2 genomes in order to resolve the geography and timing of divergence events within HSV-2. We analyze 65 newly sequenced HSV-2 genomes collected from primarily West and Central Africa along with 330 previously published genomes sampled over a 47-year period. Evolutionary simulations confirm that the molecular clock in HSV-2 is too slow to be detected using available data. However, phylogeographic analysis indicates that all biologically plausible evolutionary rates would place the ancestor of the worldwide lineage in East Africa, arguing against the trans-Atlantic slave trade as the source of worldwide diversity. The best supported evolutionary rates between 4.2×10−8 and 5.6×10−8 substitutions/site/year suggest a most recent common ancestor for HSV-2 around 90-120 kya and initial dispersal around 21.9-29.3 kya. These dates suggest HSV-2 left Africa during subsequent waves of human migration out of East Africa.

Background Prior to direct-acting antivirals (DAAs), HCV incidence rose among men who have sex with men (MSM) living with HIV infection in Germany despite high hepatitis C virus (HCV) treatment rates. We establish a HCV elimination modeling framework to evaluate whether existing treatment rates can achieve the World Health Organization (WHO) incidence target among MSM living with HIV in Germany. Methods To evaluate progress towards HCV elimination in Germany, we adapted a previously published HCV transmission model among MSM living with diagnosed HIV. We modelled HCV incidence and prevalence until 2030 (relative to 2015) under existing treatment and DAA scale-up and explored potential impacts of disruptions in treatment and behavioral risk reduction due to the COVID-19 pandemic. Results Continuing current treatment rates will result in stable HCV incidence among MSM living with HIV in Germany between 2015–2030. The WHO HCV incidence target is achievable under DAA scale-up to 100% treatment combined with treatment of those previously diagnosed and untreated (at a rate of 15%/year) and would result in greater reductions with early treatment (3 vs 6 months) reducing incidence from 4.0/100person-years to 0.8/100person-years by 2030. A 12-month disruption to HCV treatment (20% reduction) and risk behaviors (25%,50%,75% reduction) during the COVID-19 pandemic would result in a 15% relative increase in total HCV incidence in 2030 compared to that expected under the status quo. Conclusions HCV elimination among MSM living with HIV in Germany requires further DAA scale-up among those newly diagnosed combined with efforts to treat those previously diagnosed but untreated. Prospective monitoring will establish whether Germany is on track for HCV microelimination.

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.

BackgroundDue 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) due to war in eastern Ukraine.MethodsIn this cross-sectional study, we used modified respondent-driven sampling to recruit IDPWID who have settled in Odessa, Ukraine. We generated partial and near full length genome (NFLG) HCV sequences using Oxford Nanopore MinION in a simulated field environment. Maximum likelihood and Bayesian methods were used to establish phylodynamic relationships.FindingsBetween June and September 2020, we collected epidemiological data and whole blood samples from 164 IDPWID. Rapid testing identified an HIV, anti-HCV, and HIV/HCV co-infection prevalence of 39%, 67.7%, and 31.1%, respectively. 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-migration. Unstable housing post-migration was associated with more reports of injection drug use in the past 30 days (p=0.048).InterpretationLocal generation of viral sequencing data and phylogenetic analysis in rapidly changing low-resource environments, such as those faced by forcibly displaced people, can inform timely adaptation of prevention and treatment.FundingOxford University John Fell Fund, ISS Wellcome Trust, Branco Weiss Fellowship.

The first case of HIV in Pakistan was documented in 1987, with multiple subtypes and circulating recombinant forms being introduced and currently circulating in the country. Since then, there has been a shift in the country from a low prevalence/high risk to a high-risk concentrated epidemic. Pakistan’s epidemic is concentrated among key populations at greater risk of HIV infection including people who inject drugs (PWID), Hijra sex workers (HSW), female sex workers (FSW), male sex workers (MSW), and men who have sex with men (MSM). This study focused on the geographical aspect as well as on the interactions between key populations at higher risk of contracting HIV. We aimed at understanding the behavior of these key populations at a molecular level with high granularity as well as investigating the possibility of multiple HIV-1 introductions in Pakistan. In this cross-sectional biological and behavioral survey, we collected dried blood spots (DBS) for the purposes of seroprevalence estimates and molecular epidemiology from individuals in 17 cities in Pakistan representing four key populations: PWID, HSW, MSW, and FSW. A total of 1153 envelope sequences (reference positions in HXB2: 7860-8274) of HIV were sequenced using a Sanger-based sequencing approach. To identify clusters based on the introduction of the virus in Pakistan from foreign countries we added 3623 publicly available HIV envelope sequences to our dataset. Phylogeographic inference suggests at least 15 independent introductions of the virus into Pakistan, with a total of 12 clusters ranging from 3 to 675 sequences in size containing sequences from Pakistan and neighboring countries exclusively. Our phylogenetic analysis shows a significant degree of connectivity and directionality suggesting broad and overlapping networks of HIV-1 transmission among cities and key populations in Pakistan.

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.

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., West and colleagues develop the Variant Database software tool for examination of changing Spike mutations in SARS-CoV-2 genomes. The authors use this to detect emerging lineages of SARS-CoV-2 in New York and report the rapid spread of the B.1.526 lineage in the city.

The Origins of SARS-CoV-2: A Critical Review Holmes et al. Published online: 18-Aug-2021, Cell, https://doi.org/10.1016/j.cell.2021.08.017 Since the first reports of a novel SARS-like coronavirus in December 2019 in Wuhan, China, there has been intense interest in understanding how SARS-CoV-2 emerged in the human population. Recent debate has coalesced around two competing ideas: a “laboratory escape” scenario and zoonotic emergence. Here, we critically review the current scientific evidence that may help clarify the origin of SARS-CoV-2. Computer readable versions of data tables, SVG maps, and acknowledgements of sequence data used are available from: https://github.com/sars-cov-2-origins/critical-review, Authors' final peer-reviewed version. Published as: https://doi.org/10.1016/j.cell.2021.08.017

Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3–12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5–12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2–19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.

Viruses closely related to human pathogens can reveal the origins of human infectious diseases. Human herpes simplexvirus type 1 (HSV-1) and type 2 (HSV-2) are hypothesized to have arisen via host-virus codivergence and cross-species transmission. We report the discovery of novel herpes simplexviruses during a large-scale screening of fecal samples from wild gorillas, bonobos, and chimpanzees. Phylogenetic analysis indicates that, contrary to expectation, simplexviruses from these African apes are all more closely related to HSV-2 than to HSV-1. Molecular clock-based hypothesis testing suggests the divergence between HSV-1 and the African great ape simplexviruses likely represents a codivergence event between humans and gorillas. The simplexviruses infecting African great apes subsequently experienced multiple cross-species transmission events over the past 3 My, the most recent of which occurred between humans and bonobos around 1 Ma. These findings revise our understanding of the origins of human herpes simplexviruses and suggest that HSV-2 is one of the earliest zoonotic pathogens.

Natural selection favors virulence when it is coupled with increased viral transmission

Molecular epidemiological analysis of viral pathogens can identify factors associated with increased transmission risk. We investigated the frequency of genetic clustering in a large dataset of NS34A, NS5A, and NS5B viral sequences from patients with chronic hepatitis C virus (HCV) genotypes 1–6 infection. Within a subset of patients with longitudinal samples, Receiver Operator Characteristic (ROC) analysis was applied which identified a threshold of 0.02 substitutions/site as most appropriate for clustering. From the 7,457 patients with chronic HCV infection included in this analysis, we inferred 256 clusters comprising 541 patients (7.3%). We found that HCV/HIV co-infection, young age, and high HCV viral load were all associated with increased clustering frequency, an indicator of increased transmission risk. In light of previous work on HCV/HIV co-infection in acute HCV cohorts, our results suggest that patients with HCV/HIV co-infection may disproportionately be the source of new HCV infections and treatment efforts should be geared towards elimination in this vulnerable population.

Purpose of review To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups. Recent findings Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks. Summary Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.

Summary Background Transgender women are among the groups at highest risk for HIV infection, with a prevalence of 27·7% in the USA; and despite this known high risk, undiagnosed infection is common in this population. We set out to identify transgender women and their partners in a molecular transmission network to prioritise public health activities. Methods Since 2006, HIV protease and reverse transcriptase gene (pol) sequences from drug resistance testing have been reported to the Los Angeles County Department of Public Health and linked to demographic data, gender, and HIV transmission risk factor data for each case in the enhanced HIV/AIDS Reporting System. We reconstructed a molecular transmission network by use of HIV-TRAnsmission Cluster Engine (with a pairwise genetic distance threshold of 0·015 substitutions per site) from the earliest pol sequences from 22 398 unique individuals, including 412 (2%) self-identified transgender women. We examined the possible predictors of clustering with multivariate logistic regression. We characterised the genetically linked partners of transgender women and calculated assortativity (the tendency for people to link to other people with the same attributes) for each transmission risk group. Findings 8133 (36·3%) of 22 398 individuals clustered in the network across 1722 molecular transmission clusters. Transgender women who indicated a sexual risk factor clustered at the highest frequency in the network, with 147 (43%) of 345 being linked to at least one other person (adjusted odds ratio [aOR] 2·0, p=0·0002). Transgender women were assortative in the network (assortativity 0·06, p Interpretation Clustering of transgender women and the observed tendency for linkage with cisgender men who did not identify as MSM, shows the potential to use molecular epidemiology both to identify clusters that are likely to include undiagnosed transgender women with HIV and to improve the targeting of public health prevention and treatment services to transgender women. Funding California HIV and AIDS Research Program and National Institutes of Health–National Institute of Allergy and Infectious Diseases.

Public health interviews (i.e., partner services), during which persons with diagnosed human immunodeficiency virus (HIV) infection name their sexual or needle-sharing partners (named partners), are used to identify HIV transmission networks to guide and prioritize HIV prevention activities. HIV sequence data, generated from provider-ordered drug resistance testing, can be used to understand characteristics of molecular clusters, a group of sequences for which each sequence is highly similar (linked) to all other sequences, and assess whether named partners are plausible HIV transmission partners. Although molecular data in higher HIV-morbidity states have been analyzed (1-3), few analyses exist for lower morbidity states (4), such as Wisconsin, which reported 4.6 HIV diagnoses per 100,000 persons aged ≥13 years in 2016 (5). The Wisconsin Division of Public Health (DPH) analyzed HIV sequence data generated from provider-ordered drug resistance testing and collected through routine HIV surveillance to identify molecular clusters and describe demographic and transmission risk characteristics among pairs of persons whose sequences were highly genetically similar (i.e., molecular linkages). In addition, overlap between partner linkages identified during public health interviews and molecular linkages was assessed. Overall, characteristics of molecular clusters in Wisconsin mirrored those from states with more HIV diagnoses, particularly in that most molecular linkages were observed among persons of the same race (78.2% of non-Hispanic blacks [blacks] linked to other blacks), the same transmission risk (90.2% of men who have sex with men [MSM] linked to other MSM), and the same age group (59.2% of persons aged 20-29 years linked to other persons aged 20-29 years). Among named partner linkages identified during interviews in which both persons also had a reported sequence, overlap of named partner and molecular linkages was moderate: 33.8% of named partners were plausible transmission partners according to available molecular data. Analysis of HIV sequence data is a useful tool for characterizing transmission patterns not immediately apparent using traditional public health interview data, even in a state with lower HIV morbidity. Prevention recommendations generated from national data (e.g., targeting preexposure prophylaxis for HIV-negative persons at high risk and implementing measures to maintain viral suppression among persons with HIV infection) also are relevant in a lower HIV-morbidity state.

BACKGROUND: Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States. METHODS: We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using two genetic distance thresholds (0.5% and 1.5%) and two time periods for diagnoses (all years and 2013–2015, i.e., recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies. RESULTS: A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5–13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years. CONCLUSIONS: Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.